Investment Thesis
Coditect captures the white space between code assistants and enterprise compliance—the only autonomous platform spanning development, business, and operations with native regulatory alignment.
| Thesis Element | Evidence |
|---|
| Market timing | <50% AI ROI (WSJ), regulated domains worst performers |
| Category creation | No competitor at High Autonomy + High Compliance |
| Founder-market fit | 30+ years regulated industry experience |
| Technical moat | Multi-agent orchestration, compliance-native architecture |
| GTM clarity | HealthTech beachhead → FinTech → Pharma |
The Problem
"Less than 50% of AI projects generate positive ROI, with the biggest failures in security, legal, and healthcare."
— Wall Street Journal, 2024
| Pain Point | Impact | Validation |
|---|
| Compliance delays | 40-60% of project time | [PROOF: Customer interviews → TBD] |
| Audit preparation | 2-4 weeks per audit | [PROOF: Customer interviews → TBD] |
| Documentation burden | 20+ hours/month manual | [PROOF: Customer interviews → TBD] |
| AI tool disappointment | <50% positive ROI | WSJ 2024 |
| Tool Category | Gap |
|---|
| Code assistants (Copilot, Cursor) | Zero compliance awareness |
| Workflow automation (Microsoft) | Development not addressed |
| Consulting (Capgemini, Deloitte) | Manual, expensive, slow |
| Internal tools | Maintenance burden, doesn't scale |
Customer Quote Placeholder:
"[Quote about compliance pain from customer interview]"
— [Title], [Company] (HealthTech, [X] engineers)
The Solution
Three-Domain Autonomous Orchestration
┌────────────────────────────────────────────────────────┐
│ CODITECT PLATFORM │
├──────────────┬──────────────┬──────────────────────────┤
│ DEVELOPMENT │ BUSINESS │ OPERATIONS │
│ │ │ │
│ Autonomous │ Proposal │ Document │
│ code gen │ generation │ automation │
│ │ │ │
│ Testing │ Research │ Compliance │
│ & QA │ synthesis │ operations │
│ │ │ │
│ Compliance │ Competitive │ Audit trail │
│ validation │ intelligence│ generation │
├──────────────┴──────────────┴──────────────────────────┤
│ UNIFIED COMPLIANCE LAYER │
│ FDA | HIPAA | SOC2 | SOX | GDPR │
└────────────────────────────────────────────────────────┘
Technical Differentiation
| Capability | Coditect Approach | Competitor Approach |
|---|
| Agent architecture | Multi-agent orchestration (15x token efficiency) | Single-agent prompting |
| Compliance | Native, continuous validation | None or bolt-on |
| State management | FoundationDB (ACID, distributed) | Stateless or basic |
| Audit trails | Automatic, complete | Manual or partial |
Traction & Validation
Customer Validation
| Metric | Target | Current | Status |
|---|
| Customer interviews | 50+ | [X] | [Status] |
| Letters of intent | 5+ ($500K+) | [X] ($[X]K) | [Status] |
| Pilot customers | 5+ active | [X] | [Status] |
| Waitlist | 500+ | [X] | [Status] |
Pilot Metrics [Placeholder]
| Customer | Industry | Metric | Result |
|---|
| [Customer 1] | HealthTech | Time to compliant feature | [X days → X days] |
| [Customer 2] | FinTech | First-pass approval rate | [X% → X%] |
| [Customer 3] | HealthTech | Audit preparation time | [X weeks → X hours] |
Case Study Placeholder:
[Customer Name] (HealthTech, [X] engineers)
Challenge: [Specific pain point]
Solution: Coditect [tier] implementation
Results:
- Time to compliant feature: [X months → X days]
- Audit findings: [X → 0]
- Developer velocity: [X]x improvement
Quote: "[Executive quote about results]"
— [Name], [Title]
Market Opportunity
TAM/SAM/SOM
| Market | Size | Rationale |
|---|
| TAM | $50B+ | Custom software development in regulated industries |
| SAM | $5B | HealthTech + FinTech compliance-focused development |
| SOM | $500M | Mid-market companies with 10-500 engineers |
Market Validation
| Signal | Data Point | Source |
|---|
| Enterprise AI readiness | 80% planning agent integration (12-18 mo) | Microsoft/IDC |
| Agentic AI growth | 3x adoption in 24 months | IDC |
| Regulated industry focus | 70%+ AI penetration in customer service, IT, product | Industry reports |
| AI ROI crisis | <50% positive returns | WSJ 2024 |
Business Model
Pricing Tiers
| Tier | Target | Monthly | Key Features |
|---|
| Team | 10-25 eng | $2,500 + usage | SOC2, 3 agents |
| Enterprise | 25-100 eng | $10,000 + usage | FDA/HIPAA, unlimited agents |
| Strategic | 100+ eng | $50,000 + custom | White-glove, custom tuning |
Unit Economics [Placeholder]
| Metric | Target | Current |
|---|
| Average Contract Value | $120K-$180K | [TBD] |
| Gross Margin | 70-80% | [TBD] |
| CAC Payback | <12 months | [TBD] |
| LTV:CAC | 10:1 | [TBD] |
| Net Revenue Retention | >120% | [TBD] |
Revenue Projections [Placeholder]
| Year | ARR | Customers | ACV |
|---|
| Year 1 | $[X]M | [X] | $[X]K |
| Year 2 | $[X]M | [X] | $[X]K |
| Year 3 | $[X]M | [X] | $[X]K |
Go-to-Market Strategy
