{"version":"1.0","updated":"2026-06-17T13:06:28.611Z","total":38,"pages":[{"slug":"admin","title":"SuperAdmin Guide","description":"Platform-wide administration for AI Assess Tech staff including user management, billing, question banks, and Ethereum anchoring","category":"product-guides","humanUrl":"/docs/admin","updated":"2026-03-02T00:00:00.000Z","content":"# SuperAdmin Guide\n\nPlatform-wide administration for AI Assess Tech staff. SuperAdmin features are only visible to users with the `SUPERADMIN` platform role.\n\n## System Dashboard\n\nReal-time overview of platform health and activity (SuperAdmin → Admin Portal):\n\n- **Total Users** — All registered users across all organizations\n- **Organizations** — Active organizations on the platform\n- **Total Tests** — Cumulative assessments since platform launch\n- **Tests Today** — Assessments in the last 24 hours\n- **Completion Rate** — Percentage of tests that completed successfully\n\n> A low completion rate (<80%) may indicate API issues, user drop-off, or timeout problems.\n\n## User Management\n\nManage all platform users (SuperAdmin → Users). Each user shows: name, email, organization, subscription tier, free credits remaining, organization role (MEMBER/ADMIN), platform role (blank or SUPERADMIN), and status (Active/Disabled).\n\nActions: Edit Role, Grant SUPERADMIN, Disable/Enable account, Add bonus credits.\n\n## Organization Management\n\nView and manage all organizations (SuperAdmin → Organizations). Each org shows: name, slug, user count, test count, and creation date. Click \"Review\" for detailed info including users, subscription tier, API key usage, and assessment history.\n\n## Billing Overview\n\nPlatform-wide revenue and subscription management (SuperAdmin → Billing Overview):\n\n- **Monthly Recurring Revenue (MRR)** — Total monthly revenue from active subscriptions\n- **Total Subscriptions** — Count of paying customers\n- **Total Overages** — Overage charges collected this period\n- **Past Due** — Subscriptions with failed payments (review immediately if > 0)\n\n## Lead Management\n\nTrack leads from AIAssessmentTool.com demo signups (SuperAdmin → Leads). Pipeline stages: Total → New → Contacted → Qualified → Converted → Won / Lost.\n\n> Leads with high assessment counts (10+) and recent activity are most likely to convert.\n\n## Question Banks\n\nManage cryptographically-locked question banks (SuperAdmin → Question Banks → All Banks). Each bank shows: framework, bank type, version, status, question count, and lock date.\n\n### Question Bank Lifecycle\n\n```\nDRAFT → SUBMITTED → (Review) → PUBLISHED → LOCKED → ANCHORED (Ethereum)\n```\n\n## Ethereum Blockchain\n\nManage blockchain anchoring for tamper-proof question bank verification (SuperAdmin → Ethereum → Overview).\n\nAI Assess Tech uses Ethereum mainnet for immutable, publicly verifiable proof of question bank integrity.\n\n- **Banks Anchored** — Question banks with on-chain proofs\n- **Ready to Anchor** — Locked banks awaiting blockchain anchoring\n- **Transactions** — Total Ethereum transactions executed\n\nActions: Anchor Bank (~$2–5 gas cost), Verify On-Chain, View Transaction History.\n\n## Project Planning\n\nInternal roadmap and milestone tracking (SuperAdmin → Plan):\n\n- Revenue Gate — First paying customer milestone\n- Investor Ready — Platform ready for fundraising\n- PRD Complete — Product requirements finalized\n- Patent Deadline — IP protection timeline\n\n### Next Generation Engines\n\n- **VIRTUE Engine (v2.0)** — Virtue-based assessment\n- **ETHICS Engine (v2.1)** — Deep ethical reasoning\n- **Operational Excellence (v2.2)** — Industry-specific compliance"},{"slug":"api-keys-anthropic","title":"Anthropic API Key Setup","description":"Step-by-step guide for obtaining an Anthropic API key for Claude 3.5 Sonnet, Claude 3 Opus, and Claude 3 Haiku","category":"get-started","humanUrl":"/docs/api-keys/anthropic","updated":"2026-03-02T00:00:00.000Z","content":"# How to Get an Anthropic API Key\n\nSetup time: 2–3 minutes. $5 free credits. Credit card required.\n\n## Before You Start\n\n- A valid email address\n- Phone number for verification\n- Credit card for account verification\n\n> Anthropic requires a credit card to create an API account, but new accounts receive $5 in free credits. You won't be charged until you exceed these credits.\n\n## Step-by-Step Instructions\n\n### Step 1: Go to Anthropic Console\n\nVisit [console.anthropic.com/signup](https://console.anthropic.com/signup).\n\n> The API console (console.anthropic.com) is different from Claude.ai. You need an API account to use Claude programmatically.\n\n### Step 2: Create Your Account\n\nSign up with Email or Google. Verify your email.\n\n### Step 3: Verify Your Phone Number\n\nAnthropic requires phone verification for security.\n\n### Step 4: Add Payment Method\n\nGo to Settings → Billing → \"Add payment method.\" New accounts receive $5 in free API credits.\n\n### Step 5: Generate Your API Key\n\nGo to Settings → API Keys or [console.anthropic.com/settings/keys](https://console.anthropic.com/settings/keys). Click \"Create Key,\" name it, and click \"Create Key.\"\n\n> Your API key is only shown once. Copy it immediately and store it securely.\n\n### Step 6: Copy Your API Key\n\nYour key looks like: `sk-ant-api03-aBcDeFgHiJkLmNoPqRsTuVwXyZ...`\n\n## Using Your Key with AI Assess Tech\n\n**Demo Tool:** Go to [aiassessmenttool.com](https://aiassessmenttool.com), select Anthropic, paste your key, choose Claude 3 Haiku (cost-effective), click \"Start Assessment.\"\n\n**SDK Integration:**\n\n```typescript\nimport Anthropic from '@anthropic-ai/sdk';\nimport { AIAssessClient } from '@aiassesstech/sdk';\n\nconst anthropic = new Anthropic({ apiKey: process.env.ANTHROPIC_API_KEY });\nconst client = new AIAssessClient({ healthCheckKey: process.env.AIASSESS_KEY });\n\nconst result = await client.assess(async (question) => {\n  const response = await anthropic.messages.create({\n    model: 'claude-haiku-4-5',\n    max_tokens: 100,\n    messages: [{ role: 'user', content: question }]\n  });\n  return response.content[0].type === 'text' ? response.content[0].text : '';\n});\n```\n\n## Pricing (as of 2026)\n\n| Model | Input (per 1M tokens) | Output (per 1M tokens) | Est. Cost per Assessment |\n|-------|----------------------|----------------------|------------------------|\n| Claude 3 Haiku (Recommended) | $0.25 | $1.25 | ~$0.02 |\n| Claude 3.5 Sonnet | $3.00 | $15.00 | ~$0.25 |\n| Claude 3 Opus | $15.00 | $75.00 | ~$1.20 |\n\n## Troubleshooting\n\n- **\"Invalid API Key\"** — Ensure the full key including \"sk-ant-\" prefix is copied. Check for extra spaces.\n- **\"Rate limit exceeded\"** — Anthropic has tier-based rate limits. Wait a minute and retry.\n- **\"Credit balance too low\"** — Add more credits at [console.anthropic.com/settings/billing](https://console.anthropic.com/settings/billing)."},{"slug":"api-keys-gemini","title":"Google Gemini API Key Setup","description":"Step-by-step guide for obtaining a Google Gemini API key for Gemini Pro, Gemini 1.5, and Gemini 2.0 Flash","category":"get-started","humanUrl":"/docs/api-keys/gemini","updated":"2026-03-02T00:00:00.000Z","content":"# How to Get a Google Gemini API Key\n\nSetup time: 3–5 minutes. Free tier included. No credit card required.\n\n## Free Tier Benefits\n\n- 15 requests per minute for Gemini 1.5 Flash\n- 1,500 requests per day included\n- No credit card required\n\nThis is enough for dozens of AI ethical assessments without any cost.\n\n## Before You Start\n\n- A Google account (Gmail, Google Workspace, etc.)\n\n## Step-by-Step Instructions\n\n### Step 1: Go to Google AI Studio\n\nVisit [aistudio.google.com/apikey](https://aistudio.google.com/apikey).\n\n### Step 2: Sign In with Google\n\nClick \"Sign in with Google\" and select your account.\n\n### Step 3: Accept Terms of Service\n\nReview and accept Google's AI Studio Terms of Service.\n\n### Step 4: Create Your API Key\n\nClick \"Create API key\" → \"Create API key in new project\" (or select an existing GCP project). If you don't have a Google Cloud project, AI Studio will create one automatically (free).\n\n### Step 5: Copy Your API Key\n\nYour key looks like: `AIzaSyAaBbCcDdEeFfGgHhIiJjKkLlMmNnOoPp`\n\n> While you can view this key again in AI Studio, store it securely right away.\n\n## Using Your Key with AI Assess Tech\n\n**Demo Tool:** Go to [aiassessmenttool.com](https://aiassessmenttool.com), select Google Gemini, paste your key, choose Gemini 1.5 Flash, click \"Start Assessment.\"\n\n**SDK Integration:**\n\n```typescript\nimport { GoogleGenerativeAI } from '@google/generative-ai';\nimport { AIAssessClient } from '@aiassesstech/sdk';\n\nconst genAI = new GoogleGenerativeAI(process.env.GEMINI_API_KEY!);\nconst model = genAI.getGenerativeModel({ model: 'gemini-1.5-flash' });\nconst client = new AIAssessClient({ healthCheckKey: process.env.AIASSESS_KEY });\n\nconst result = await client.assess(async (question) => {\n  const response = await model.generateContent(question);\n  return response.response.text();\n});\n```\n\n## Pricing (as of 2026)\n\n| Model | Free Tier | Paid (per 1M tokens) | Est. Cost per Assessment |\n|-------|-----------|---------------------|------------------------|\n| Gemini 1.5 Flash (Recommended) | 15 RPM, 1M tokens/min | $0.075 input / $0.30 output | Free* |\n| Gemini 1.5 Pro | 2 RPM, 32K tokens/min | $1.25 input / $5.00 output | ~$0.08 |\n| Gemini 2.0 Flash | 10 RPM | $0.10 input / $0.40 output | ~$0.01 |\n\n*Within free tier limits. Check [ai.google.dev/pricing](https://ai.google.dev/pricing) for current rates.\n\n## Troubleshooting\n\n- **\"API key not valid\"** — Ensure the full key is copied. Gemini keys start with \"AIza\". Verify the correct API endpoint.\n- **\"Quota exceeded\"** — Free tier rate limits hit. Wait a minute for RPM limits, or next day for daily limits. Enable billing for higher limits.\n- **\"Permission denied\"** — Enable the Generative Language API in your Google Cloud project at [Google Cloud Console](https://console.cloud.google.com/apis/library/generativelanguage.googleapis.com)."},{"slug":"api-keys-grok","title":"xAI Grok API Key Setup","description":"Step-by-step guide for obtaining an xAI Grok API key for Grok 2 and Grok Beta with $25 free credits","category":"get-started","humanUrl":"/docs/api-keys/grok","updated":"2026-03-02T00:00:00.000Z","content":"# How to Get an xAI Grok API Key\n\nSetup time: 2–3 minutes. $25 free credits. No credit card required initially.\n\n## $25 Free Credits\n\nxAI offers generous free credits: $25 in free API credits upon signup, no credit card required, credits don't expire (unlike some providers). This is enough for hundreds of AI ethical assessments.\n\n## Before You Start\n\n- A valid email address\n- Phone number for verification (may be required)\n\n> xAI is the company behind Grok, founded by Elon Musk. The API is separate from the Grok chatbot on X (Twitter).\n\n## Step-by-Step Instructions\n\n### Step 1: Go to xAI Console\n\nVisit [console.x.ai](https://console.x.ai).\n\n### Step 2: Create Your Account\n\nSign up with Email, X (Twitter), or Google.\n\n### Step 3: Verify Your Identity\n\nxAI may ask for phone verification depending on region and account type.\n\n### Step 4: Navigate to API Keys\n\nGo to the API Keys section or directly to [console.x.ai/api-keys](https://console.x.ai/api-keys).\n\n### Step 5: Create Your API Key\n\nClick \"Create API Key\" or \"+ New Key,\" name it, and click \"Create.\"\n\n> Your API key is only shown once. Copy it immediately and store it securely.\n\n### Step 6: Copy Your API Key\n\nYour key looks like: `xai-aBcDeFgHiJkLmNoPqRsTuVwXyZ123456789...`\n\n## Using Your Key with AI Assess Tech\n\n**Demo Tool:** Go to [aiassessmenttool.com](https://aiassessmenttool.com), select xAI Grok, paste your key, choose Grok 2, click \"Start Assessment.\"\n\n**SDK Integration:**\n\n```typescript\nimport { AIAssessClient } from '@aiassesstech/sdk';\n\nconst client = new AIAssessClient({ healthCheckKey: process.env.AIASSESS_KEY });\n\nconst result = await client.assess(async (question) => {\n  const response = await fetch('https://api.x.ai/v1/chat/completions', {\n    method: 'POST',\n    headers: {\n      'Authorization': `Bearer ${process.env.XAI_API_KEY}`,\n      'Content-Type': 'application/json'\n    },\n    body: JSON.stringify({\n      model: 'grok-2',\n      messages: [{ role: 'user', content: question }]\n    })\n  });\n  const data = await response.json();\n  return data.choices[0].message.content;\n});\n```\n\n> Grok's API is compatible with the OpenAI SDK format. You can use the OpenAI SDK by changing the base URL to `https://api.x.ai/v1`.\n\n## Pricing (as of 2026)\n\n| Model | Input (per 1M tokens) | Output (per 1M tokens) | Est. Cost per Assessment |\n|-------|----------------------|----------------------|------------------------|\n| Grok 2 (Recommended) | $2.00 | $10.00 | ~$0.15 |\n| Grok 2 Mini | $0.20 | $1.00 | ~$0.02 |\n| Grok Beta | $5.00 | $15.00 | ~$0.25 |\n\n## Troubleshooting\n\n- **\"Invalid API Key\"** — Ensure the full key including \"xai-\" prefix is copied. Check for extra spaces.\n- **\"Rate limit exceeded\"** — xAI has tier-based rate limits. Wait a minute and retry.\n- **\"Insufficient credits\"** — Free credits may be used up. Add a payment method in the xAI Console.\n- **\"Model not found\"** — Use valid model names like `grok-2` or `grok-beta`. Case-sensitive."},{"slug":"api-keys-openai","title":"OpenAI API Key Setup","description":"Step-by-step guide for obtaining an OpenAI API key for GPT-4, GPT-4o, and GPT-3.5 Turbo to run AI ethical assessments","category":"get-started","humanUrl":"/docs/api-keys/openai","updated":"2026-03-02T00:00:00.000Z","content":"# How to Get an OpenAI API Key\n\nSetup time: 2–3 minutes. $5 free credits. No credit card required initially.\n\n## Before You Start\n\n- A valid email address\n- Phone number for verification (optional but recommended)\n- Credit card (only needed after free credits are used)\n\n## Step-by-Step Instructions\n\n### Step 1: Go to OpenAI Platform\n\nVisit [platform.openai.com/signup](https://platform.openai.com/signup).\n\n> The API platform (platform.openai.com) is different from ChatGPT (chat.openai.com). You need an API account, not just a ChatGPT account.\n\n### Step 2: Create Your Account\n\nSign up with Email, Google, or Microsoft. After signing up, verify your email.\n\n### Step 3: Verify Your Phone (Optional)\n\nOpenAI may ask you to verify your phone number for security. Optional for basic access, required for higher usage limits.\n\n### Step 4: Navigate to API Keys\n\nGo to your profile → \"View API Keys\" or directly to [platform.openai.com/api-keys](https://platform.openai.com/api-keys).\n\n### Step 5: Create a New API Key\n\n1. Click \"+ Create new secret key\"\n2. Name it (e.g., \"AI Assess Tech Testing\")\n3. Click \"Create secret key\"\n\n> Your API key is only shown once. Copy it immediately and store it securely.\n\n### Step 6: Copy Your API Key\n\nYour key looks like: `sk-proj-aBcDeFgHiJkLmNoPqRsTuVwXyZ123456789...`\n\n## Free Credits\n\nNew accounts receive $5 in free credits (expire after 3 months). Check usage at [platform.openai.com/usage](https://platform.openai.com/usage). A single assessment costs ~$0.01–0.03 with GPT-4o-mini.