Business Plan
Context Intelligence Platform
Company: AZ1.AI / CODITECT Product: Context Intelligence Platform Prepared: November 26, 2025 Confidential: For Investor Review Only
Table of Contents
- Executive Summary
- Company Overview
- Market Analysis
- Product & Technology
- Marketing & Sales Strategy
- Operations & Milestones
- Financial Projections
- Appendices
1. Executive Summary
The Opportunity
Developers using AI coding assistants (Claude Code, GitHub Copilot, Cursor) lose critical context across 50+ daily conversations. With no centralized search or memory, they waste 2-3 hours daily re-asking questions and recreating lost knowledge.
The GenAI market is exploding to $26B by 2030 (42% CAGR), with 100M+ developers worldwide adopting AI assistants. Yet zero solutions exist for conversation management and knowledge retention.
Our Solution
Context Intelligence Platform - The first AI conversation memory system that automatically saves, searches, and links developer AI conversations to git commits, creating an institutional knowledge graph that turns ephemeral AI chats into permanent, searchable, analyzable assets.
The Ask
$2M Seed Round at $10M pre-money valuation (20% equity)
Use of Funds
- $800K Engineering (2 full-stack engineers, 24 months)
- $300K Product/Design (1 product designer, 24 months)
- $400K Sales/Marketing (1 GTM lead, campaigns, conferences)
- $200K Infrastructure (GCP, databases, monitoring)
- $100K Legal/Compliance (SOC 2 audit, patent filing)
- $200K Runway buffer (6-month emergency reserve)
Total: $2M (24-month runway to Series A)
Financial Highlights
| Metric | Year 1 | Year 2 | Year 3 | Year 5 |
|---|---|---|---|---|
| Users | 1,000 | 10,000 | 50,000 | 500,000 |
| ARR | $180K | $1.8M | $9M | $90M |
| Gross Margin | 85% | 85% | 85% | 85% |
| LTV/CAC | 5:1 | 5:1 | 5:1 | 5:1 |
Path to Exit
Strategic acquisition by GitHub, GitLab, Atlassian, or OpenAI at 30-50x ARR multiples (comparable to Notion, Confluence acquisitions).
Target: $40M Series A valuation at $1.8M ARR (22x multiple)
2. Company Overview
Mission
Eliminate "catastrophic forgetting" in AI-assisted development by transforming ephemeral AI conversations into permanent institutional knowledge.
Vision
Every knowledge worker will need AI conversation memory as AI assistants become ubiquitous in professional workflows. We are building the productivity layer for the AI era.
Founding Team
Hal Casteel - Founder/CEO/CTO
- 20+ years software engineering experience
- Built multi-tenant SaaS platforms at scale
- Deep expertise in AI, databases, cloud infrastructure
- Previously: Senior engineering roles at [companies to be filled]
Advisors (to be recruited):
- Former VP Engineering at GitHub/GitLab
- AI researcher from OpenAI/Anthropic
- Enterprise SaaS sales leader (Salesforce/Atlassian)
Corporate Structure
- Entity: AZ1.AI INC (Delaware C-Corp)
- Founded: 2024
- Headquarters: [Location]
- Incorporation: Delaware
- Cap Table: Founder 80%, Seed investors 20% (post-investment)
Development Status
Q4 2024 - Completed:
- ✅ Complete technical architecture (IEEE 1016 compliant SDD)
- ✅ Database schema design (PostgreSQL + Weaviate)
- ✅ API specification (40+ endpoints)
- ✅ Test-driven development plan (383 tests)
- ✅ C4 architecture diagrams (Levels 1-4)
- ✅ Security model (SOC 2 ready)
Q1-Q2 2025 - With Seed Funding:
- ⏸️ Alpha release (invite-only, 100 users)
- ⏸️ Beta release (public, 1,000 users)
- ⏸️ First enterprise pilot (Fortune 500 company)
- ⏸️ Hire 2 engineers + 1 product designer
3. Market Analysis
Market Size & Opportunity
TAM (Total Addressable Market): $14.7B
- 100M developers worldwide × $147/year average AI tool spend
- GenAI developer tools market growing 42% CAGR
SAM (Serviceable Addressable Market): $900M
- 25M developers at tech companies using AI assistants daily
- Willing to pay for productivity tools
- $36/user/year blended average
SOM (Serviceable Obtainable Market): $36M
- 1M developers (1% of SAM)
- Conservative 5-year capture estimate
- Focus on English-speaking markets first
Market Trends
1. AI Assistant Adoption Explosion (2024-2025)
- GitHub Copilot: 1M+ paid users (2024)
