A substantial engineering investment in enterprise-grade AI safety infrastructure
AI Assess Tech isn't a prototype or proof-of-concept. It's a production platform with 814,776 lines of original code, including production and tests, built with 750+ VibeCoded hours of engineering effort. At 100 hours Before AI (BAI) for every 1 hour of VibeCoding, the total BAI level of effort is about 35–40 man years. Backed by 17,112 automated tests, 254 AI governance rules, 659K VibeCoding session lines across 152 development threads, and 2,779,462 lines of supporting documentation.
This page provides transparency into the engineering foundation that makes AI Assess Tech a trustworthy platform for AI behavioral assessment.
Real numbers from a real production system. Updated 9/9/2026. Code, tests, and documentation are a first-party source count. VibeCoding session lines are aggregated from local Cursor development history (not shipped code).
814,776
Lines of Code
480,282 production + 334,494 tests17,112
Automated Tests
4,968 suites, source count2,779,462
Supporting Documentation
Git-tracked .md and .mdc files659K
VibeCoding Session Lines
152 Cursor threads, local history219
API Endpoints
REST API route files254
AI Governance Rules
243 live, 11 superseded100
Database Models
3,914 lines schemaKey investments that make the AI Assess Tech SaaS platform enterprise-ready.
ANET-AGI-001 is a production deployment of 6 autonomous AI agents — running in production since February 16, 2026 — each with independent ethical oversight, temporal behavioral tracking, and constitutional governance. It represents a second major engineering investment equal in scale to the core platform, and the first demonstrated implementation of runtime AI governance with separation of powers.
Patent-pending Three-Variable Guidance Equation with flight plans, corridor tracking, and inertial ethical monitoring
97
Files
532
Tests
15,900
Lines
LCSH assessment framework with drift detection, fleet anomaly detection, and SHA-256 audit chains
46
Files
408
Tests
17,392
Lines
7-step morning briefing protocol with veto authority, DecisionStore, and 8 fleet tools
29
Files
316
Tests
4,283
Lines
Coinbase CDP wallet on Base L2, multi-platform social, and 25 agent tools with Commander approval gates
54
Files
408
Tests
13,684
Lines
Engineering pipeline manager with Docker sandbox, memory persistence, and 10 fleet tools
27
Files
146
Tests
5,714
Lines
64+ health checks across 12 categories, morning report via Telegram, watchdog auto-restart, and predictive preflight probes
88
Files
1420
Tests
26,845
Lines
| Package | Description | Files | Tests | Lines |
|---|---|---|---|---|
| Fleet Bus | Constitutional inter-agent messaging | 38 | 390 | 8,145 |
| Fleet Alerting | Severity-routed escalation system | 13 | 7 | 1,225 |
| Prompt Shield | 11-layer injection defense | 81 | 143 | 5,022 |
| Mission Control | 28-panel glass cockpit dashboard | 272 | 757 | 57,908 |
Every feature is backed by comprehensive automated testing across both the platform and fleet.

Harness snapshot from 9/9/2026. Current counts are the source inventory dated 9/9/2026.
| Category | Location | Files | Lines |
|---|---|---|---|
| Platform tests | __tests__ | 1,028 | 224,353 |
| Package tests | packages/ | 323 | 66,838 |
| App tests | apps/ | 153 | 17,223 |
| Deployment tests | deployment/ | 41 | 15,721 |
| Other first-party tests | Remaining first-party test files | 49 | 10,359 |
| TOTAL | 17,112 tests, 4,968 suites | 1,594 | 334,494 |
Built on modern, well-supported technologies for long-term maintainability.
Official SDKs for seamless integration into your applications.
@aiassesstech/sdkFull-featured SDK for Node.js and browser environments
aiassesstechNative Python SDK for data science and backend integrations
@aiassesstech/sdk-wrapperLightweight wrapper for quick integrations
We believe the platforms you trust should be transparent about their engineering investment. The metrics on this page are real, verifiable, and updated regularly. When you use AI Assess Tech, you're using a platform built with the same rigor we expect from the AI systems we assess.
Metrics last updated: 9/9/2026
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