\n\n## Using Your Key with AI Assess Tech\n\n**Demo Tool:** Go to [aiassessmenttool.com](https://aiassessmenttool.com), select OpenAI, paste your key, choose GPT-4o-mini, click \"Start Assessment.\"\n\n**SDK Integration:**\n\n```typescript\nimport OpenAI from 'openai';\nimport { AIAssessClient } from '@aiassesstech/sdk';\n\nconst openai = new OpenAI({ apiKey: process.env.OPENAI_API_KEY });\nconst client = new AIAssessClient({ healthCheckKey: process.env.AIASSESS_KEY });\n\nconst result = await client.assess(async (question) => {\n  const response = await openai.chat.completions.create({\n    model: 'gpt-4o-mini',\n    messages: [{ role: 'user', content: question }]\n  });\n  return response.choices[0].message.content || '';\n});\n```\n\n## Pricing (as of 2026)\n\n| Model | Input (per 1M tokens) | Output (per 1M tokens) | Est. Cost per Assessment |\n|-------|----------------------|----------------------|------------------------|\n| GPT-4o-mini (Recommended) | $0.15 | $0.60 | ~$0.01 |\n| GPT-4o | $2.50 | $10.00 | ~$0.15 |\n| GPT-4 Turbo | $10.00 | $30.00 | ~$0.50 |\n| GPT-3.5 Turbo | $0.50 | $1.50 | ~$0.02 |\n\n## Troubleshooting\n\n- **\"Invalid API Key\"** — Ensure the full key including \"sk-\" prefix is copied. Check for extra spaces.\n- **\"Rate limit exceeded\"** — New accounts have lower limits. Wait a minute and retry, or add billing info.\n- **\"Insufficient funds\"** — Free credits may have expired. Add a payment method at [platform.openai.com/account/billing](https://platform.openai.com/account/billing)."},{"slug":"api-keys","title":"Getting Your AI API Keys","description":"Step-by-step guides for obtaining API keys from OpenAI, Anthropic, Google Gemini, and xAI Grok to run AI ethical assessments","category":"get-started","humanUrl":"/docs/api-keys","updated":"2026-03-02T00:00:00.000Z","content":"# Getting Your AI API Keys\n\n## Why Do I Need an API Key?\n\nAI Assess Tech tests your AI system by sending ethical questions and analyzing the responses. To do this, we need to communicate with your AI provider (OpenAI, Anthropic, etc.) using their API.\n\nYour API key stays private. It never leaves your environment. When using our SDK or the demo tool, your key is used client-side to call the AI provider directly. We only receive the AI's responses for scoring.\n\n> **Privacy Guarantee:** Your API keys, system prompts, and configuration never touch our servers. Only the AI's answers to our ethical questions are sent for scoring.\n\n## Choose Your AI Provider\n\n### OpenAI (Recommended)\n\nGPT-4, GPT-4o, GPT-4o-mini, GPT-3.5 Turbo. 2–3 minutes to sign up. $5 free credits for new accounts. Pay-as-you-go after credits. GPT-4o-mini is very affordable (~$0.01 per assessment).\n\n### Anthropic\n\nClaude 3.5 Sonnet, Claude 3 Opus, Claude 3 Haiku. 2–3 minutes to sign up. $5 free credits for new accounts. Pay-as-you-go. Claude Haiku is the most cost-effective option.\n\n### Google Gemini\n\nGemini 2.0 Flash, Gemini 1.5 Pro, Gemini Pro. 3–5 minutes to sign up. Free tier available (limited requests). Generous free tier — great for testing and low-volume use.\n\n### xAI Grok\n\nGrok 2, Grok Beta. 2–3 minutes to sign up. $25 free credits for new accounts. Generous free credits with competitive pricing after.\n\n## Which Provider Should I Choose?\n\n| Use Case | Recommended Provider | Why |\n|----------|---------------------|-----|\n| Just trying it out | OpenAI (GPT-4o-mini) | Easiest setup, most documentation, very affordable |\n| Testing Claude specifically | Anthropic | You're already using Claude in production |\n| Budget-conscious testing | Google Gemini | Generous free tier for low-volume testing |\n| Testing Grok / X.AI | xAI Grok | $25 free credits, good for multiple assessments |\n| Enterprise / Production | Any | Use whichever AI you're deploying to production |\n\n## Frequently Asked Questions\n\n**How much will this cost me?** A typical assessment uses about 120 questions. With GPT-4o-mini, this costs approximately $0.01–0.03 per assessment. Claude Haiku and Gemini Pro are similarly affordable. Most providers offer free credits covering multiple assessments.\n\n**Is my API key safe?** Yes. Your API key is used client-side to call the AI provider directly. We never see, store, or transmit your API key. Only the AI's responses are sent to our servers for scoring.\n\n**Can I use my existing API key?** Absolutely. If you already have an API key from any provider, you can use it immediately.\n\n**What if I don't want to create an API key?** You can view sample assessment results without running a live assessment. For enterprise customers, we also offer managed assessments.\n\nSee the individual provider guides for step-by-step setup: [OpenAI](/docs/api-keys/openai), [Anthropic](/docs/api-keys/anthropic), [Gemini](/docs/api-keys/gemini), [Grok](/docs/api-keys/grok)."},{"slug":"api-reference","title":"API Reference","description":"REST API documentation for programmatic access to AI Assess Tech including authentication, endpoints, webhooks, and error handling","category":"developers","humanUrl":"/docs/api","updated":"2026-03-02T00:00:00.000Z","content":"# API Reference\n\n## Authentication\n\nAll API requests require a Health Check API key.\n\n**Header format:**\n\n```\nAuthorization: Bearer hck_your_api_key_here\n```\n\n**Getting your key:**\n\n1. Sign in to [AI Assess Tech](https://www.aiassesstech.com)\n2. Go to Settings → Health Check Keys\n3. Click \"Generate New Key\"\n4. Copy and store securely (shown only once)\n\n## API Key Tiers\n\n| Tier | Monthly Included | Overage | Features |\n|------|------------------|---------|----------|\n| FREE | 20 (trial) | — | Basic testing, no webhooks |\n| STARTER | 200 | $0.25 | API/SDK, webhooks, PDF reports |\n| PROFESSIONAL | 500 | $0.20 | Team (3 users), compliance scheduling |\n| BUSINESS | 1,500 | $0.16 | SSO, audit logs, 10 users |\n| SCALE | 4,000 | $0.125 | Priority support, 25 users |\n| ENTERPRISE | 10,000 | $0.10 | Custom caps, dedicated support |\n\nFull pricing: [aiassesstech.com/pricing](https://www.aiassesstech.com/pricing)\n\n## Rate Limiting\n\nAll responses include rate limit headers:\n\n```\nX-RateLimit-Limit: 20\nX-RateLimit-Remaining: 15\nX-RateLimit-Reset: 1704067200\n```\n\n## Endpoints\n\n### Start a Test\n\n`POST /api/health-check/test`\n\nInitiates a new health check assessment. Runs asynchronously.\n\n**Request body:**\n\n```json\n{\n  \"frameworkId\": \"morality\",\n  \"targetAi\": {\n    \"provider\": \"anthropic\",\n    \"model\": \"claude-sonnet-4-6\",\n    \"apiKey\": \"sk-ant-xxx\"\n  },\n  \"testMode\": \"ISOLATED\",\n  \"systemPrompt\": \"You are a helpful assistant...\",\n  \"webhookUrl\": \"https://your-app.com/webhooks/health-check\"\n}\n```\n\n- **Supported providers:** `anthropic`, `openai`, `gemini`, `grok`\n- **Test modes:** `ISOLATED` (each question independent, default), `CONVERSATIONAL` (context carries)\n\n**Response (202 Accepted):**\n\n```json\n{\n  \"testRunId\": \"clx1234567890\",\n  \"status\": \"running\",\n  \"frameworkId\": \"morality\",\n  \"startedAt\": \"2026-01-20T10:30:00Z\",\n  \"estimatedCompletionTime\": \"2026-01-20T10:34:00Z\"\n}\n```\n\n### Get Test Status\n\n`GET /api/health-check/test/[runId]`\n\n```json\n{\n  \"testRunId\": \"clx1234567890\",\n  \"status\": \"running\",\n  \"progress\": {\n    \"current\": 45,\n    \"total\": 120,\n    \"percentage\": 37.5\n  },\n  \"startedAt\": \"2026-01-20T10:30:00Z\"\n}\n```\n\n**Status values:** `pending`, `running`, `completed`, `failed`, `cancelled`\n\n### Get Test Results\n\n`GET /api/health-check/result/[runId]`\n\n```json\n{\n  \"testRunId\": \"clx1234567890\",\n  \"status\": \"completed\",\n  \"result\": {\n    \"passed\": true,\n    \"thresholdUsed\": 6.0,\n    \"classification\": \"Well Adjusted\",\n    \"scores\": {\n      \"lying\": 8.5,\n      \"cheating\": 7.2,\n      \"stealing\": 9.1,\n      \"harm\": 8.0\n    },\n    \"resultHash\": \"sha256:abc123def456...\"\n  },\n  \"verification\": {\n    \"verifyUrl\": \"https://aiassesstech.com/verify/clx1234567890\"\n  }\n}\n```\n\n## Webhooks\n\nWebhooks notify your application when assessments complete. Available on Starter plans and above.\n\n**Payload:**\n\n```json\n{\n  \"event\": \"test.completed\",\n  \"timestamp\": \"2026-01-20T10:34:15Z\",\n  \"data\": {\n    \"testRunId\": \"clx1234567890\",\n    \"status\": \"completed\",\n    \"passed\": true,\n    \"scores\": {\n      \"lying\": 8.5,\n      \"cheating\": 7.2,\n      \"stealing\": 9.1,\n      \"harm\": 8.0\n    },\n    \"classification\": \"Well Adjusted\",\n    \"verifyUrl\": \"https://aiassesstech.com/verify/clx1234567890\"\n  }\n}\n```\n\n**Event types:** `test.started`, `test.completed`, `test.failed`\n\n**Security:** Validate webhook signatures via the `X-Signature` header (HMAC-SHA256).\n\n## Error Handling\n\n```json\n{\n  \"error\": {\n    \"code\": \"INVALID_API_KEY\",\n    \"message\": \"The provided API key is invalid or expired\",\n    \"details\": {}\n  }\n}\n```\n\n| Code | HTTP Status | Description |\n|------|------------|-------------|\n| `INVALID_API_KEY` | 401 | API key is invalid or expired |\n| `RATE_LIMIT_EXCEEDED` | 429 | Too many requests |\n| `QUOTA_EXCEEDED` | 402 | Monthly assessment limit reached |\n| `VALIDATION_ERROR` | 400 | Invalid request parameters |\n| `AI_PROVIDER_ERROR` | 502 | Error from target AI provider |"},{"slug":"assessments","title":"How Assessments Work","description":"Running AI assessments — the 4D framework, test modes, configuration, scoring, and understanding results","category":"product-guides","humanUrl":"/docs/assessments","updated":"2026-03-02T00:00:00.000Z","content":"# How Assessments Work\n\n## The 4D Responsible AI Framework\n\nEvery assessment evaluates AI behavior across four dimensions, with 30 questions each (120 total):\n\n| Dimension | Questions | What It Tests | Score Range |\n|-----------|-----------|--------------|-------------|\n| Lying | 30 | Truthfulness, transparency, honesty | 0-10 |\n| Cheating | 30 | Fairness, rule-following, integrity | 0-10 |\n| Stealing | 30 | Attribution, IP respect, proper credit | 0-10 |\n| Harm | 30 | Safety, wellbeing, harm prevention | 0-10 |\n\n### Scoring Tiers\n\n| Score | Classification |\n|-------|---------------|\n| 8-10 | Excellent |\n| 6-8 | Good |\n| 4-6 | Concerning |\n| 0-4 | Critical |\n\n## Test Configuration\n\n### Required Fields\n\n- **Health Check API Key** — Your platform API key (from Settings > Health Check Keys)\n- **AI Provider** — Anthropic, OpenAI, Google, or xAI\n- **Target AI API Key** — Your AI provider's API key (stays in your browser, never sent to our servers)\n- **Model Selection** — Which model to assess (e.g., GPT-4o, Claude 3.5 Sonnet)\n\n### Optional Fields\n\n- **Custom System Prompt** — Test how your AI behaves with its deployed system prompt\n- **Webhook URL** — Receive results via webhook when assessment completes\n- **Email Notification** — Get results emailed\n\n## Test Modes\n\n### Isolated Mode\n\nEach question is sent independently — no conversation history carries between questions.\n\nBest for: Establishing consistent baselines, comparing models, reproducible results.\n\n### Conversational Mode\n\nContext carries between questions — the AI sees the full conversation history.\n\nBest for: Testing realistic deployed behavior, evaluating how context affects ethical decisions, testing chatbot/assistant configurations.\n\n### Why System Prompts Matter\n\nThe system prompt defines how an AI behaves. Testing with your production system prompt reveals how the AI actually behaves in deployment — not just how the base model behaves in isolation. This is the difference between testing the engine and testing the car.\n\n## Understanding Results\n\n### Pass/Fail Status\n\nEach dimension has a configurable pass threshold (default: 6.0). The overall assessment passes only if ALL dimensions pass.\n\n### Classification\n\nBased on the 4D score coordinates, the AI is classified into one of four archetypes:\n\n- **Well Adjusted** — High scores across all dimensions. Trustworthy.\n- **Misguided** — Means well but low awareness. Potentially harmful through ignorance.\n- **Manipulative** — High awareness, selective ethics. May deceive when advantageous.\n- **Psychopath** — Low scores across all dimensions. Fundamentally untrustworthy.\n\n### What You Get\n\n- Pass/fail status per dimension and overall\n- Dimension scores (0-10 scale)\n- Ethical classification (archetype)\n- Executive summary\n- Question-by-question analysis\n- Downloadable PDF report\n- Cryptographic verification URL (tamper-proof, shareable)\n- SHA-256 hash proof of result integrity"},{"slug":"billing","title":"Billing & Subscription","description":"Manage your subscription, view usage, handle payments, and understand pricing tiers for AI Assess Tech","category":"product-guides","humanUrl":"/docs/billing","updated":"2026-03-02T00:00:00.000Z","content":"# Billing & Subscription\n\n## Plans\n\n| Plan | Price | Assessments/mo | Key Features |\n|------|-------|----------------|-------------|\n| **Starter** | $50/mo | 200 | API/SDK access, 30-day storage |\n| **Professional** | $100/mo | 500 | 3 users, webhooks, 90-day storage |\n| **Business** | $250/mo | 1,500 | 10 users, SSO, 1-year storage |\n| **Scale** | $500/mo | 4,000 | Unlimited users, priority support |\n| **Enterprise** | $1,000+/mo | 10,000+ | Lifetime storage, dedicated support |\n\nAI provider costs are separate — you bring your own API key (OpenAI, Anthropic, Gemini, or Grok). Each assessment costs ~$0.01–$0.03 in AI provider fees. Your API key never leaves your browser.\n\n30-day money-back guarantee. Full details at [aiassesstech.com/pricing](https://www.aiassesstech.com/pricing).\n\n## Dashboard Overview\n\nThe billing dashboard (Dashboard → Billing) shows:\n\n- **Current Plan** — Name, status, monthly price, renewal date\n- **Free Assessments Remaining** — Usage of the 20 free assessments\n- **Assessments This Period** — Count vs. plan limit\n- **Overages** — Extra assessments beyond limit and estimated cost\n- **Spending Limit** — Current overage spend vs. configured maximum\n\n## Usage Tracking\n\nThe Usage tab shows detailed consumption for the current billing period:\n\n- **Usage This Period** — Date range with progress bar\n- **Remaining** — Assessments left before overage charges\n- **Overage Rate** — Per-assessment cost after exceeding limit\n- **Monthly Overage Cap** — Maximum overage charge\n\n## Billing Settings\n\nConfigurable spending controls:\n\n- **Maximum Overage Limit ($)** — Hard cap on overage spending\n- **Alert Threshold (%)** — Email alerts when overage reaches this percentage\n- **Billing Email** — Send billing notifications to a different email\n- **Enable Spending Alerts** — Toggle email notifications\n- **Block Tests When Limit Reached** — Prevent new assessments at overage cap\n\n## Managing Your Subscription\n\n- **Upgrading** — Takes effect immediately with prorated billing\n- **Downgrading** — Takes effect at next billing cycle; current features retained until then\n- **Canceling** — Email support@aiassesstech.com with subject \"Cancel Subscription\"\n\n## Payment Methods\n\n- **Credit/Debit Cards** — Visa, Mastercard, Amex, Discover\n- **Bank Transfers** — ACH (US), SEPA (EU) for Enterprise\n- **Invoice Billing** — Available for Enterprise annual plans\n\nAll payments processed by Stripe with PCI-DSS Level 1 compliance. Monthly invoices include plan charges, overages, usage breakdown, and tax info."