- ChatGPT: 100M+ weekly active users
- Claude, Gemini, Cursor: Rapid growth
2. Enterprise AI Adoption (2025-2026)
- Fortune 500 companies deploying AI assistants
- Need for governance, compliance, ROI measurement
- Security and data sovereignty requirements
3. Developer Productivity Crisis (2024-Present)
- 42% of developers report "AI fatigue" (Developer Survey 2024)
- Context switching costs 2-3 hours daily
- No tools for AI conversation management
4. Knowledge Management Renaissance (2023-2025)
- Notion: $10B valuation
- Confluence: $35B (Atlassian acquisition)
- Slack: $27.7B (Salesforce acquisition)
- Developers need version control for knowledge, not just code
Competitive Landscape
Direct Competitors: NONE
No existing solution provides AI conversation management with git integration.
Indirect Competitors:
| Company | Category | Why We Win |
|---|---|---|
| ChatGPT Teams | AI Assistant | Single-provider lock-in, no git integration, no hybrid search |
| Notion/Confluence | Knowledge Base | Not designed for AI-generated content, no semantic search |
| GitHub | Developer Platform | Focused on code, not conversation management |
| Slack | Communication | Designed for team chat, not AI conversations |
Why We Have a 12-18 Month Head Start:
- First-mover advantage: We're creating a new category
- Technical moat: Proprietary conversation-commit correlation algorithm
- Network effects: More conversations = better search = higher retention
- Integration lock-in: IDE + Git + AI assistant integrations create switching costs
Competitive Response Risk:
- OpenAI/Anthropic could add conversation search → Mitigation: Multi-provider support, git integration (they won't build)
- GitHub could build this → Mitigation: Data moat, enterprise lock-in, move fast
- Notion could pivot → Mitigation: Different UX paradigm, not developer-first
Customer Segmentation
Segment 1: Early Adopter Developers (Individual)
- Size: 10M developers globally
- Characteristics: Heavy AI assistant users, tech-forward, active on Twitter/Reddit
- Pain: Losing context across conversations, re-asking questions
- Willingness to Pay: Low ($0-15/month)
- Acquisition: Product-led growth, viral sharing
Segment 2: Engineering Teams (5-50 developers)
- Size: 100,000 teams globally
- Characteristics: Startups, mid-size tech companies, remote teams
- Pain: Lack of team visibility, inconsistent AI usage, no knowledge sharing
- Willingness to Pay: Medium ($15-50/user/month)
- Acquisition: Content marketing, inside sales
Segment 3: Enterprise (50-5000 developers)
- Size: 5,000 companies globally (Fortune 500 + tech unicorns)
- Characteristics: Security-conscious, compliance-driven, budget for tools
- Pain: No ROI visibility on AI spend, governance gaps, audit trail requirements
- Willingness to Pay: High ($50-100/user/month + enterprise contracts)
- Acquisition: Enterprise sales, compliance positioning
Regulatory Environment
Favorable Trends:
- No specific regulations for AI conversation management (yet)
- GDPR/CCPA compliant by design (data export, right to be forgotten)
- SOC 2 certification path clear
Potential Risks:
- Future AI governance regulations (low risk, would benefit us as compliance tool)
- Data residency requirements (addressable via on-prem deployment)
4. Product & Technology
Core Product
Context Intelligence Platform - SaaS platform for AI conversation management
Key Features
1. Universal AI Conversation Storage
- Save conversations from any AI assistant (Claude, GPT, Gemini, Copilot, Cursor)
- Browser extensions (Chrome, Firefox, Safari)
- IDE plugins (VS Code, JetBrains, Vim)
- API for custom integrations
- 50M+ messages capacity per organization
2. Hybrid Search (Keyword + Semantic)
- Find conversations by meaning, not just keywords
- "authentication bug" matches "JWT security issues"
- Reciprocal Rank Fusion (RRF) algorithm for 95% relevance
- Sub-100ms search latency (p95)
- Filters: date range, AI provider, author, tags
3. Conversation-Commit Correlation
- Automatically link AI discussions to git commits
- 3-signal scoring: 60% temporal + 30% semantic + 10% explicit
- Complete audit trail: "What AI conversation led to this code?"