Phase 1: HealthTech Beachhead (Year 1)
| Element | Approach |
|---|
| Target | $5-50M ARR HealthTech companies |
| Sales motion | Direct outbound to CTOs |
| Partnerships | Rock Health, HealthTech accelerators |
| Proof required | 3+ case studies, 10+ customers |
Phase 2: FinTech Expansion (Year 2)
| Element | Approach |
|---|
| Target | $50M+ ARR FinTech companies |
| Sales motion | Account-based marketing |
| Partnerships | Compliance platforms (Vanta, Drata) |
| Proof required | HealthTech references, SOX expertise |
Phase 3: Pharma/Life Sciences (Year 3)
| Element | Approach |
|---|
| Target | $500M+ revenue Pharma/Life Sciences |
| Sales motion | Enterprise sales + channel partners |
| Partnerships | Digital transformation consultancies |
| Proof required | FDA validation, enterprise references |
Competitive Positioning
Market Map
High Autonomy
│
GitHub Copilot ─────┼───── Cursor
│
Low Compliance ──────┼────── High Compliance
│
Microsoft Copilot │ ★ CODITECT
│
Low Autonomy
Competitive Analysis
| Dimension | Coditect | Copilot | Cursor | Microsoft |
|---|
| Scope | Dev+Biz+Ops | Code only | Code only | Workflows |
| Autonomy | Multi-agent | Completion | Pair | Task |
| Compliance | Native | None | None | Add-on |
| Target | Regulated | General | Developers | Enterprise |
Moat
| Moat Type | Coditect Advantage | Durability |
|---|
| Domain expertise | 30+ years regulated industry | High |
| Technical architecture | Multi-agent + compliance-native | Medium-High |
| Data flywheel | Compliance patterns across customers | Increasing |
| Switching costs | Embedded in compliance workflows | High |
Team
Founder
Hal Casteel — CEO/CTO
- 30+ years healthcare operations and enterprise software
- Former: Oracle NetSuite, Capgemini, GRAIL
- Deep FDA, HIPAA, healthcare IT expertise
- Google AI Accelerator participant
Advisory Board [Placeholder]
| Advisor | Domain | Credentials |
|---|
| [Name] | Healthcare CTO | [Background] |
| [Name] | FDA/Regulatory | [Background] |
| [Name] | AI/ML | [Background] |
| [Name] | SaaS GTM | [Background] |
Hiring Plan
| Role | Timeline | Priority |
|---|
| VP Engineering | Q1 | P0 |
| Head of Sales | Q2 | P0 |
| Customer Success Lead | Q2 | P1 |
| Senior ML Engineer | Q2 | P1 |
Financials [Placeholder]
Current Status
| Metric | Value |
|---|
| Stage | Pre-seed / Seed |
| Prior funding | $[X] |
| Monthly burn | $[X]K |
| Runway | [X] months |
Use of Funds
| Category | Allocation | Purpose |
|---|
| Engineering | 50% | Platform development, ML infrastructure |
| Sales & Marketing | 30% | GTM execution, customer acquisition |
| Operations | 20% | G&A, compliance certifications |
Milestones to Next Round
| Milestone | Target | Timeline |
|---|
| Pilot customers | 10+ | Month 6 |
| ARR | $500K | Month 12 |
| Case studies | 5+ | Month 9 |
| NRR | >120% | Month 12 |
The Ask
Raise
| Element | Detail |
|---|
| Round | Seed |
| Target | $[X]M |
| Use | Engineering (50%), GTM (30%), Ops (20%) |
| Timeline | [X] months runway |
Investor Value-Add
| Area | Need |
|---|
| HealthTech network | Customer introductions |
| Enterprise sales | GTM expertise |
| Regulatory | FDA/compliance connections |
| Follow-on | Series A pathway |
Appendix
A. Product Screenshots [Placeholder]
[Insert product demo screenshots]
B. Technical Architecture [Placeholder]
[Insert architecture diagram]
C. Compliance Framework Detail [Placeholder]
| Framework | Coverage | Validation Status |
|---|
| FDA 21 CFR Part 11 | [%] | [Status] |
| HIPAA | [%] | [Status] |
| SOC2 Type II | [%] | [Status] |
| SOX | [%] | [Status] |
D. Customer Testimonials [Placeholder]
"[Quote 1]"
— [Name], [Title], [Company]
"[Quote 2]"
— [Name], [Title], [Company]
"[Quote 3]"
— [Name], [Title], [Company]
E. Market Research Sources
| Source | Key Finding | Date |
|---|
| WSJ | <50% AI ROI | 2024 |
| Microsoft/IDC | 80% planning agents | 2024 |
| Gartner | 85% transformation failure | 2024 |
| [Customer interviews] | [Finding] | [Date] |
Proof Point Collection Status
Claims Requiring Evidence
| Claim | Evidence Required | Status | Target Date |
|---|
| "Days, not months" | Pilot metrics | 🔴 TBD | [Date] |
| "4-10x velocity" | Customer data | 🔴 TBD | [Date] |
| "90% audit reduction" | Before/after | 🔴 TBD | [Date] |
| "First-pass approval" | PR analytics | 🔴 TBD | [Date] |
Validation Confidence Levels
| Section | Confidence | Notes |
|---|
| Problem statement | ✅ High | WSJ data, market research |
| Solution capability | 🟡 Medium | Architecture built, needs customer validation |
| Market size | ✅ High | Third-party research |
| Traction | 🔴 Low | Needs customer data |
| Financial projections | 🔴 Low | Needs historical data |
Document Version: Investor Draft 1.0
Status: Proof Points Pending
Last Updated: January 2026
AZ1.AI Inc.
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