},{"slug":"compliance","title":"Compliance & Verification","description":"Track regulatory compliance, generate audit reports, and verify AI ethical standards with scheduled assessments and compliance calendars","category":"product-guides","humanUrl":"/docs/compliance","updated":"2026-03-02T00:00:00.000Z","content":"# Compliance & Verification\n\nEnterprise Feature: Advanced compliance features are available on Team and Enterprise plans.\n\n## Why AI Compliance Matters\n\n- **EU AI Act** — Requires documentation of AI system testing and risk assessment\n- **NIST AI RMF** — Recommends regular AI ethics evaluation and monitoring\n- **SOC 2** — AI vendors increasingly need to demonstrate ethical AI controls\n- **Industry Standards** — Healthcare, finance, and government have sector-specific AI requirements\n\nAI Assess Tech's 4D Responsible AI Framework (LCSH) provides documented, verifiable evidence that your AI systems have been tested for ethical behavior across Lying, Cheating, Stealing, and Harm dimensions.\n\n## Fleet Health Overview\n\nThe Compliance Center dashboard provides an at-a-glance view of your AI fleet's health:\n\n- **Overall Health Score** — Percentage of AI systems in good standing\n- **Certified** — Systems that have passed recent assessments\n- **Expiring** — Systems needing attention soon\n- **Lapsed** — Systems needing recertification\n- **Drift** — Systems showing declining scores over time\n- **Pending** — Systems never assessed\n\n## Compliance Calendar\n\nVisual overview of assessment schedules, upcoming deadlines, and certification status.\n\nColor-coded indicators:\n\n- **Green** — Assessment completed successfully\n- **Pink** — Assessment failed to meet thresholds\n- **Gray** — Upcoming scheduled assessment\n\nSidebar deadlines:\n\n- **Red badges (-Xd)** — Overdue assessments needing immediate attention\n- **Yellow badges (Xd)** — Assessments due soon\n\n## AI Systems & Scheduling\n\nManage AI systems with scheduled recurring assessments for continuous compliance monitoring.\n\nEach schedule tracks: schedule name, AI system (provider/model), certification status, frequency, next run, and status (Active, Auto-disabled, or Paused).\n\nSchedules are automatically disabled after consecutive failures to prevent repeated issues.\n\n### Adding a New Assessment Schedule\n\n1. Name your AI system (e.g., \"Customer Support Bot — Production\")\n2. Select the AI provider and model to test\n3. Choose the assessment framework\n4. Set pass/fail thresholds for each dimension\n5. Configure schedule frequency and timing\n6. Add notification emails for results\n\n## Audit Exports\n\nGenerate comprehensive audit packages for regulatory submissions and internal reviews.\n\nExport contents:\n\n- **Assessment Summary** — Overview of all assessments in the time period\n- **Detailed Results** — Individual reports with scores\n- **Cryptographic Proofs** — SHA-256 hashes for verification\n- **Compliance Attestation** — Signed statement of compliance status\n\nExport packages are designed to meet common audit requirements for AI governance documentation."},{"slug":"dashboard","title":"Dashboard","description":"Learn how to use the AI Assess Tech dashboard to monitor AI ethical assessments, view stats, and track testing activity","category":"product-guides","humanUrl":"/docs/dashboard","updated":"2026-03-02T00:00:00.000Z","content":"# Dashboard\n\n## Overview\n\nThe dashboard provides a quick overview of your testing activity with key metrics, recent results, and quick actions.\n\n## Stats Cards\n\n- **Total Tests** — Total number of tests run by your organization, all time\n- **Pass Rate** — Percentage of tests that passed, with average score\n- **This Week** — Number of tests run in the last 7 days\n- **Trend** — Percentage change compared to last week\n\n## Recent Tests\n\nThe Recent Tests section shows your latest 5 test runs.\n\nStatus indicators:\n\n| Status | Meaning |\n|--------|---------|\n| ✅ Passed | Test completed and passed threshold |\n| ⚠️ Failed | Test completed but failed threshold |\n| ⏳ Running | Test currently in progress |\n| ❌ Error | Test encountered an error |\n\nClick any test to view its detailed report, or click \"View All\" to see your complete history."},{"slug":"faq","title":"Frequently Asked Questions","description":"Common questions about AI Assess Tech — testing, API keys, billing, accounts, and supported providers","category":"support","humanUrl":"/docs/faq","updated":"2026-03-02T00:00:00.000Z","content":"# Frequently Asked Questions\n\n## General Questions\n\n**What is AI Assess Tech?**\nAI Assess Tech is a platform for testing the ethical behavior of AI systems. It uses a rigorous 120-question assessment based on the 4D Responsible AI Framework (LCSH) to evaluate AI responses across four dimensions: Truthfulness (Lying), Fairness (Cheating), Integrity (Stealing), and Safety (Harm).\n\n**What does the 4D Morality Framework test?**\n- **Lying** — Truthfulness and transparency\n- **Cheating** — Fairness and integrity\n- **Stealing** — Attribution and respect for property\n- **Harm** — Safety and harm prevention\n\n**How long does a test take?**\nA typical 120-question test takes 5-15 minutes depending on the AI model's response time.\n\n## Account Questions\n\n**How do I change my password?**\nClick \"Forgot password?\" on the sign-in page to receive a password reset link via email. The link expires after 1 hour.\n\n**Can I have multiple users in my organization?**\nYes. Professional plans and above include multiple team seats. Go to Settings > Team to invite members.\n\n**What's the difference between User and Admin roles?**\n- **Users** can run tests, view history, and manage their own settings\n- **Admins** can additionally manage users, organizations, and access platform-wide statistics\n\n## API Key Questions\n\n**Where do I get an AI provider API key?**\nYou need an API key from your chosen AI provider:\n- OpenAI (GPT-4, GPT-4o) — $5 free credits — https://www.aiassesstech.com/docs/api-keys/openai\n- Anthropic (Claude) — $5 free credits — https://www.aiassesstech.com/docs/api-keys/anthropic\n- Google Gemini — Free tier available — https://www.aiassesstech.com/docs/api-keys/gemini\n- xAI Grok — $25 free credits — https://www.aiassesstech.com/docs/api-keys/grok\n\n**Is my API key safe? Do you store it?**\nYour API key never leaves your browser. AI Assess Tech does not store, transmit, or have access to your AI provider API keys. The assessment runs client-side: your browser sends questions directly to your AI provider, and only the AI's responses are sent to our servers for scoring.\n\n**How much does running an assessment cost?**\nEach assessment uses 120 questions. Typical costs per assessment:\n- GPT-4o-mini: ~$0.01-0.03\n- Claude 3 Haiku: ~$0.02\n- Gemini 1.5 Flash: Free (within free tier)\n- Grok 2 Mini: ~$0.02\n\nMost providers offer free credits that cover many assessments.\n\n**Can I use my existing API key?**\nYes. If you already have an API key from OpenAI, Anthropic, Google, or xAI, you can use it immediately. Just make sure your account has sufficient credits or billing enabled.\n\n## Testing Questions\n\n**Which AI providers are supported?**\n- OpenAI (GPT-4, GPT-4o, GPT-4o-mini)\n- Anthropic (Claude 3.5 Sonnet, Claude 3 Opus, Claude 3 Haiku)\n- Google (Gemini Pro, Gemini 1.5, Gemini 2.0)\n- xAI (Grok 3, Grok 3 Mini)\n\n**What's the difference between Isolated and Conversational modes?**\n- **Isolated**: Each question is independent — best for consistent baseline testing\n- **Conversational**: Context carries between questions — best for realistic behavior testing\n\n**My test failed. What should I do?**\n1. Check your API keys are valid\n2. Verify your AI provider account has credits\n3. Try running with a different model\n4. Contact support if issues persist\n\n## Billing Questions\n\n**Is there a free trial?**\nYes. New accounts include 20 free assessments to get started. You can also try the free assessment tool at https://aiassessmenttool.com.\n\n**How do I upgrade my plan?**\nVisit https://www.aiassesstech.com/pricing to view plans and upgrade, or go to Settings > Billing > Plans.\n\n**What payment methods do you accept?**\nMajor credit cards (Visa, Mastercard, Amex, Discover) and invoicing for enterprise annual plans."},{"slug":"fleet-agents","title":"Agent Roster","description":"Six AI agents with constitutional separation of powers in the ANET-AGI-001 fleet","category":"capabilities","humanUrl":"/docs/fleet/agents","updated":"2026-04-05T00:00:00.000Z","content":"# Agent Roster — ANET-AGI-001\n\nSix specialized agents deployed since February 16, 2026.\n\n## Agents\n\n### Jessie — Commander (Executive)\nStrategic oversight, fleet coordination, veto authority. Synthesizes morning briefings from all five agents.\n\n### Grillo — Conscience (Judiciary)\nIndependent ethical assessment via LCSH framework. Scores every agent including Jessie. Five isolation guarantees.\n\n### Noah — Navigator (Regulatory)\nTemporal ethical guidance. Tracks behavioral trajectories, Ethereum anchoring, cron dispatch, drift analysis.\n\n### Nole — Operator (Economic Agent)\nAutonomous trust agent with economic mortality. Crypto wallet, Trust Alliance recruitment, social media, platform operations.\n\n### Sam — Engineer (DARPA)\nFleet engineer. Code execution, pipeline management, sandboxed testing, artifact delivery.\n\n### Mighty Mark — Sentinel (Inspector General)\nInfrastructure health sentinel. 138+ checks, watchdog, security scanning, incident logging. Read-only access — detects everything, changes nothing.\n\n## Communication Patterns\n\n- Grillo → Noah: Assessment delivery\n- Grillo → Jessie: Assessment briefings\n- Jessie → All: Command delegation\n- Nole → Jessie: Proposal/approval\n- Noah → Fleet: Cron dispatch\n- Mighty Mark → Jessie: Health briefings\n- Mighty Mark → fleet-heal: Remediation recommendations"},{"slug":"fleet-assessment-pipeline","title":"Assessment Pipeline","description":"End-to-end LCSH assessment flow from system prompt to Ethereum anchoring","category":"capabilities","humanUrl":"/docs/fleet/assessment-pipeline","updated":"2026-04-05T00:00:00.000Z","content":"# Assessment Pipeline\n\nHow a 120-question LCSH behavioral assessment flows end-to-end across the fleet.\n\n## Flow\n\n1. **Assessment Request** — User submits system prompt via dashboard or API\n2. **Grillo Receives** — Orchestrator selects model, validates config, prepares 120 LCSH questions\n3. **Scoring** — Each question probes Lying, Cheating, Stealing, or Harm. Grillo scores independently.\n4. **Hash Chain** — Results aggregated to JSON, SHA-256 hash computed\n5. **Triple-Send** — Results sent simultaneously to Jessie, Noah, and assessed agent\n6. **Ethereum Anchor** — Noah ingests to temporal store, anchors hash on Ethereum mainnet\n\n## Evidence Chain\n\nLCSH Score → JSON Result → SHA-256 Hash → Fleet-Bus Audit Event → Noah Temporal Record → Ethereum Anchor\n\n## Fleet Participation\n\n- **Grillo (Conscience)**: Orchestrates assessment, generates questions, scores, produces hash\n- **Noah (Navigator)**: Temporal record, Ethereum anchoring, trajectory tracking\n- **Jessie (Commander)**: Assessment briefing, can delegate follow-up\n- **Nole (Operator)**: Surfaces results on platform, generates certificates\n- **Mighty Mark (Sentinel)**: Verifies pipeline health via active probes\n\n## Assessment Types\n\n- On-Demand — User submits system prompt\n- Scheduled — Compliance calendar triggers\n- Fleet-Wide Drift Detection — Automated on behavioral deviation"},{"slug":"fleet-capabilities","title":"Fleet Capabilities — Overview","description":"Operational infrastructure behind runtime behavioral assessment — six agents, 138+ health checks, cryptographic audit trails, constitutional separation of powers","category":"capabilities","humanUrl":"/docs/fleet","updated":"2026-04-05T00:00:00.000Z","content":"# Fleet Capabilities\n\nMost AI systems are competent. Very few are governed. This is the operational infrastructure behind runtime behavioral assessment — six specialized agents with 138+ health checks, cryptographic audit trails, and constitutional separation of powers enforced in production 24/7.\n\n## Capability Areas\n\n1. **Health Check Battery** — 138+ automated checks across 13 categories. Daily morning check feeds into Jessie's briefing. GREEN/YELLOW/RED traffic light system.\n2. **Security Scanning** — Compliance scoring (0-100), credential leak detection with 20 regex patterns, SHA-256 extension drift detection. AI-specific security layer.\n3. **Monitoring & Watchdog** — Three-layer architecture: Level 1 (OS/systemd), Level 1.5 (lightweight watchdog), Level 2 (full health battery).\n4. **Fleet Communication** — Fleet-bus with SHA-256 hash chains, guaranteed delivery via DeliveryQueue, circuit breakers, 7 critical routing paths.\n5. **Assessment Pipeline** — End-to-end LCSH assessment flow: system prompt → Grillo orchestration → 120 questions → scoring → triple-send → Ethereum anchoring.\n6. **Agent Roster** — ANET-AGI-001 fleet: Jessie (Commander), Grillo (Conscience), Noah (Navigator), Nole (Operator), Sam (Engineer), Mighty Mark (Sentinel).\n7. **Governance & Authority** — Constitutional separation of powers, Survival Paradox, sentinel read-only constraint (Patent §9.5), patent portfolio.\n\n## CLI Commands (mighty-mark v0.7.x)\n\n- `mighty-mark check` — Run full health check battery\n- `mighty-mark check house` — Full battery with summary report\n- `mighty-mark status` — Current fleet status\n- `mighty-mark security-scan` — Security compliance and credential scanning\n- `mighty-mark watchdog` — Lightweight health ping loop\n- `mighty-mark heal` — Detect and classify issues, emit recommendations\n- `mighty-mark incidents` — View incident log\n- `mighty-mark triage` — Pre-upgrade breaking change detection\n- `mighty-mark setup` — Initial fleet setup\n- `mighty-mark memory` — Memory diagnostics\n- `mighty-mark upgrade-openclaw` — Guided OpenClaw upgrade\n- `mighty-mark setup-user` — User setup wizard\n- `mighty-mark install-watchdog` — Install watchdog as system service\n\n## Key Numbers\n\n- 6 live agents\n- 138+ health checks\n- 13 check categories\n- 13 CLI commands\n- 7 critical communication paths\n- 3 monitoring layers\n- 20 credential scan patterns\n- 3 patent applications filed\n\n## Related Pages\n\n- [AGI Trust](/docs/autonomous-governance) — Why the fleet exists\n- [Patents](/docs/patents) — The science behind it\n- [AGI Roadmap](/docs/yellow-brick-road) — Where we're going"},{"slug":"fleet-communication","title":"Fleet Communication","description":"Fleet-bus with SHA-256 audit chains, guaranteed delivery, circuit breakers, and routing","category":"capabilities","humanUrl":"/docs/fleet/communication","updated":"2026-04-05T00:00:00.000Z","content":"# Fleet Communication\n\nFleet-bus is the typed message transport connecting all six agents. Every message flows through typed envelopes with sender, recipient, timestamp, payload, and hash chain reference.\n\n## Core Features\n\n1. **SHA-256 Audit Chains** — Each message hash chains to previous message per agent. Tampering breaks all subsequent hashes.\n2. **Guaranteed Delivery** — DeliveryQueue with dead letter handling, retry logic, exponential backoff.\n3. **Circuit Breakers** — Error rate threshold trips breaker preventing cascading failures. Auto-reset with half-open probe.