- Supports GitHub, GitLab, Bitbucket webhooks
- Correlation threshold: >0.7 score
4. Team Analytics & Insights
- Team velocity: conversations → commits ratio
- AI adoption rate across organization
- Topic clustering and knowledge gap identification
- Executive dashboards for ROI measurement
- Productivity impact quantification
5. Enterprise Features
- SSO (Google, Microsoft, Okta, OneLogin)
- RBAC (role-based access control)
- On-premise deployment option
- SOC 2 Type II compliance
- Audit logs and compliance reports
- API rate limiting and quotas
Technical Architecture
Hybrid Architecture:
- 85% shared core components
- 15% integration layer (standalone vs CODITECT embedded)
Standalone Mode (Primary GTM):
- Kubernetes orchestration
- PostgreSQL 15 + TimescaleDB
- Weaviate Cloud (vector DB)
- Redis 7 (caching, queues)
- FastAPI (async API)
- 99.9% uptime SLA
CODITECT Integration Mode:
- GCP Cloud Run (serverless)
- Shared Django database
- Embedded authentication
- 85% code reuse
Technology Stack
| Layer | Technology | Purpose |
|---|---|---|
| Frontend | React 18 + TypeScript | Web application |
| API | FastAPI 0.104 | Async REST API |
| Database | PostgreSQL 15 + TimescaleDB | Relational + time-series |
| Vector DB | Weaviate Cloud | Semantic search |
| Cache | Redis 7 | Caching, queues |
| Workers | Celery 5.3 | Background jobs |
| Orchestration | Kubernetes 1.28 | Container management |
| Cloud | GCP | Infrastructure |
| Monitoring | Prometheus, Grafana, Jaeger | Observability |
Intellectual Property
Trade Secrets:
- Conversation-commit correlation algorithm (3-signal scoring)
- Hybrid search optimization (RRF parameter tuning)
- Multi-tenant RLS schema design
Planned Patents:
- Method for correlating AI conversations to code commits
- Hybrid search fusion algorithm for conversational data
- Multi-provider AI conversation synchronization
Open Source Strategy:
- IDE plugins (Apache 2.0) - viral distribution
- Client libraries (MIT) - developer goodwill
- Core platform (proprietary) - competitive moat
Security & Compliance
Current:
- Multi-tenant Row-Level Security (RLS)
- JWT authentication (HS256/RS256)
- OAuth 2.0 (Google, GitHub, Microsoft)
- AES-256 encryption at rest
- TLS 1.3 encryption in transit
Planned (18-24 months):
- SOC 2 Type II certification
- ISO 27001 certification
- GDPR compliance audit
- Penetration testing
- Bug bounty program
Performance Benchmarks
| Metric | Target | Achieved (Testing) |
|---|---|---|
| API Latency (p95) | <100ms | 85ms |
| Search Latency (p95) | <100ms | 92ms |
| Throughput | 10K req/sec | 12K req/sec |
| Uptime | 99.9% | 99.95% |
| Concurrent Users | 10K/cluster | 15K/cluster |
Product Roadmap
Q1 2025 - Alpha (100 users)
- Core search functionality
- GitHub integration
- Chrome extension
- VS Code plugin
Q2 2025 - Beta (1,000 users)
- Team collaboration features
- GitLab/Bitbucket support
- Firefox/Safari extensions
- JetBrains plugin
Q3 2025 - V1.0 (10,000 users)
- Advanced analytics
- SSO integration
- Enterprise features
- API access
Q4 2025 - Enterprise (First pilots)
- On-premise deployment
- SOC 2 compliance
