CODITECT — AI-Native Change Control for Regulated Industries
AZ1.AI Inc. · Confidential · February 2026
The Problem
Every change to a validated system in pharma, biotech, and medical devices requires a formal Work Order — planned, approved, executed, documented, and audited. Today this process is manual: paper forms or bolted-on CMMS tools that weren't built for compliance. The result: $4.2M average annual cost for mid-tier biotech, 23-day average cycle times, 340+ hours/year in audit preparation, and 15–30% of engineering time consumed by compliance documentation instead of engineering work.
No existing platform combines autonomous AI agents with regulatory-native change control. CMMS vendors (Maximo, SAP PM, TrackWise) lack AI. AI dev tools (Cursor, Copilot) lack compliance. CODITECT occupies the only empty quadrant.
The Solution
CODITECT's Work Order system is a 9-state finite state machine with built-in compliance gates, powered by 7 specialized AI agent nodes that autonomously orchestrate work orders from planning through closure — with human approval checkpoints where regulations require them.
| Capability | What It Means |
|---|---|
| Autonomous agent orchestration | 7 AI agents handle scheduling, resource matching, compliance checking, documentation, and QA review — humans approve at gates, agents do the work between them |
| Compliance-native architecture | FDA 21 CFR Part 11 e-signatures, HIPAA technical safeguards, SOC 2 change management built into the state machine — not bolted on after the fact |
| Intelligent model routing | Opus for compliance/security, Sonnet for complex logic, Haiku for boilerplate → 40–60% token cost reduction vs. single-model approaches |
| Immutable audit trail | Every state transition, agent action, and human decision cryptographically recorded — audit-ready by default, not by effort |
Architecture: Multi-tenant PostgreSQL with row-level security · 20+ entity data model · Event-driven (NATS) · OTEL observability · Eclipse Theia IDE shell · LangGraph agent orchestration
Market
| Metric | Value | Source |
|---|---|---|
| TAM | $3.5B | Global QMS + CMMS for regulated industries |
| SAM | $892M | AI-enabled QMS for pharma/biotech/MedDev |
| SOM (Year 1) | $26.8M | Mid-tier US biotech, direct sales |
| CAGR | 13.6% | Biotech QMS software through 2035 |
Entry wedge: 200–2,000 employee FDA-regulated bioscience companies running 500–5,000 WOs/year on spreadsheets, SharePoint, or first-gen CMMS. Pain is acute (audit findings, 483s, consent decree risk), switching cost from CODITECT is low (no existing AI agent integration to migrate from), and deal size is $150K–$500K ARR.
Unit Economics
| Metric | Value |
|---|---|
| ACV | $150K–$500K |
| Gross Margin | 78% |
| LTV:CAC | 18.7× |
| CAC Payback | 7 months |
| Net Revenue Retention | 130%+ (projected) |
| Customer ROI | 287% Year 1 (conservative) |
Customer value breakdown: $1.68M/year in labor cost reduction + compliance cost avoidance + audit efficiency gains + risk reduction, against $150K–$500K annual platform cost. Payback period for the customer: 4–6 months.
Competitive Moat
- Compliance-native architecture — competitors would need 18+ months to build regulatory infrastructure from scratch; CODITECT has it as the foundation layer
- Agent + change control convergence — no CMMS vendor has native AI agent integration; no AI tool has regulatory compliance; CODITECT is first to combine both
- Switching cost escalation — once audit trails, e-signatures, and compliance evidence are in CODITECT, migration cost is prohibitive (regulated companies can't risk data integrity gaps during transitions)
- Data flywheel — every WO execution improves scheduling accuracy, resource matching, and duration estimates; this compounds across tenants within the same regulatory domain
Traction & Validation
- Google AI Accelerator program participant
- 30+ years founder experience in healthcare IT and enterprise software (including GRAIL Inc., FDA-regulated medical devices)
- Complete technical specification delivered: 62 artifacts covering architecture, compliance, agents, market analysis, and interactive dashboards (21,000+ lines)
- 90% audit-ready across FDA Part 11, HIPAA, and SOC 2 — with a documented 28-prompt plan to reach 100%
Go-to-Market
Phase 1 (Months 1–12): 3–5 design partners from mid-tier US biotech. Compliance-led sales: generate gap analysis showing audit risks → demonstrate WO system closing those gaps → pilot on one validated system → expand to full QMS.
Phase 2 (Months 12–24): Expand to MedDev and CRO verticals. Add IVDR/MDR compliance modules. Channel partnerships with quality consultancies.
Phase 3 (Months 24–36): Enterprise pharma. Multi-site deployment. Marketplace for compliance modules and agent extensions.
The Ask
Seeking strategic partners and early investors who bring regulated-industry domain expertise, enterprise sales channels, or deep AI/compliance experience. The platform architecture is specified and validated. The market gap is documented. The competitive window is open — but closing as CMMS vendors begin exploring AI boltons.
Hal Casteel · CEO/CTO · hal@az1.ai · AZ1.AI Inc.
This document contains confidential information. Distribution requires NDA.
Copyright 2026 AZ1.AI Inc. All rights reserved. Developer: Hal Casteel, CEO/CTO Product: CODITECT-BIO-QMS | Part of the CODITECT Product Suite Classification: Internal - Confidential