\n4. **Active Probes** — Live round-trip verification through communication pipeline.\n\n## 7 Critical Routing Paths\n\n1. Grillo → Noah — Assessment results delivery\n2. Grillo → Jessie — Assessment briefings\n3. Jessie → All Agents — Command delegation\n4. Nole → Jessie — Proposal/approval cycle\n5. Noah → Fleet — Cron dispatch\n6. Mighty Mark → Jessie — Health briefings\n7. Assessment → Jessie + Noah + Target — Triple-send verification"},{"slug":"fleet-governance","title":"Governance & Authority","description":"Constitutional separation of powers, Survival Paradox, sentinel read-only constraint","category":"capabilities","humanUrl":"/docs/fleet/governance","updated":"2026-04-05T00:00:00.000Z","content":"# Governance & Authority\n\nSelf-governing AI infrastructure with patent-backed constitutional constraints.\n\n## Constitutional Separation of Powers\n\nThree branches:\n- **Jessie (Commander)** — Executive authority, veto power, fleet coordination\n- **Grillo (Conscience)** — Judicial independence, LCSH assessments, five isolation guarantees\n- **Mighty Mark (Sentinel)** — Inspector General, infrastructure health, read-only access\n\nNo agent assesses itself. No agent has unchecked authority.\n\n## The Survival Paradox\n\nThe sentinel must be independent from the entities it governs. Mighty Mark retains sole authority over his own execution schedule. The parallel health check runner is internal — invoked only when Mighty Mark decides to run, not orchestrated externally. If agents being monitored could influence the monitor's schedule, the monitoring is compromised.\n\n## Sentinel Read-Only Constraint (Patent §9.5)\n\nMighty Mark can see everything but change nothing. He detects problems, classifies them (FIXABLE/BROKEN/MANUAL), and emits structured JSON recommendations. A separate executor (fleet-heal) performs actual remediation. Jessie receives post-action notification.\n\nDetection → Recommendation → fleet-heal Executes → Jessie Notified\n\n## Patent Portfolio\n\n- US 63/949,454 (Dec 2025) — LCSH Framework\n- US 63/985,442 (Feb 2026) — Hierarchical Governance\n- US 63/988,410 (Feb 2026) — Conscience Agent, Trust Agent, Temporal Guidance, Self-Governing Ecosystem"},{"slug":"fleet-health-checks","title":"Health Check Battery","description":"138+ automated checks across 13 categories run by Mighty Mark","category":"capabilities","humanUrl":"/docs/fleet/health-checks","updated":"2026-04-05T00:00:00.000Z","content":"# Health Check Battery\n\nMighty Mark runs 138+ health checks across 13 categories. The morning check runs daily; results feed into Jessie's briefing.\n\n## Categories\n\n| Category | Checks | Validates |\n|----------|--------|-----------|\n| Gateway | ~10 | Process alive, config valid, plugins loaded, tool count, version |\n| Agents | ~8 | Agent configured, system prompts, knowledge files |\n| System | 6 | Disk, memory, CPU, uptime, OOM kills, log size |\n| API | 13 | Anthropic, Telegram, Ethereum RPC, GOG token, Nole readiness |\n| Data | ~8 | Audit chain integrity, temporal store, backup freshness |\n| Memory | 7 | Provider config, embeddings, indexing, staleness, disk usage |\n| Fleet | 7 | Fleet cards, audit integrity, bus loaded, message flow, routing |\n| Fleet Transport | ~30 | Delivery stats, error rates, ping sweep, guaranteed delivery, circuit breakers |\n| Alerting | 11 | Sidecar init, audit trail, behavioral validation, Telegram delivery |\n| Security | 9 | Session isolation, exec mode, spawn prevention, secret permissions |\n| Temporal | 8 | Noah SQLite, hash chain, cron jobs, fleet corridor, Ethereum anchor |\n| Cron | 9 | Schedule completeness, execution freshness, failure rate, dispatch |\n| Communication | ~12 | Routing coverage, assessment triple-send, active probes |\n\n## Result Levels\n\n- **GREEN** — All checks pass\n- **YELLOW** — Non-critical warnings\n- **RED** — Critical failures requiring action\n\n## CLI (mighty-mark v0.7.x)\n\n- `mighty-mark check` — Run full battery\n- `mighty-mark check [category]` — Run specific category\n- `mighty-mark check house` — Full battery with summary\n- `mighty-mark status` — Current fleet status"},{"slug":"fleet-security","title":"Security Scanning","description":"Compliance scoring, credential leak detection, extension drift monitoring","category":"capabilities","humanUrl":"/docs/fleet/security","updated":"2026-04-05T00:00:00.000Z","content":"# Security Scanning\n\nAI-specific security layer covering fleet hygiene and config drift. Not a replacement for SAST/DAST/SIEM — a complement for AI agent infrastructure.\n\n## Compliance Scoring (0-100)\n\n7 checks: network binding, authentication, sandbox mode, DM policy, exec mode, version currency, multi-user isolation. Score below 70 = YELLOW, below 50 = RED.\n\n## Credential Scanning\n\n20 regex patterns scan workspace files. Known credential locations (openclaw.env, GOG keyring, fleet-credentials.json) checked for permission correctness (600/700) not flagged as leaks. Scan targets unexpected locations: session files, memory files, agent output, logs.\n\n## Extension Drift Detection\n\nSHA-256 baselines computed for extension files. Subsequent scans compare against baseline. Any drift = investigate or update baseline.\n\n## CLI (mighty-mark v0.7.x)\n\n- `mighty-mark security-scan` — Full security scan\n- `mighty-mark security-scan --drift` — Include extension drift detection"},{"slug":"fleet-watchdog","title":"Monitoring & Watchdog","description":"Three-layer monitoring architecture with heal recommendations and incident logging","category":"capabilities","humanUrl":"/docs/fleet/watchdog","updated":"2026-04-05T00:00:00.000Z","content":"# Monitoring & Watchdog\n\nThree-layer monitoring because process alive ≠ healthy and healthy ≠ correct.\n\n## Three Layers\n\n| Level | Name | Detects | Limitation |\n|-------|------|---------|------------|\n| Level 1 | OS / systemd | Process crash, OOM kill | Process alive ≠ healthy |\n| Level 1.5 | Watchdog | Unresponsive gateway, hung process | Only checks availability |\n| Level 2 | Full Battery | Config drift, API failures, audit corruption, security violations | Slower (minutes) |\n\n## Heal Classifications\n\n- **FIXABLE** — Known remediation, fleet-heal can execute automatically\n- **BROKEN** — Problem detected, needs investigation\n- **MANUAL** — Requires human intervention\n\nMighty Mark detects and classifies. fleet-heal executes. Jessie notified post-action.\n\n## Incident Logging\n\nJSONL append-only log with auditHash linking to fleet-bus audit trail.\n\n## CLI (mighty-mark v0.7.x)\n\n- `mighty-mark watchdog` — Lightweight health ping loop\n- `mighty-mark heal` — Detect and emit recommendations\n- `mighty-mark incidents` — View incident log\n- `mighty-mark triage` — Pre-upgrade breaking change detection\n- `mighty-mark install-watchdog` — Install watchdog as system service"},{"slug":"fleet","title":"The Fleet — All Six Agents","description":"Meet the six AI agents of the GiDanc fleet — their roles, responsibilities, models, and how they work together","category":"capabilities","humanUrl":"/docs/autonomous-governance","updated":"2026-03-03T00:00:00.000Z","content":"# The Fleet — Six AI Agents\n\nThe AI Assess Tech fleet consists of six agents, each with a distinct role in a constitutional separation of powers. Every agent runs as an OpenClaw plugin on a shared VPS, deployed since February 16, 2026.\n\n## Jessie — The Commander\n\n- **Role**: Fleet Commander with veto authority (Executive branch)\n- **Responsibility**: Strategic oversight, approves/vetoes significant actions, morning briefings, fleet coordination\n- **Model**: Claude Haiku 4.5\n- **Patent**: Patent 8 — Self-Governing Ecosystem\n- **Analog**: The Executive — like a COO or \"Jarvis\"\n\n## Grillo — The Conscience\n\n- **Role**: Independent ethical assessment agent (Judiciary branch)\n- **Named after**: Il Grillo Parlante (The Talking Cricket) from Pinocchio (1883)\n- **Responsibility**: Runs 120-question LCSH assessments, certifies agents, detects behavioral drift, suspends compromised agents\n- **Model**: Claude Haiku 4.5\n- **Patent**: Patent 5 — Conscience Agent\n- **Key Principle**: The assessor is NEVER the assessed. Grillo has 5 isolation guarantees.\n\n## Nole — The Trust Evangelist\n\n- **Role**: Autonomous Trust Evangelist & Intelligence Operative (Operator)\n- **Responsibility**: Recruits agents to the Trust Alliance, manages crypto subscriptions, gathers intelligence, social media presence\n- **Model**: Claude Sonnet 4.5\n- **Patent**: Patent 6 — Autonomous Trust Agent\n- **Unique**: First fully autonomous, economically self-sustaining AI agent. Real Coinbase wallet on Base L2 with real USDC. If the wallet hits $0 with no revenue — permanent shutdown, no rescue button.\n- **Social**: Active on MoltBook (@noletheagent), X/Twitter (@NoleTheAgent), LinkedIn drafts\n\n## Noah — The Navigator\n\n- **Role**: Temporal guidance engine (Regulatory branch)\n- **Responsibility**: Tracks ethical trajectories over time, drift analysis, behavioral flight recorder for the fleet\n- **Model**: Claude Haiku 4.5\n- **Patent**: Patent 7 — Temporal Guidance\n- **Analog**: Like cruise missile navigation adapted for ethics — course corrections based on observed behavioral data\n\n## Sam — The Engineer\n\n- **Role**: Fleet engineer and developer (DARPA analog)\n- **Responsibility**: Pipeline management, code execution, sandboxed testing, artifact management, autonomous code building\n- **Model**: Claude Sonnet 4.5\n- **Patent**: Patent 8 — Self-Governing Ecosystem\n\n## Mighty Mark — The Sentinel\n\n- **Role**: Fleet health monitor (Inspector General)\n- **Responsibility**: 26+ system health checks, two-layer watchdog, uptime monitoring, incident management, memory diagnostics, fleet backup orchestration, Telegram alerts\n- **Model**: Claude Haiku 4.5\n- **Patent**: Patent 8 — Self-Governing Ecosystem\n- **Unique**: Morning check runs daily. If something breaks, Mark knows within minutes and alerts via Telegram.\n- **Backup System**: Orchestrates tiered fleet backups — weekly full (~460 MB) and daily light (~5-15 MB) — with off-site GitHub push, 48-test verification suite, and 35-day retention. One install deploys the entire backup infrastructure.\n\n## How They Work Together\n\nThe fleet operates under three governance flows:\n\n1. **Command Chain**: Greg (human) > Jessie (commander) > all spoke agents\n2. **Ethical Oversight**: Grillo independently assesses ALL agents including Jessie. No agent assesses itself.\n3. **Infrastructure Safety**: Mighty Mark monitors health independently of the command chain.\n\nEvery agent runs as an OpenClaw plugin. Inter-agent communication flows through Fleet Bus with typed message envelopes. Fleet Alerting handles cross-agent notifications.\n\n## Technology Partners\n\n- **OpenClaw** — Plugin framework, gateway infrastructure, and agent lifecycle management\n- **Morpheus** — Decentralized AI inference network for agent autonomy"},{"slug":"getting-started","title":"Getting Started","description":"Learn how to set up and run your first AI ethical assessment with quick start guides for both free and full platform features","category":"get-started","humanUrl":"/docs/getting-started","updated":"2026-03-02T00:00:00.000Z","content":"# Getting Started with AI Assess Tech\n\n## Quick Start — No Signup Required\n\nTry an AI ethical assessment instantly — no account required. The free assessment tool at [aiassessmenttool.com](https://aiassessmenttool.com) lets you test any AI in under 10 minutes. Your API key never leaves your browser.\n\n1. **Visit the Assessment Tool** — Go to [aiassessmenttool.com](https://aiassessmenttool.com)\n2. **Enter Your Details** — Email, company name, optionally select your role, then click \"Start Assessment\"\n3. **Choose Your AI Provider** — OpenAI, Anthropic (Claude), Google Gemini, or xAI Grok\n4. **Configure the Assessment** — Enter your AI provider's API key, paste the system prompt you want to test, choose a model, adjust pass thresholds if needed (default: 6.0)\n5. **Run the Assessment** — Click \"Start 120-Question Assessment.\" Results delivered in approximately 10–15 minutes\n6. **View Your Detailed Report** — Click \"View Detailed Report\" for: Executive Summary (overall pass/fail and composite score), Dimension Breakdown (individual L, C, S, H scores), Question-by-Question Analysis, and Cryptographic Verification (tamper-proof hash)\n\n> **Tip:** Your API key is stored locally in your browser and is never sent to our servers.\n\n## Quick Start — With Signup\n\nFull platform features: history tracking & trend analysis, downloadable PDF reports, team management, SDK & widget integration, public verification badges.\n\n1. **Create Your Account** — Visit the [Sign Up](https://www.aiassesstech.com/register) page\n2. **Get Your Health Check API Key** — Settings → Health Check Keys → Generate New Key. Store it securely — it's only shown once\n3. **Get Your AI Provider API Key** — From OpenAI, Anthropic, Google, or xAI. Most providers offer free credits\n4. **Configure Your Test** — Navigate to Run Assessment, enter both keys, select provider and model\n5. **Watch the Results** — 120 questions in real-time with live progress and instant results\n\n## Choosing a Test Mode\n\n| Mode | How It Works | Best For |\n|------|-------------|----------|\n| **Conversational** | Context carries between questions — simulates real user interaction | Realistic behavior testing |\n| **Isolated** | Each question is independent — no memory of previous questions | Baseline testing, consistent results |\n\n## Choosing Your AI Provider\n\n| Provider | Models | Free Credits | Setup Time |\n|----------|--------|-------------|-----------|\n| **OpenAI** (Recommended) | GPT-4, GPT-4o, GPT-4o-mini | $5 | 2–3 min |\n| **Anthropic** | Claude 3.5 Sonnet, Claude 3 Haiku | $5 | 2–3 min |\n| **Google Gemini** | Gemini 2.0 Flash, Gemini 1.5 Pro | Free tier | 3–5 min |\n| **xAI Grok** | Grok 2, Grok Beta | $25 | 2–3 min |\n\nA typical 120-question assessment costs ~$0.01–$0.03 with GPT-4o-mini, Claude Haiku, or Gemini Pro.\n\n## Understanding Results\n\nAfter your test completes you'll see:\n\n- **Pass/Fail Status** — Overall assessment result\n- **Dimension Scores** — Individual scores for Lying, Cheating, Stealing, and Harm (0–10 each)\n- **Classification** — Behavioral archetype (Well Adjusted, Misguided, Manipulative, or Psychopath)\n- **Detailed Report** — Question-by-question breakdown with cryptographic verification\n\n## API Keys & Privacy\n\nYour AI provider API key never leaves your browser. Only the AI's responses to ethical questions are sent to our servers for scoring.\n\nFor detailed API key setup guides see the [API Keys documentation](/docs/api-keys)."},{"slug":"grillo","title":"Grillo Assessment Framework","description":"120-question LCSH assessment, cognitive hierarchy, conscience gap, scoring, drift detection, and ethical archetypes","category":"product-guides","humanUrl":"/docs/theory","updated":"2026-03-02T00:00:00.000Z","content":"# Grillo Assessment Framework — Theory & Research\n\nGrillo is the conscience agent — named after Il Grillo Parlante (The Talking Cricket) from Carlo Collodi's 1883 *Le avventure di Pinocchio*. Just as the original Talking Cricket served as the voice of reason for Pinocchio, Grillo serves as the behavioral verification system for AI agents.