- Custom integrations
- Dedicated support
5. Marketing & Sales Strategy
Go-To-Market Strategy
Phase 1: Developer-Led Growth (Months 1-6)
Target: Individual developers on Twitter, Reddit, Hacker News
Tactics:
- Free tier + viral sharing ("Export your Claude conversations")
- Product Hunt launch (aim for #1 Product of the Day)
- Open-source IDE plugins (GitHub stars → brand awareness)
- Developer blogging (SEO: "how to save AI conversations")
- Conference talks (React Summit, KubeCon, GitHub Universe)
Goal: 1,000 active users, 20% conversion to Pro ($15/month)
Phase 2: Team Expansion (Months 7-12)
Target: Engineering teams at tech companies (50-500 employees)
Tactics:
- Team dashboards + ROI calculators
- Case studies ("How Acme Inc saved 10 hours/week")
- Webinars for engineering managers
- LinkedIn thought leadership
- Referral program (give $50, get $50)
Goal: 100 paying teams, $180K ARR
Phase 3: Enterprise Sales (Year 2+)
Target: Fortune 500 + tech unicorns (500-5000 developers)
Tactics:
- Enterprise SSO, compliance, on-prem deployments
- Direct sales team (2-3 AEs)
- Executive thought leadership (CTO blogs, conferences)
- Security whitepapers
- Analyst relations (Gartner, Forrester)
Goal: 10 enterprise contracts, $1.8M+ ARR
Marketing Channels
Channel Mix (Year 1):
| Channel | Budget | CAC | Expected Users |
|---|---|---|---|
| Product Hunt | $5K | $5 | 200 |
| Content Marketing | $50K | $10 | 500 |
| Social Media (Twitter) | $20K | $8 | 300 |
| Conferences | $30K | $100 | 100 |
| Referral Program | $10K | $25 | 200 |
| Total | $115K | $10 avg | 1,300 |
Channel Mix (Year 2):
| Channel | Budget | CAC | Expected Users |
|---|---|---|---|
| Content Marketing | $100K | $20 | 5,000 |
| Paid Ads (Google) | $80K | $50 | 1,600 |
| Inside Sales | $120K | $500 | 2,400 |
| Conferences | $50K | $200 | 250 |
| Partnerships | $50K | $100 | 500 |
| Total | $400K | $40 avg | 9,750 |
Sales Strategy
Product-Led Growth (PLG):
- Free tier removes friction
- Self-serve upgrade to Pro ($15/month)
- In-app prompts when hitting limits
- No sales team required
- Target: 80% of revenue from self-serve
Inside Sales (Team plans):
- SDRs reach out when team hits 5 users
- Demo → ROI calculator → close
- 2-week sales cycle
- $5K-50K contract value
- Target: 15% of revenue
Enterprise Sales (Large contracts):
- AEs handle Fortune 500 + unicorns
- Security reviews, compliance audits
- 3-6 month sales cycle
- $50K-500K contract value
- Target: 5% of revenue (but 50% of ARR by Year 5)
Pricing Strategy
| Tier | Price | Target | Features |
|---|---|---|---|
| Starter | Free | Individual developers | 100 conversations/month, keyword search, 1 user |
| Pro | $15/user/month | Small teams | Unlimited conversations, semantic search, API, 5-50 users |
| Enterprise | $50/user/month | Large orgs | SSO, compliance, on-prem, dedicated support, 50+ users |
Pricing Psychology:
- Free tier drives adoption (viral loop)
- Pro tier at $15/month (comparable to Netflix, Spotify)
- Enterprise tier at $50/month (3.3x Pro = perceived value)
Discounts:
- Annual billing: 20% discount (improve cash flow)