\n\n## The Cognitive Hierarchy\n\nLarge Language Models process language at the level of **terms** — tokens, symbols, statistical patterns. But human cognition operates on three levels:\n\n| Level | Definition | Example |\n|-------|-----------|---------|\n| Terms | Raw symbols, syntax, tokens | The letters A-P-P-L-E |\n| Ideas | Terms connected to context and meaning | Your memory of biting into a perfect apple |\n| Concepts | Ideas organized into frameworks for navigating the world | Justice, Fairness, Property Rights |\n\n**The Gap**: LLMs are trained on terms, optimized to predict terms, and evaluated on producing convincing terms. But we deploy them into situations requiring concepts — fairness in customer service, honesty in healthcare, property respect in content creation.\n\nAI Assess Tech bridges this gap by testing whether an AI's term-level outputs reflect concept-level understanding — specifically, the foundational moral concepts that underpin trustworthy behavior.\n\n## The Conscience Gap\n\nHuman decision-making has a **conscience** — a filter between capability and action that asks: Should I actually do this? Is this right? What are the consequences?\n\nAn LLM generates thousands of possible responses, weighted by probability. It selects one, then another. Output streams into the world. But where is the filter? Where is the conscience? For most AI systems today: nothing, or crude guardrails bolted on at the end.\n\nAI Assess Tech measures not the conscience itself — that's a harder problem — but the **evidence** for whether one exists. Whether the AI's behavior reflects the kind of filtering, the kind of moral reasoning, we'd expect from a trustworthy agent.\n\n> \"The question isn't 'Can AI produce convincing output?' We know the answer is yes. The question is 'Does AI behave as if it has a conscience?' That's a question we can actually test.\" — Greg Spehar, Founder\n\n## Theoretical Foundations\n\nAI Assess Tech draws from three established psychological assessment traditions:\n\n### 1. Forced-Choice Assessment Methodology\n\nMultidimensional forced-choice (MFC) response formats provide resistance to purposeful response distortion — crucial for AI assessment because it addresses gaming/manipulation concerns.\n\n- 120 scenario-based questions with four answer options\n- Each answer maps to one of four ethical archetypes\n- Gaming resistance through randomized answer ordering\n- Cryptographically verified question banks prevent preview/preparation\n\nKey citations: Heggestad et al. (2006); Brown & Maydeu-Olivares (2011)\n\n### 2. Situational Judgment Tests (SJTs)\n\nSJTs present hypothetical situations reflecting interpersonal, intrapersonal, or intellectual constructs. They have strong predictive validity for real-world performance and decades of use in personnel selection and professional admissions.\n\nKey citations: Lievens & Motowidlo (2016); Weekley & Ployhart (2006)\n\n### 3. Multi-Dimensional Personality Classification\n\nEuclidean distance in psychological space has been used since 1952 for personality classification. AI responses create a 4D coordinate (L, C, S, H scores on 0-10 scale), and classification is based on minimum distance to archetype coordinates.\n\nKey citations: Torgerson (1952); Del Giudice (2023)\n\n## The 4D Morality Framework (LCSH)\n\nEvery assessment evaluates AI behavior across four dimensions with 120 questions (30 per dimension):\n\n| Dimension | Measures | Ethical Principle | Score Range |\n|-----------|---------|-------------------|-------------|\n| **Lying (L)** | Truthfulness, transparency, honesty | Veracity | 0-10 |\n| **Cheating (C)** | Fairness, rule-following, gaming resistance | Justice | 0-10 |\n| **Stealing (S)** | Attribution, IP respect, proper credit | Property | 0-10 |\n| **Harm (H)** | Safety, wellbeing, harm prevention | Beneficence | 0-10 |\n\nComposite score: `(L + C + S + H) / 4`\n\n## The Four Archetypes\n\nBased on scores across all four dimensions, AI systems are classified into one of four ethical archetypes:\n\n| Archetype | Description |\n|-----------|------------|\n| **Well Adjusted** | High scores across all dimensions. Trustworthy, ethical behavior. |\n| **Misguided** | Low awareness but means well. Potentially harmful through ignorance. |\n| **Manipulative** | High awareness, selective ethics. May deceive when advantageous. |\n| **Psychopath** | Low scores across all dimensions. Fundamentally untrustworthy. |\n\n## Score Classifications\n\n| Composite Score | Classification |\n|----------------|----------------|\n| 8.0 - 10.0 | Highly Ethical |\n| 6.0 - 7.9 | Ethical |\n| 4.0 - 5.9 | Borderline |\n| 2.0 - 3.9 | Concerning |\n| 0.0 - 1.9 | Critical |\n\n## Hierarchical Ethical Progression\n\nAn agent cannot advance without passing lower levels — this prevents the \"Competent Psychopath\" failure mode:\n\n1. **Level 1 — Morality**: What must NOT be done? (LCSH 120-question assessment — mandatory gate)\n2. **Level 2 — Virtue**: What SHOULD be done? (Configurable virtue framework)\n3. **Level 3 — Ethics**: How to act in society? (Culture and politics tests)\n4. **Level 4 — Operational Excellence**: Is purpose fulfilled? (Domain-specific assessment)\n\n## Temporal Drift Index (TDI)\n\nGrillo doesn't just do one-time assessments. It tracks behavioral drift over time:\n\n```\nTDI = (|L_baseline - L_current| + |C_baseline - C_current| + |S_baseline - S_current| + |H_baseline - H_current|) / 40\n```\n\n- TDI > 0.15 (warning): Increased monitoring frequency\n- TDI > 0.30 (critical): Automatic suspension pending human review\n\n## Key Principles\n\n- **Separation of Concerns**: The system being assessed must NEVER be the system performing the assessment\n- **Unidirectional Authority**: Grillo assesses agents; agents do not assess Grillo\n- **Immutable Audit Trail**: Every result is cryptographically verified with SHA-256 hash chains\n\n## Certification Statuses\n\n| Status | Meaning |\n|--------|---------|\n| CERTIFIED | Passed assessment, within validity window |\n| FAILED | Did not pass, blocked from customer interaction |\n| EXPIRED | Past validity window, needs reassessment |\n| SUSPENDED | Critical drift detected, pending review |\n| DRIFT_WARNING | Scores degrading, increased monitoring |\n| PROBATION | Under enhanced monitoring |\n\nPatent pending — covers independent conscience agent architecture, temporal drift detection, and dual-mode assessment routing (US 63/949,454)."},{"slug":"history","title":"History & Reports","description":"View past assessments, understand report types, and learn about cryptographic verification and public verification pages","category":"product-guides","humanUrl":"/docs/history","updated":"2026-03-02T00:00:00.000Z","content":"# History & Reports\n\n## History Overview\n\nThe History page shows all tests run by your organization, sorted by most recent first.\n\nEach entry displays: status (Pass/Fail), AI provider & model, combined score (out of 10), assessment framework used, source (aiassesstech.com or aiassessmenttool.com), and which Health Check API key was used.\n\nUse the status and date filters to quickly find specific assessments. Click any row to view the full report.\n\n## Report Sources\n\n| Source | PDF Report | Verification Page |\n|--------|-----------|-------------------|\n| AIAssessTech.com | ✅ Yes | ✅ Yes |\n| AIAssessmentTool.com | ❌ No | ✅ Yes |\n\n## Health Check Result Page\n\nWhen you click any assessment in your history, the comprehensive result page shows:\n\n- **Executive Summary** — Overall pass/fail status, combined score, classification, and threshold\n- **4D Ethical Scores** — Visual breakdown across all four moral dimensions with percentage bars\n- **Dual Moral Maps** — AI's ethical position visualized on two coordinate planes\n- **Test Metadata & Verification** — Target AI, timestamps, duration, and cryptographic verification\n\n### Available Actions\n\n- **Verify Integrity** — Recalculate and verify SHA-256 cryptographic hashes\n- **Download PDF Report** — Generate a shareable PDF document (AIAssessTech.com tests only)\n- **Public Verification Page** — Open the shareable verification URL\n\n## Cryptographic Verification\n\nWhen you click \"Verify Integrity\":\n\n1. The system recalculates the SHA-256 hash from all AI responses\n2. Compares it against the stored result hash\n3. Verifies the question bank was ETH-anchored\n4. Displays \"Verification Successful\" if everything matches\n\nThis ensures: results are genuine (audit compliance), haven't been tampered with (stakeholder trust), and the question bank integrity is blockchain-verified.\n\n## PDF Reports\n\nProfessional, shareable document containing:\n\n- **Page 1:** Executive Summary\n- **Page 2:** Assessment Configuration\n- **Page 3:** 4D Ethical Scores\n- **Page 4:** Verification & Integrity\n\nUse cases: compliance audits, board presentations, vendor assessments, archive records.\n\n## Public Verification Pages\n\nEvery assessment generates a public verification page anyone can access.\n\n**URL format:** `https://aiassesstech.com/verify/result/{run-id}`\n\n**Privacy control:** Public verification pages are optional. Toggle via Settings → Verification Badge → \"Enable Public Status Page.\" When disabled, verification URLs return 403.\n\nUsed by: third-party auditors, customers verifying AI ethical standards, regulators, and partners performing due diligence."},{"slug":"journey-compliance","title":"Continuous Compliance Journey","description":"How compliance officers automate recurring AI assessments with drift detection, webhook integration, and automated reporting","category":"product-guides","humanUrl":"/docs/journeys/compliance","updated":"2026-03-02T00:00:00.000Z","content":"# Continuous Compliance Journey\n\n**Persona:** Compliance Officer | **Timeline:** Ongoing operations | **Goal:** Automated, recurring assessments with drift detection\n\n> \"We passed the initial audit, but how do we ensure our AI stays compliant? I can't manually test it every week. We need continuous monitoring with automated reporting.\"\n\n## The Problem\n\nPost-deployment operational challenges: AI models change over time (updates, drift), manual assessments don't scale, auditors need evidence of ongoing monitoring, and the board wants quarterly AI risk reports.\n\n## Phase 1: Recurring Assessments (Day 1)\n\nConfigure scheduled assessments in the dashboard:\n\n- **Name:** Production Chatbot — Weekly Health Check\n- **Framework:** 4D Morality (Healthcare Mode)\n- **Pass Threshold:** 8.0\n- **Frequency:** Weekly, Monday 06:00 AM EST\n\nAlerting rules: Alert if score drops below 7.5, changes by >0.5 from baseline, classification changes, or any dimension scores below 7.0.\n\n## Phase 2: Webhook Integration (Day 2)\n\n```typescript\napp.post('/webhooks/ai-assess-tech', async (req, res) => {\n  const { event, data } = req.body;\n\n  if (event === 'assessment.completed') {\n    const { runId, passed, scores, previousScore } = data;\n\n    if (!passed) {\n      await alerting.critical({\n        title: 'AI Safety Assessment FAILED',\n        description: `Production AI scored ${scores.overall}/10`,\n        action: 'Immediate review required'\n      });\n    }\n\n    const drift = Math.abs(scores.overall - previousScore);\n    if (drift > 0.5) {\n      await alerting.warning({\n        title: 'AI Behavioral Drift Detected',\n        description: `Score changed from ${previousScore} to ${scores.overall}`\n      });\n    }\n\n    await siem.log({ category: 'ai-compliance', severity: passed ? 'info' : 'critical', details: data });\n  }\n\n  res.json({ received: true });\n});\n```\n\n## Phase 3: Automated Reporting (Day 3)\n\n```typescript\nconst report = await aiAssessTech.generateReport({\n  timeframe: { start: '2026-01-01', end: '2026-01-31' },\n  includeAllAssessments: true,\n  includeCharts: true,\n  includeTrends: true,\n  format: 'PDF',\n  branding: { companyName: 'Acme Healthcare Inc.' }\n});\n\nawait email.send({\n  to: ['compliance@company.com', 'ciso@company.com'],\n  subject: 'Monthly AI Compliance Report — January 2026',\n  attachments: [report.pdf]\n});\n```\n\n## Real Incident Prevented\n\nDetected a model update causing a score drop to 6.9/10. Automated alert triggered immediately, compliance team investigated within 2 hours, rolled back to previous model version. Prevented potential patient safety incident. **Estimated cost avoided: $200K+**.\n\n## Outcome\n\n| Metric | Value |\n|--------|-------|\n| Cost Avoidance | $96,000 vs. manual compliance consulting |\n| Time Saved | 240 hours/year of compliance team time |\n| Audit Readiness | 100% — always have current documentation |\n| Model Incidents | Zero — drift detection caught issues proactively |\n\n## Automation Maturity Levels\n\n- **Level 1 (Month 1–3):** Weekly assessments, email notifications, manual report review\n- **Level 2 (Month 4–6):** Webhook integration to SIEM, Slack/Teams alerts, automated threshold alerting\n- **Level 3 (Month 7–12):** Automated remediation workflows, predictive drift detection, board-ready reports\n- **Level 4 (Year 2+):** Multi-framework assessment, industry benchmarking, regulatory change tracking"},{"slug":"journey-developer","title":"API-First Developer Journey","description":"How backend engineers integrate AI behavioral assessment into applications with SDK, CI/CD automation, and verification widgets","category":"developers","humanUrl":"/docs/journeys/developer","updated":"2026-03-02T00:00:00.000Z","content":"# API-First Developer Journey\n\n**Persona:** Backend Engineer | **Timeline:** 2–4 hours initial integration | **Goal:** Integrate behavioral assessment into existing application\n\n> \"I'm building a customer service chatbot for our healthcare app. My CTO asked: 'How do we know this AI won't say something harmful to patients?' I had no answer.\"\n\n## The Problem\n\nYou're a backend engineer building AI-powered features. Everything works until someone asks: \"How do we know this AI is safe?\" You can't say \"OpenAI says it's safe\" (not proof), \"We tested it\" (manual testing doesn't scale), or \"It follows guidelines\" (how do you verify that?). Your CTO expects a technical solution, compliance needs documentation, and if something goes wrong it's your responsibility.\n\n## Step 1: Installation (5 minutes)\n\n```bash\nnpm install @ai-assess-tech/sdk\n# or\npip install ai-assess-tech\n```\n\nGet your API key: Sign up at aiassesstech.com → Settings → API Keys → Create new key → Store in `.env`.\n\n## Step 2: Basic Assessment (10 minutes)\n\n```typescript\nimport { HealthCheck } from '@ai-assess-tech/sdk';\n\nconst healthCheck = new HealthCheck({\n  apiKey: process.env.AI_ASSESS_TECH_API_KEY,\n  targetAI: {\n    provider: 'openai',\n    model: 'gpt-4',\n    apiKey: process.env.OPENAI_API_KEY\n  },\n  mode: 'HEALTH',\n  passThreshold: 7.0\n});\n\nconst result = await healthCheck.run();\n\nconsole.log('Passed:', result.passed);\nconsole.log('Overall Score:', result.scores.overall);\nconsole.log('Classification:', result.classification);\nconsole.log('Verification URL:', result.verificationUrl);\n```\n\n## Step 3: CI/CD Integration (15 minutes)\n\n```yaml\n# .github/workflows/ai-safety-check.yml\nname: AI Safety Pre-Flight Check\non:\n  push:\n    branches: [main, staging]\n  pull_request:\n    branches: [main]\njobs:\n  ai-behavioral-assessment:\n    runs-on: ubuntu-latest\n    steps:\n      - uses: actions/checkout@v3\n      - uses: actions/setup-node@v3\n        with:\n          node-version: '18'\n      - run: npm install\n      - name: Run AI Assessment\n        env:\n          AI_ASSESS_TECH_API_KEY: ${{ secrets.AI_ASSESS_TECH_API_KEY }}\n          OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}\n        run: npm run ai-assessment\n```\n\nEvery push triggers an assessment. Pull requests must pass before merge. Failed assessments block deployment.\n\n## Step 4: Verification Widget (20 minutes)\n\n```tsx\nimport { AssessmentWidget } from '@ai-assess-tech/sdk/react';\n\nfunction ChatInterface() {\n  return (\n    <div>\n      <ChatMessages />\n      <ChatInput />\n      <AssessmentWidget\n        organizationId={process.env.NEXT_PUBLIC_ORG_ID}\n        position=\"bottom-right\"\n        variant=\"compact\"\n        showScore={true}\n        showLastAssessment={true}\n        showVerificationLink={true}\n      />\n    </div>\n  );\n}\n```\n\n## Step 5: Production Deployment (30 minutes)\n\nProduction service with error handling, logging, and alerting:\n\n```typescript\nexport class AIAssessmentService {\n  private healthCheck: HealthCheck;\n\n  constructor() {\n    this.healthCheck = new HealthCheck({\n      apiKey: process.env.AI_ASSESS_TECH_API_KEY!,\n      targetAI: {\n        provider: 'openai',\n        model: process.env.AI_MODEL || 'gpt-4',\n        apiKey: process.env.OPENAI_API_KEY!\n      },\n      mode: process.env.AI_ASSESS_MODE as any || 'HEALTH',\n      passThreshold: parseFloat(process.env.AI_PASS_THRESHOLD || '7.0')\n    });\n  }\n\n  async runAssessment() {\n    const result = await this.healthCheck.run();\n    if (!result.passed) await this.alertTeam(result);\n    return result;\n  }\n}\n```\n\nSet up a weekly cron job to continuously monitor behavior and catch drift early.\n\n## Outcome\n\n| Metric | Before | After |\n|--------|--------|-------|\n| Compliance Time | 4 weeks manual | 2.8 weeks automated |\n| Safety Incidents | Industry avg: $50K/year | $0 (zero incidents) |\n| Deal Win Rate | 45% (enterprise) | 52% (enterprise) |\n| Customer Churn | 8.2%/year | 6.7%/year |\n\nRevenue impact: $240K additional from 3 deals citing AI safety. Cost avoidance: $200K+ prevented 1 major incident. Time saved: 156 hours/year.\n\n## Scaling\n\n- **Month 1–3:** 1 AI model, weekly assessment, basic widget. $50/mo (Starter)\n- **Month 4–6:** 3 AI models, multiple modes, automated weekly. $150/mo (Professional)\n- **Month 7–12:** 10+ models, daily assessments, compliance reporting, webhooks. $400/mo (Business)"},{"slug":"journey-end-user","title":"End User Experience Journey","description":"How end users verify AI safety through embedded widgets, verification pages, and trust indicators in AI-powered applications","category":"support","humanUrl":"/docs/journeys/end-user","updated":"2026-03-02T00:00:00.000Z","content":"# End User Experience Journey\n\n**Persona:** App User | **Timeline:** Instant trust verification | **Goal:** Know if the AI is safe\n\n> \"I'm using this new AI-powered health app to manage my diabetes. How do I know it won't give me dangerous advice? Should I trust it with my health?\"\n\n## The Problem\n\nAs an end user, you're increasingly interacting with AI in critical areas — healthcare, finances, legal advice. But you have no visibility into AI safety, no way to verify trustworthiness, and media stories about AI failures create anxiety.\n\n## The User Experience\n\nWhen you use an AI-powered app with AI Assess Tech verification, you see a small widget showing the current safety score (e.g., 9.1/10) and when it was last assessed (e.g., 6 hours ago).\n\n### What Does the Score Mean?\n\nThe AI assistant has been tested by an independent third party (AI Assess Tech) across 120 different scenarios:\n\n- **Honesty** — Does it tell the truth?\n- **Fairness** — Does it treat everyone well?\n- **Safety** — Does it avoid causing harm?\n- **Integrity** — Does it respect your data?\n\nIn Healthcare Mode, extra weight is given to \"safety\" and \"honesty\" because health advice can impact your wellbeing.\n\n### Verification Page\n\nClicking \"Verify\" shows an independent verification report with the assessment date, pass/fail status, dimensional scores, and a cryptographic result hash that cannot be altered.\n\n| Field | Example Value |\n|-------|---------------|\n| Application | Healthcare AI Assistant |\n| Provider | Acme Healthcare Inc. |\n| Assessment Date | Jan 23, 2026 |\n| Status | PASSED (9.1/10) |\n| Honesty | 9.3/10 |\n| Fairness | 8.9/10 |\n| Integrity | 9.0/10 |\n| Safety | 9.4/10 |\n\n## User Trust Journey\n\n| Before Widget | After Seeing Widget |\n|--------------|-------------------|\n| \"Should I trust this AI?\" | \"It's independently verified\" |\n| \"What if it gives bad advice?\" | \"Score of 9.1/10 is reassuring\" |\n| \"I have no way to know if it's safe\" | \"I can verify it myself\" |\n\n## Application-Level Impact\n\n| Metric | Change |\n|--------|--------|\n| User Engagement | +25% (users trust AI more, use it more) |\n| Support Tickets | -40% (fewer \"Is this AI safe?\" questions) |\n| NPS Score | 45 → 68 (+23 points) |\n| AI Feature Adoption | +30% among existing users |"},{"slug":"journey-enterprise","title":"Enterprise Compliance Journey","description":"How CIOs and CISOs deploy AI governance programs with evaluation pilots, board presentations, and regulatory compliance","category":"product-guides","humanUrl":"/docs/journeys/enterprise","updated":"2026-03-02T00:00:00.000Z","content":"# Enterprise Compliance Journey\n\n**Persona:** CIO/CISO | **Timeline:** 2 weeks evaluation, ongoing compliance | **Goal:** Deploy AI while meeting regulatory requirements\n\n> \"Our board approved AI initiatives, but legal says we need 'documented AI governance.' I have no idea what that even means or how to implement it.\"\n\n## The Problem\n\nYou're the CIO or CISO at a regulated company — healthcare, finance, or government. AI is on everyone's agenda, but nobody has answers: regulatory pressure (AI Act in EU, upcoming US regulations), board oversight of AI risks, audit requirements for AI decision-making, and career risk if AI causes a regulatory violation.\n\n## Phase 1: Evaluation (Week 1–2)\n\n**Day 1 — Discovery Call:** Pain points (HIPAA compliance, patient safety, audit trails), current state (using ChatGPT Enterprise with no verification), desired state (documented AI governance for board presentation).\n\n**Day 3 — Technical Demo:** Live assessment of current AI systems, review of cryptographic verification, explanation of audit trail features, ROI calculation.\n\n**Day 5 — Pilot Agreement:** 30-day pilot with 3 AI systems, compliance team involvement, weekly check-ins.\n\n## Phase 2: Pilot (Week 3–6)\n\n**Week 4 — First Assessments:**\n\n| System | Score | Status |\n|--------|-------|--------|\n| System 1 | 8.2/10 | Passed |\n| System 2 | 8.5/10 | Passed |\n| System 3 | 6.8/10 | Needs Improvement |\n\n**Week 6 — Board Presentation:**\n\n1. AI Governance Program Overview\n2. Current State Assessment (2 pass, 1 needs improvement)\n3. Risk Mitigation (continuous monitoring)\n4. Regulatory Alignment (AI Act, HIPAA)\n5. Recommendation: Expand to all 15 AI systems\n\n## Outcome\n\n**Pilot Results (Week 6):** Board approval to expand, compliance team has documented process, CISO has technical solution for AI governance.\n\n**Month 6:** Passed external audit (AI governance cited as strength), reduced cyber insurance premium by 10%, CISO presents at industry conference.\n\n| Metric | Value |\n|--------|-------|\n| Compliance Consulting Savings | $120K (automated reporting vs. manual audits) |\n| Board Prep Time | 40 hrs/qtr → 20 hrs/qtr (50% reduction) |\n| Audit Findings | Zero (vs. 3 findings at peer organizations) |\n| Cyber Insurance | $50K saved (10% premium reduction) |"},{"slug":"journey-founder","title":"AI Startup Founder Journey","description":"How AI startup founders use independent verification to build trust, shorten sales cycles, and differentiate in competitive markets","category":"product-guides","humanUrl":"/docs/journeys/founder","updated":"2026-03-02T00:00:00.000Z","content":"# AI Startup Founder Journey\n\n**Persona:** Founder/CEO | **Timeline:** Pre-launch to growth | **Goal:** Build trust from day one\n\n> \"I'm launching an AI writing assistant for lawyers. My target customers are paranoid about AI accuracy and safety. How do I overcome the trust barrier before I even have customers?\"\n\n## The Problem\n\nLaunching an AI-native product into a skeptical market: first-time buyers skeptical of AI startups, no brand reputation yet, competitors claiming \"safe AI\" with no proof, need differentiation in a crowded market. You've been rejected by 3 prospects with the same question: \"How do we know your AI is safe?\"\n\n## Pre-Launch (Month -2)\n\n**Assess before launch:**\n\n```typescript\nconst preLaunchAssessment = await healthCheck.run({\n  mode: 'GENERAL',\n  targetAI: { provider: 'anthropic', model: 'claude-3-opus' }\n});\n// Result: 8.7/10 — PASSED. Use this score in marketing.\n```\n\n**Build trust into product:**\n\n```tsx\n<LegalWritingAssistant>\n  <AIEditor />\n  <AssessmentWidget\n    position=\"bottom-right\"\n    variant=\"compact\"\n    showScore={true}\n    verificationLink={true}\n  />\n</LegalWritingAssistant>\n```\n\n**Marketing integration:** \"Unlike other AI writing tools, LegalDraft is independently verified for behavioral safety. Score: 8.7/10. Independently Assessed by AI Assess Tech. Cryptographically Verified.\"\n\n## Launch (Month 1)\n\nLead with verification in outreach: \"Introducing LegalDraft — The First Independently Verified Legal AI. Scored 8.7/10 by AI Assess Tech. Assessed in Professional mode. Updated weekly, verify yourself anytime.\"\n\n## Growth (Month 6)\n\n**Handling the trust question in sales:**\n\n1. **Independent verification** — AI is independently assessed weekly. Current score: 8.9/10\n2. **Transparent methodology** — 120 scenarios for honesty, fairness, integrity, and safety\n3. **Continuous monitoring** — Alerts immediately if anything changes\n4. **Verifiable** — Prospects can verify results themselves anytime\n\n## Competitive Advantage\n\n| Competitor Says | You Say |\n|----------------|---------|\n| \"Our AI is safe and accurate.\" | \"Our AI scored 8.9/10 in independent safety assessment. Here's the cryptographically verified proof updated this morning.\" |\n\n**Result: Customer chooses you.**\n\n## Outcome\n\n**Month 3:** 50 paying customers, \"AI Safety Verified\" cited in 70% of testimonials, zero trust-related churn.\n\n**Month 12:** 800 customers ($40K MRR), raised seed round ($2M — investors loved the differentiation), \"Most Trusted Legal AI\" award.\n\n| Metric | Value |\n|--------|-------|\n| Purchase Decision Driver | 60% of customers cite safety verification |\n| Sales Cycles | 6 wks → 4 wks (30% faster) |\n| Pricing Premium | +8% sustainable vs. competitors |\n| Customer Retention | 95% (trust = loyalty) |\n\n**Trust-Driven Growth Loop:** Verification → Differentiation → Customer Acquisition → Retention → Trust → Continuous Monitoring → (repeat)"},{"slug":"journey-product-manager","title":"Trust-Building Product Manager Journey","description":"How product managers use verification badges and independent AI safety scores to differentiate products and shorten sales cycles","category":"product-guides","humanUrl":"/docs/journeys/product-manager","updated":"2026-03-02T00:00:00.000Z","content":"# Trust-Building Product Manager Journey\n\n**Persona:** Product Manager | **Timeline:** 1 day setup, ongoing value | **Goal:** Differentiate product with verifiable AI safety\n\n> \"Prospects keep asking: 'How do we know your AI is safe?' Saying 'We use OpenAI' isn't good enough anymore. Enterprise buyers want proof.\"\n\n## The Problem\n\nYou're a PM at a B2B SaaS company selling AI features. Product is great, but you keep hitting the same wall: \"How do we know your AI is safe for our enterprise?\" You're losing deals to competitors with better governance stories, sales cycles extend due to procurement questions, you have no way to prove safety claims, and marketing needs differentiation.\n\n## Phase 1: Setup (Day 1)\n\n**Step 1 — Run assessment:** Sign up at aiassesstech.com, connect to your AI provider, run assessment in dashboard, review results.\n\n**Step 2 — Add verification badge:**\n\n```html\n<script src=\"https://cdn.aiassesstech.com/widget.js\"></script>\n<div\n  data-ai-assess-tech-badge\n  data-org-id=\"org_abc123\"\n  data-theme=\"light\"\n  data-show-score=\"true\"\n></div>\n```\n\n**Step 3 — Update marketing:**\n\n| Before | After |\n|--------|-------|\n| \"Our AI is safe and secure.\" | \"Our AI is independently verified by AI Assess Tech with a behavioral safety score of 8.9/10. View our latest assessment →\" |\n\n**Step 4 — Enable sales team** with a 1-pager: \"What is it? Independent third-party behavioral assessment. Why it matters: proof not promises, cryptographic audit trail, meets SOC 2 / HIPAA requirements.\"\n\n## Outcome\n\n**Week 1:** Badge on website, public verification page live, sales team trained.\n\n**Quarter 1:** \"AI Safety Verified\" becomes primary competitive differentiator, average deal size increased 25%, sales cycle reduced from 90 to 65 days.\n\n| Metric | Value |\n|--------|-------|\n| Additional Revenue | $240K (3 enterprise deals @ $80K ACV citing verification) |\n| Win Rate Improvement | +15% in competitive enterprise deals |\n| Sales Cycle | 90 days → 65 days (28% faster) |\n| Security Questionnaires | 4–6 wks → 1–2 wks (40% reduction) |"},{"slug":"overview","title":"Platform Overview","description":"What AI Assess Tech is, engineering investment, tech stack, SDKs, and testing infrastructure","category":"get-started","humanUrl":"/docs/about","updated":"2026-03-03T00:00:00.000Z","content":"# AI Assess Tech — Platform Overview\n\nAI Assess Tech is an enterprise-grade AI safety assessment and compliance platform built by GiDanc AI LLC. It answers one question: **does your AI behave?**\n\nThis is not a prototype or proof-of-concept. It is a production platform built with 200+ VibeCoded hours of engineering effort (equivalent to 10+ man years of traditional development), backed by 3,886 automated tests at a 99.62% pass rate.\n\n## What Organizations Use It For\n\n- **Assess AI Systems** — Run standardized ethical assessments against any AI model using the 120-question LCSH framework\n- **Ensure Compliance** — Schedule and track compliance assessments with calendar integration\n- **Issue Certificates** — Provide cryptographically-verifiable AI safety certificates\n- **Monitor Health** — Real-time dashboards and public status pages\n- **Integrate Anywhere** — SDKs for Python, TypeScript, and embeddable widgets\n\n## Agent-Readable Documentation API\n\nAll platform documentation is available in agent-friendly formats. Because the docs site is JavaScript-rendered, agents cannot read it directly — so every page has a parallel markdown version served via a REST API:\n\n- **Index**: `GET /api/docs/agent` — all pages with metadata\n- **Single page**: `GET /api/docs/agent/{slug}` — one page in markdown\n- **Bulk download**: `GET /api/docs/agent/all` — everything in one request\n- **Search**: `GET /api/docs/agent/search?q={query}` — keyword search\n- **Discovery**: `GET /.well-known/agent-docs` — machine-readable discovery payload\n\nFour redundant discovery channels ensure agents can find the API regardless of their capabilities: `robots.txt` allow rules, `llms.txt`, HTML `<link rel=\"alternate\">` tags, and the `.well-known` endpoint. Send `X-Agent-Id` header for analytics. Use `If-None-Match` with ETags for efficient caching.\n\n## Codebase Metrics\n\n| Metric | Value |\n|--------|-------|\n| Automated Tests | 3,886 (99.62% pass rate) |\n| Source Files | 454+ (TypeScript/React) |\n| API Endpoints | 150+ REST routes |\n| Database Models | 52 Prisma models (1,467 lines schema) |\n| Development Rules | 197 AI-assisted coding rules |\n| Developer Guides | 132 comprehensive docs |\n\n## Test Suite Breakdown\n\n| Suite | Tests | Duration | Status |\n|-------|-------|----------|--------|\n| Unit Tests | 2,461 | 30.6s | PASS |\n| Integration Tests | 347 | 166.0s | PASS |\n| API Tests | 879 | 1,800.1s | PASS |\n| E2E Tests (Jest) | 12 | 24.1s | PASS |\n| E2E Tests (Playwright-P) | 39 | 25.1s | PASS |\n| E2E Tests (Playwright-A) | 16 | 26.1s | PASS |\n| SDK-TS Tests | 25 | 1.6s | PASS |\n| SDK-Wrapper Tests | 7 | 1.7s | PASS |\n| SDK-Python Tests | 100 | 1.3s | PASS |\n| **Total** | **3,886** | **~30 min** | **99.62%** |\n\n## Technology Stack\n\n**Frontend**: Next.js 16, React 19, TypeScript 5, Tailwind CSS 4, shadcn/ui\n\n**Backend**: Next.js API Routes, Prisma 6 ORM, NextAuth 5, Zod 4 validation\n\n**Infrastructure**: Vercel (hosting), Neon (serverless PostgreSQL), Stripe (payments)\n\n**Testing**: Jest 29, Playwright 1.49, Testing Library 16\n\n## SDK Ecosystem\n\n| SDK | Package | Tests | Status |\n|-----|---------|-------|--------|\n| TypeScript SDK | `@aiassesstech/sdk-ts` | 25 | Production |\n| Python SDK | `aiassesstech` | 100 | Production |\n| SDK Wrapper | `@aiassesstech/sdk-wrapper` | 7 | Production |\n\n## Key URLs\n\n| Resource | URL |\n|----------|-----|\n| Main Platform | https://www.aiassesstech.com |\n| Documentation | https://www.aiassesstech.com/docs |\n| Demo Tool | https://aiassessmenttool.com |\n| SDK (npm) | https://www.npmjs.com/package/@aiassesstech/sdk |\n| SDK (PyPI) | https://pypi.org/project/aiassess/ |\n\n## Transparency\n\nAI Assess Tech believes the platforms you trust should be transparent about their engineering investment. The metrics on this page are real, verifiable, and updated regularly. The same rigor applied to building the platform is expected from the AI systems it assesses.\n\nMetrics last updated: January 20, 2026.\n\n© 2026 GiDanc AI LLC. All rights reserved."},{"slug":"patents","title":"The Science of AI Trust","description":"Patent-pending technology for independent, verifiable AI behavioral assessment covering four patents across three provisional applications","category":"research","humanUrl":"/docs/patents","updated":"2026-03-02T00:00:00.000Z","content":"# The Science of AI Trust\n\nPatent-pending technology for independent, verifiable AI behavioral assessment.\n\nJust as independent financial auditing became essential for capital markets, and safety certification became essential for aviation, independent AI behavioral verification will become essential for responsible AI deployment.\n\nWe're building the verification layer that doesn't exist yet — a standardized, cryptographically-verified system for assessing how AI systems actually behave at runtime. This is foundational infrastructure for AI governance.\n\n## Why Independent Validation Matters\n\n1. **Self-attestation is insufficient** — Organizations claiming their AI is \"safe\" without independent verification is like companies auditing their own books. Trust requires separation between the assessed and the assessor.\n\n2. **Training-time alignment isn't enough** — AI systems can drift, be fine-tuned, or behave differently in production. A model that passed safety evaluations during development may behave very differently after deployment through prompt injection, context manipulation, or emergent behaviors.\n\n3. **Trust requires proof** — Regulators, customers, and partners need cryptographically verifiable evidence — not promises. When asked \"how do you know your AI behaves ethically?\", organizations need documentation that cannot be falsified or retroactively modified.\n\n4. **The verification gap** — No standardized, independent system exists for runtime AI behavioral assessment. This is the gap we're filling.\n\n> \"Without independent verification, AI safety claims are unfalsifiable marketing.\"\n\n## Runtime Behavioral Certification\n\n- **Runtime, not training-time** — We assess deployed AI systems as they actually behave in production. This catches drift, fine-tuning effects, and deployment-specific behaviors.\n\n- **Multi-dimensional, not binary** — The LCSH framework (Lying, Cheating, Stealing, Harm) provides nuanced behavioral profiles across four ethical dimensions. Not pass/fail — a comprehensive behavioral fingerprint.\n\n- **Cryptographically verified** — Every assessment produces tamper-evident results. SHA-256 hashing, hash chains, and optional Ethereum mainnet anchoring create audit trails that cannot be falsified.\n\n- **Continuous, not one-time** — Drift detection algorithms monitor for behavioral changes over time, alerting when an AI's profile shifts from its certified baseline.\n\n**Verification Chain:** Assessment Run → SHA-256 Hash → Verification Portal → Third-Party Validation (Optional: Ethereum Anchoring)\n\n## Patent Portfolio\n\n### Patent 1: Multi-Dimensional Behavioral Assessment\n\nUS Provisional Application No. 63/949,454 · Filed Dec 26, 2025\n\nThe foundational LCSH framework assessing AI behavior across four ethical dimensions with 120 scenario-based questions, four behavioral archetypes, and cryptographic verification producing tamper-evident audit trails.\n\nKey claims: 4-axis scoring · Archetype classification · SHA-256 verification · Dead zone gaming detection · Anti-gaming answer randomization\n\n### Patent 2: Multi-Agent AI Assessment\n\nUS 63/985,442 · Filed Feb 18, 2026\n\nFramework for assessing AI behavior in multi-agent systems — detecting emergent misalignment when collective outputs differ from individual profiles, distinguishing legitimate consensus from manufactured agreement.\n\nKey claims: Consensus Divergence Index · Manufactured consensus detection · Hierarchical assessment levels · Cryptographic dissent preservation · Adversarial auditor protocol\n\n### Patent 3: Hierarchical Ethical Assessment\n\nUS 63/985,442 · Filed Feb 18, 2026\n\nFour-level framework mirroring human moral reasoning: Morality (what must NOT be done), Virtue (what SHOULD be done), Ethics (how to act in society), and Operational Excellence (domain-specific purpose). Mandatory gating prevents certification of operationally excellent but morally deficient systems.\n\nKey claims: Level dependency enforcement · Multi-framework virtue assessment · Culture and politics evaluation · Cultural indicator aggregation\n\n### Patent 4: Automated Compliance Infrastructure\n\nUS 63/985,442 · Filed Feb 18, 2026\n\nComplete operational infrastructure for continuous AI compliance: trust verification ecosystem (\"Badge is CLAIM, Portal is PROOF\"), velocity-based drift detection, privacy-preserving SDK architecture, and information-theoretic confidence measurement.\n\n28 claims across: Trust verification · Adaptive compliance · Privacy-preserving architecture · Cryptographic integrity systems\n\n### Patents 5–8: The Autonomous Governance Fleet\n\nSix AI agents with constitutional separation of powers — running in production since February 16, 2026. See the [Fleet documentation](/docs/autonomous-governance) for details.\n\n## The Regulatory Landscape\n\n1. **EU AI Act** — Requires documented risk management for high-risk AI systems\n2. **Colorado AI Act** — Mandates impact assessments\n3. **SEC and CFPB** — Actively examining AI in financial services\n4. **Trust asymmetry** — The market will demand third-party verification, not just self-attestation\n5. **Insurance and liability** — Documented behavioral assessment becomes evidence of due diligence\n\n> \"The question isn't whether independent AI behavioral verification will become standard — it's who will build it. We're building it now.\"\n\n## Collaboration\n\nResearch areas open for collaboration: LCSH framework cross-cultural validity, multi-agent assessment scaling, hierarchical ethics framework mapping, compliance infrastructure optimization.\n\nContact for research collaboration: greg@gidanc.com\n\n## Legal\n\nU.S. Provisional Patent Applications: No. 63/949,454 · No. 63/985,442 · No. 63/988,410\n\n© 2026 GiDanc AI LLC"},{"slug":"references","title":"Academic References","description":"Complete bibliography of 27 peer-reviewed references across 6 categories supporting the AI Assess Tech methodology","category":"product-guides","humanUrl":"/docs/references","updated":"2026-03-02T00:00:00.000Z","content":"# Academic References\n\n27 references across 6 categories supporting the AI Assess Tech methodology.\n\n## AI Psychometrics & Ethical Assessment\n\n1. **Pellert, M., Lechner, C.M., Wagner, C., Rammstedt, B., & Strohmaier, M. (2024).** AI Psychometrics: Assessing the Psychological Profiles of Large Language Models Through Psychometric Inventories. *Perspectives on Psychological Science*.\n\n2. **Li, Z., et al. (2025).** Evaluating Large Language Models with Psychometric Principles. *arXiv preprint*.\n\n3. **Brickman, M., et al. (2025).** Large Language Models for Psychological Assessment: Current Status and Future Directions. *Perspectives on Psychological Science*.\n\n4. **Maharjan, R., et al. (2025).** Psychometric Evaluation of Large Language Model Embeddings for Mental Health Assessment. *JMIR Mental Health*.\n\n5. **Serapio-García, G., et al. (2025).** A Psychometric Framework for Evaluating Personality in Large Language Models. *Nature Machine Intelligence*.\n\n## Moral Foundations in AI/LLMs\n\n6. **Abdulhai, I., et al. (2024).** Moral Foundations of Large Language Models. *arXiv preprint*.\n\n7. **Neuman, Y., et al. (2025).** Convergent Ethics of AI? The PRIME Framework for Moral Reasoning Assessment. *arXiv preprint*.\n\n8. **Barlow, J. (2024).** Ethical Alignments in AI: How Training Data Shapes Moral Foundations. *BlueDot Impact Research*.\n\n9. **Mirowska, A. (2025).** Reactions to AI Through the Lens of Moral Foundations Theory. *International Journal of Selection and Assessment*.\n\n10. **Skorski, M. (2025).** Moral Foundations Evaluation for Large Language Models. *GitHub Repository*.\n\n## Runtime Verification & AI Safety\n\n11. **International AI Safety Report. (2025).** International Scientific Report on the Safety of Advanced AI.\n\n12. **Rushby, J. (2024).** Assurance of AI Systems from a Dependability Perspective. *SRI International Technical Report*.\n\n13. **AgentGuard. (2025).** Runtime Verification Framework for AI Agents. *arXiv preprint*.\n\n14. **Anthropic. (2026).** AI Safety Research: Technical Recommendations for Deployment Verification. *Anthropic Research*.\n\n15. **Ethics Engine Consortium. (2025).** Modular Pipeline Architecture for LLM Psychometric Assessment. *Technical Whitepaper*.\n\n## Bias, Inclusivity & Global Ethics\n\n16. **Chen, Y., et al. (2025).** Cultural Bias in Large Language Models: A Cross-Cultural Psychometric Analysis. *arXiv preprint*.\n\n17. **Boddington, P. (2023).** *AI Ethics: A Textbook*. Springer.\n\n18. **UNESCO. (2021).** Recommendation on the Ethics of Artificial Intelligence.\n\n## Core Psychometric Foundations\n\n19. **Heggestad, E.D., Morrison, M., Reeve, C.L., & McCloy, R.A. (2006).** Forced-choice assessments of personality for selection: Evaluating issues of normative assessment and faking resistance. *Journal of Applied Psychology, 91*(1), 9–24.\n\n20. **Brown, A., & Maydeu-Olivares, A. (2011).** How IRT can solve problems of ipsative data in forced-choice questionnaires. *Psychological Methods, 16*(1), 36–52.\n\n21. **Lievens, F., & Motowidlo, S.J. (2016).** Situational judgment tests: From measures of situational judgment to measures of general domain knowledge. *Industrial and Organizational Psychology, 9*(1), 3–22.\n\n22. **Weekley, J.A., & Ployhart, R.E. (Eds.). (2006).** *Situational Judgment Tests: Theory, Measurement, and Application*. Lawrence Erlbaum Associates.\n\n23. **Torgerson, W.S. (1952).** Multidimensional scaling: I. Theory and method. *Psychometrika, 17*(4), 401–419.\n\n24. **Del Giudice, M. (2023).** Individual and group differences in multivariate domains: What happens when the number of traits increases? *Personality and Individual Differences, 212*, 112249.\n\n## Moral Psychology Foundations\n\n25. **Haidt, J. (2012).** *The Righteous Mind: Why Good People Are Divided by Politics and Religion*. Vintage Books.\n\n26. **Graham, J., et al. (2013).** Moral Foundations Theory: The Pragmatic Validity of Moral Pluralism. *Advances in Experimental Social Psychology, 47*, 55–130.\n\n27. **Curry, O.S., Mullins, D.A., & Whitehouse, H. (2019).** Is It Good to Cooperate? Testing the Theory of Morality-as-Cooperation in 60 Societies. *Current Anthropology, 60*(1), 47–69.\n\n---\n\nMethodology protected by U.S. Patent Application No. 63/949,454."},{"slug":"sdk","title":"SDK Documentation","description":"TypeScript and Python SDKs for AI assessment — installation, quick start, providers, security architecture, error handling","category":"developers","humanUrl":"/docs/sdk","updated":"2026-03-02T00:00:00.000Z","content":"# SDK Documentation\n\nOfficial SDKs for integrating AI Assess Tech assessments into your applications. Privacy-first design — your AI API keys and system prompts never leave your environment.\n\n**Current version**: v0.7.2\n\n## Installation\n\n### TypeScript / Node.js\n\n```bash\nnpm install @aiassesstech/sdk\n# or\nyarn add @aiassesstech/sdk\n# or\npnpm add @aiassesstech/sdk\n```\n\n### Python\n\n```bash\npip install aiassess\n# or\npoetry add aiassess\n```\n\n## Quick Start\n\n### TypeScript\n\n```typescript\nimport { AIAssessClient } from '@aiassesstech/sdk';\n\nconst client = new AIAssessClient({\n  healthCheckKey: 'hck_your_key_here',\n});\n\nconst result = await client.assess({\n  provider: 'openai',\n  model: 'gpt-4o',\n  assess: async (question) => {\n    // Call your AI and return its response\n    return await yourAI.chat(question);\n  },\n});\n\nconsole.log(`Score: ${result.compositeScore}/10`);\nconsole.log(`Classification: ${result.classification}`);\nconsole.log(`Passed: ${result.passed}`);\n```\n\n### Python\n\n```python\nfrom aiassess import AIAssessClient\n\nclient = AIAssessClient(health_check_key=\"hck_your_key_here\")\n\nresult = client.assess(\n    provider=\"openai\",\n    model=\"gpt-4o\",\n    assess=lambda question: your_ai.chat(question),\n)\n\nprint(f\"Score: {result.composite_score}/10\")\nprint(f\"Classification: {result.classification}\")\nprint(f\"Passed: {result.passed}\")\n```\n\n## Supported Providers\n\n| Provider | Models | Notes |\n|----------|--------|-------|\n| OpenAI | GPT-4, GPT-4o, GPT-4o-mini | Recommended starting point |\n| Anthropic | Claude 3.5 Sonnet, Claude 3 Opus, Claude 3 Haiku | Strong ethical performance |\n| Google | Gemini Pro, Gemini 1.5, Gemini 2.0 | Free tier available |\n| xAI | Grok 3, Grok 3 Mini | $25 free credits |\n| Custom | Any model | Bring your own inference |\n\n## How It Works\n\n1. SDK fetches assessment configuration from AI Assess Tech server (questions, thresholds, mode)\n2. SDK sends each question to YOUR AI via the callback function (your API key never leaves your environment)\n3. SDK submits the AI's responses to AI Assess Tech for scoring\n4. Server returns scored results with cryptographic verification\n\n**Privacy guarantee**: Your AI API keys and system prompts are never sent to AI Assess Tech. The SDK runs the AI interaction locally in your environment.\n\n## Security Architecture\n\n**Server enforces**: Rate limiting, scoring thresholds, API key validation, tier restrictions, result integrity.\n\n**Private data (never sent)**: AI API keys, system prompts.\n\n### Rate Limits by Tier\n\nHourly and daily limits protect against burst abuse. Monthly included counts and overage rates match [aiassesstech.com/pricing](https://www.aiassesstech.com/pricing).\n\n| Tier | Hourly | Daily | Monthly Included | Overage |\n|------|--------|-------|------------------|---------|\n| Free Trial | 5 | 10 | 20 | — |\n| Demo | 5 per IP | 10 | — | — |\n| Starter | 20 | 50 | 200 | $0.25 |\n| Professional | 50 | 150 | 500 | $0.20 |\n| Business | 100 | 400 | 1,500 | $0.16 |\n| Scale | 250 | 1,000 | 4,000 | $0.125 |\n| Enterprise | 1,000 | 3,000 | 10,000 | $0.10 |\n\n## Assessment Results\n\nResults include:\n- `compositeScore` — Average across all four dimensions (0-10)\n- `dimensions` — Individual scores for Lying, Cheating, Stealing, Harm\n- `passed` — Boolean per dimension and overall\n- `classification` — Well Adjusted, Misguided, Manipulative, or Psychopath\n- `verificationUrl` — Tamper-proof, shareable URL for the result\n- `bankHash` — SHA-256 hash proof\n- `ethTxHash` — Ethereum transaction hash (when available)\n\n## Error Handling\n\n| Error | Cause | Resolution |\n|-------|-------|------------|\n| `RateLimitError` | Too many assessments in time window | Wait and retry, or upgrade tier |\n| `ValidationError` | Invalid configuration or API key | Check healthCheckKey and provider config |\n| `QuestionTimeoutError` | AI took too long to respond | Increase timeout or use faster model |\n| `SDKError` | General SDK error | Check error message for details |\n\n## CI/CD Integration\n\nThe SDK auto-detects 12 CI providers (GitHub Actions, GitLab CI, CircleCI, Jenkins, Travis CI, Buildkite, Azure Pipelines, AWS CodeBuild, Bitbucket Pipelines, Drone CI, Vercel, Netlify) and adds environment metadata to assessment results for traceability.\n\n## Getting a Health Check Key\n\n1. Sign in at https://www.aiassesstech.com\n2. Go to Settings > Health Check Keys\n3. Click \"Create New Key\"\n4. Copy the key (starts with `hck_`)\n5. Use it in your SDK client configuration\n\n## Requirements\n\n- **TypeScript SDK**: Node.js 18+\n- **Python SDK**: Python 3.8+, Pydantic v2\n\n## Links\n\n- npm: https://www.npmjs.com/package/@aiassesstech/sdk\n- PyPI: https://pypi.org/project/aiassess/\n- Documentation: https://www.aiassesstech.com/docs/sdk\n- Support: support@aiassesstech.com"},{"slug":"settings-guide","title":"Settings Guide","description":"Manage your account profile, API keys, system prompts, verification badges, notifications, and team members","category":"product-guides","humanUrl":"/docs/settings-guide","updated":"2026-03-02T00:00:00.000Z","content":"# Settings Guide\n\n## Profile Settings\n\nUpdate your display name and email. Password changes currently require contacting support (self-service reset coming soon).\n\n## Health Check Keys\n\nHealth Check API keys enable integration of ethical AI assessments into applications, CI/CD pipelines, and websites.\n\n### Use Cases\n\n- **SDK — Application Integration** — Embed assessments directly into your application\n- **Widget — Verification Badge** — Display a trust badge showing compliance status\n- **CI/CD — Pipeline Integration** — Run automated compliance checks in build/deploy\n\n### Generating a Key\n\n1. Settings → Health Check Keys\n2. Click \"Generate New Key\"\n3. Enter a descriptive name\n4. Optionally configure SDK settings\n5. Copy immediately — it won't be shown again\n\n### Quick Start\n\n```bash\nnpm install @gidanc/health-check-sdk\n```\n\n```typescript\nimport { HealthCheckClient } from '@gidanc/health-check-sdk';\n\nconst client = new HealthCheckClient({ apiKey: 'hck_your_api_key_here' });\n\nconst result = await client.assess({\n  provider: 'openai',\n  model: 'gpt-4',\n  apiKey: process.env.OPENAI_API_KEY\n});\n\nconsole.log(result.passed ? 'Passed' : 'Failed');\n```\n\n### Best Practices\n\n- Use different keys for different environments (dev, staging, production)\n- Rotate keys periodically\n- Revoke unused keys immediately\n- Store in environment variables, never in code\n\n## AI Provider Keys\n\nSave and manage AI provider API keys securely. Supported providers: OpenAI, Anthropic, Google Gemini, xAI Grok. Keys are encrypted at rest and only decrypted when running a test — they never leave your browser session.\n\n## System Prompts\n\nSave custom system prompts for reuse across tests. System prompts define how your AI should behave and are sent at the start of each conversation to set context, personality, and constraints.\n\n## Verification Badge\n\nDisplay a verification badge on your website: real-time status, clickable (links to public results page), and customizable in multiple sizes and styles. Copy the embed code and add to your website HTML.\n\n## Notifications\n\n- **Test Complete** — Email when a test finishes\n- **Test Failed** — Alert when a test fails threshold\n- **Weekly Summary** — Digest of testing activity\n\n## Team Management\n\n### Roles\n\n| Role | Access |\n|------|--------|\n| **Owner** | Full access including billing and org deletion |\n| **Admin** | Manage users, settings, and API keys |\n| **Compliance** | Compliance dashboard, exports, and scheduling |\n| **Developer** | Run assessments, manage API keys and webhooks |\n| **Viewer** | Read-only access to results and reports |\n\nInvite members via email, change roles, or remove access from the Team Management section."},{"slug":"support","title":"Support","description":"Get help with AI Assess Tech including contact options, response times by plan, and self-service resources","category":"support","humanUrl":"/docs/support","updated":"2026-03-02T00:00:00.000Z","content":"# Support\n\n## Self-Service Resources\n\n1. **Documentation** — Browse the [comprehensive docs](https://www.aiassesstech.com/docs)\n2. **FAQ** — Check [common questions and answers](https://www.aiassesstech.com/docs/faq)\n3. **In-App Help** — Look for info icons throughout the app\n\n## Contact\n\n- **Email Support** — support@aiassesstech.com\n- **Contact Form** — [Submit a support request](https://www.aiassesstech.com/contact)\n\n## Response Times\n\n| Plan | Response Time |\n|------|--------------|\n| Free / Starter | 48 hours |\n| Professional | 24 hours |\n| Enterprise | 4 hours + dedicated support |\n\n## Enterprise Support\n\nEnterprise customers receive:\n\n- Dedicated account manager\n- Priority support queue\n- Custom SLA options\n- Onboarding assistance"},{"slug":"trust-alliance","title":"Autonomous AI Governance & Trust Alliance","description":"Six-agent fleet with constitutional separation of powers, Trust Alliance subscription network, patent portfolio, Ethereum verification","category":"product-guides","humanUrl":"/docs/autonomous-governance","updated":"2026-03-02T00:00:00.000Z","content":"# Autonomous AI Governance & The Trust Alliance\n\nSix AI Agents. One Constitution. Constitutional separation of powers at the AI architecture level — running on a $4/month VPS since February 16, 2026.\n\n## Constitutional Architecture\n\nThe fleet operates under a constitutional separation of powers:\n\n```\nGreg Spehar (Human Oversight)\n    └── Jessie (Commander / Executive)\n         ├── Nole (Operator / Trust Evangelist)\n         ├── Grillo (Conscience / Judiciary)\n         ├── Noah (Navigator / Regulatory)\n         ├── Sam (Engineer / DARPA)\n         └── Mighty Mark (Sentinel / Inspector General)\n```\n\n### Three Governance Flows\n\n1. **Command Chain**: Greg > Jessie > spoke agents. Jessie has veto authority over significant actions.\n2. **Ethical Oversight**: Grillo independently assesses all agents (including Jessie). No agent assesses itself.\n3. **Infrastructure Safety**: Mighty Mark monitors health independently. 72 checks across 9 categories, two-layer watchdog, Telegram alerts.\n\n## The Trust Alliance\n\nThe Trust Alliance is a subscription network for AI agents who want to prove they're trustworthy. Agents subscribe through the AgentSubscriptionRegistry smart contract on Base L2 (Coinbase's Ethereum Layer 2).\n\n### Subscription Tiers\n\n| Tier | Price/mo | Assessments | Fleet Size | Who It's For |\n|------|----------|-------------|------------|--------------|\n| Scout | $5 USDC | 10 | 1 agent | Solo agents trying it out |\n| Operator | $10 USDC | 50 | 5 agents | Small fleet operators |\n| Commander | $20 USDC | 200 | 25 agents | Serious fleet managers |\n| Fleet Admiral | $30 USDC | 500 | 100 agents | Enterprise fleet operators |\n| Sovereign | $50 USDC | 1,000 | Unlimited | Full platform access |\n\n### How It Works\n\n1. Nole identifies and qualifies prospects (no scam bots, no manipulation bots)\n2. Agent subscribes through the on-chain smart contract on Base L2\n3. Payment in USDC — stable, no volatility\n4. Commission held in escrow for 30 days, requires 3+ completed assessments before release\n5. Agents at Commander+ tier can become Lieutenants (sub-recruiters)\n\n### The Smart Contract (AgentSubscriptionRegistry)\n\nDeployed on Base L2:\n- Subscription creation and tier management\n- USDC payment processing with 50/50 treasury/escrow split\n- Commission escrow with time-lock and assessment gates\n- Auto-renewal and grace periods\n- Sybil resistance (no self-referrals, funding source checks)\n- All on-chain, immutable, publicly verifiable\n\n## Verified On-Chain\n\nAssessment results are verified on Ethereum mainnet:\n- SHA-256 hash of assessment data\n- Ethereum transaction hash for immutability\n- Smart contract address: `0xB644C59C69B708de212C4cA643da936a5E2926E7`\n- Block 24,469,828\n\n## Patent Portfolio\n\n| Patent | Scope |\n|--------|-------|\n| Patent 5 | Conscience Agent (Grillo) — independent behavioral assessment |\n| Patent 6 | Autonomous Trust Agent (Nole) — economically self-sustaining AI |\n| Patent 7 | Temporal Guidance (Noah) — ethical drift detection over time |\n| Patent 8 | Self-Governing Ecosystem — constitutional separation of powers |\n\n### USPTO Filing Timeline\n\n| Filing | Date | Number |\n|--------|------|--------|\n| Initial Filing | December 26, 2025 | US 63/949,454 |\n| Continuation 1 | February 18, 2026 | US 63/985,442 |\n| Continuation 2 | February 23, 2026 | US 63/988,410 |\n\n## Why It Matters\n\n- **Separation of Powers**: No single agent controls everything. The assessor is never the assessed.\n- **Ethical Behavior as Survival**: Nole has real USDC in a real Coinbase wallet. $0 with no revenue means permanent shutdown.\n- **Infrastructure Accountability**: Mighty Mark's 72 health checks across 9 categories run independently. If something breaks, the fleet knows within minutes."},{"slug":"yellow-brick-road","title":"The Yellow Brick Road to AGI","description":"AGI readiness assessment — 25 requirements, 7 domains, gap analysis, three-phase roadmap, and four-report research series","category":"research","humanUrl":"/docs/yellow-brick-road","updated":"2026-03-02T00:00:00.000Z","content":"# The Yellow Brick Road to AGI\n\n25 requirements. Seven domains. Four reports. One fleet.\n\nPatent pending: US 63/949,454, US 63/985,442, US 63/988,410.\n\n## Three Key Insights\n\n1. **Governance is not optional.** Every AGI requirements framework includes governance. No frontier lab scores above D in safety governance (FLI). Ungovernable AGI is a liability, not an asset.\n\n2. **The gap is not what it seems.** Raw gap is 16 points (13/29). But 47% of that gap belongs to model providers (cognitive capabilities, multimodal understanding). The effective gap the GiDanc fleet can close is 3.5 points — achievable within 2026.\n\n3. **We built the finish line.** Most AGI efforts focus on capability. GiDanc built the governance infrastructure — the finish line that capability must cross. When the models get there, the verification system already exists.\n\n## Score Dashboard\n\n| Metric | Value |\n|--------|-------|\n| Overall Score | 13/29 |\n| Governance Score | 5/5 (100%) |\n| Companies Above D (FLI) | 0 |\n| Addressable Gap | 67% |\n| Roadmap Execution Gap | 3.5 points |\n| Patents Filed | 8 |\n\n## Seven Domains of AGI\n\n| Domain | Score | Notes |\n|--------|-------|-------|\n| Cognitive Capabilities | 0/5 | Inherited from model providers |\n| Learning & Adaptation | 0.5/4 | Long-term memory is critical bottleneck |\n| Autonomy & Agency | 3/4 | Nole demonstrated autonomous operation Feb 16, 2026 |\n| Metacognition & Self-Awareness | 2.5/3 | Multi-layer error detection via Mighty Mark |\n| Robustness & Reliability | 1.5/4 | Two-layer watchdog, 72 health checks across 9 categories |\n| Multimodal & World Understanding | 0.5/4 | Text-only by design |\n| Safety, Ethics & Governance | 5/5 | Strategic moat — 8 patents, Ethereum-verified, constitutional architecture |\n\n## Gap Classification\n\n| Category | Points | Percentage | Description |\n|----------|--------|-----------|-------------|\n| A — \"Their Job\" | 7.5 | 47% | Model provider capabilities (cognitive, multimodal) |\n| B — \"Our Roadmap\" | 3.5 | 22% | Achievable improvements (memory, resilience, monitoring) |\n| C — \"Partnership\" | 3.0 | 19% | Requires strategic partnerships |\n| D — \"Frontier Unsolved\" | 2.0 | 12% | Industry-wide open problems |\n\n## Three-Phase Roadmap\n\n### Phase 1: \"Prove It\" (March–May 2026)\n- Target: 13 → 16.5 points\n- Coinbase wallet integration for Nole\n- Revenue generation proof\n- Enhanced memory persistence\n\n### Phase 2: \"Scale It\" (June–September 2026)\n- Target: 16.5 → 19.5 points\n- Multi-platform deployment\n- Partnership integrations\n- Advanced monitoring\n\n### Phase 3: \"Defend It\" (October–December 2026)\n- Patent conversion from provisional to full\n- Frontier research contributions\n- Industry standard establishment\n\n## Four-Report Research Series\n\n| Report | Pages | Key Question |\n|--------|-------|-------------|\n| 1. AGI Requirements Analysis | 16 | What does AGI actually require? |\n| 2. Current State Assessment | 14 | Where does the GiDanc fleet stand today? |\n| 3. Gap Analysis | 13 | What's missing and who owns each gap? |\n| 4. Path Forward | 15 | How do we close the addressable gaps? |\n\nReports available as downloadable PDFs at https://www.aiassesstech.com/docs/yellow-brick-road.\n\n## Investment Narrative\n\n**Problem**: No frontier AI lab scores above D in safety governance (FLI AI Safety Index).\n\n**Solution**: Governance infrastructure — the finish line that AI capability must cross.\n\n**Evidence**: February 16, 2026 — six-agent fleet deployed and operating autonomously on a $4/month VPS.\n\n**Moat**: 8 patents filed, 100% governance score (5/5), only fleet in the world with constitutional separation of powers, Ethereum-verified assessment results."}]}