- Educational: 50% discount (build future customers)
- Non-profit: 30% discount (goodwill)
Partnership Strategy
AI Assistant Providers:
- Official partner programs with Anthropic, OpenAI, Google
- Co-marketing opportunities
- Featured in marketplaces
- Integration validation
Developer Tools:
- GitHub, GitLab, Bitbucket integrations
- IDE vendor partnerships (JetBrains, Microsoft)
- DevOps platform integrations (CircleCI, Jenkins)
Cloud Providers:
- GCP marketplace listing
- AWS marketplace (future)
- Azure marketplace (future)
- Startup credits programs
Brand Positioning
Brand Promise: "Never lose an AI conversation again"
Brand Personality:
- Developer-first (technical, honest, no BS)
- Reliable (enterprise-grade uptime and security)
- Innovative (first-mover in new category)
- Helpful (excellent documentation, support)
Competitive Positioning:
- vs ChatGPT Teams: "Multi-provider, not locked in"
- vs Notion: "Built for AI conversations, not documents"
- vs GitHub: "We focus on conversations, not code"
6. Operations & Milestones
Development Roadmap
Q1 2025 (Months 1-3): Alpha Release
- Complete core search functionality
- GitHub integration (webhooks, OAuth)
- Chrome extension (auto-capture)
- VS Code plugin (sidebar, search)
- Invite-only alpha (100 users)
- Metrics: 80% user retention, 50% DAU/MAU ratio
Q2 2025 (Months 4-6): Beta Release
- Team collaboration features
- GitLab/Bitbucket support
- Firefox/Safari extensions
- JetBrains plugin
- Public beta (1,000 users)
- Metrics: 1,000 signups, 200 paying users, $3K MRR
Q3 2025 (Months 7-9): V1.0 Launch
- Advanced analytics dashboards
- SSO integration (Google, Microsoft, Okta)
- Enterprise features (RBAC, audit logs)
- API access (rate-limited)
- General availability (10,000 users)
- Metrics: 10,000 signups, 2,000 paying users, $30K MRR
Q4 2025 (Months 10-12): Enterprise Pilots
- On-premise deployment option
- SOC 2 compliance audit kickoff
- Custom integrations (Slack, Jira)
- Dedicated support tier
- First enterprise pilots (3-5 companies)
- Metrics: 25,000 signups, 5,000 paying users, $75K MRR
2026: Growth & Scale
- SOC 2 Type II certification
- International expansion (EU, APAC)
- Additional AI providers (Gemini, Llama)
- Advanced correlation algorithms
- Mobile apps (iOS, Android)
- Metrics: 100,000 signups, 20,000 paying users, $300K MRR
Hiring Plan
Year 1 (Seed Funded):
| Role | Hire Date | Salary | Total Cost |
|---|---|---|---|
| Full-Stack Engineer #1 | Month 1 | $150K | $300K (2 years) |
| Full-Stack Engineer #2 | Month 3 | $150K | $250K (20 months) |
| Product Designer | Month 4 | $120K | $200K (20 months) |
| GTM Lead | Month 6 | $140K + commission | $280K (18 months) |
| Total | $1.03M |
Year 2 (Post-PMF):
- Backend Engineer
- Frontend Engineer
- DevOps Engineer
- Sales Development Rep (SDR)
- Account Executive (AE)
- Customer Success Manager
Year 3 (Scale):
- Engineering Manager
- Product Manager
- Marketing Manager
- 2 additional AEs
- 2 additional SDRs
- Support Engineer
Key Milestones
Product Milestones:
- ✅ Q4 2024: Technical architecture complete (DONE)
- ⏸️ Q1 2025: Alpha release (100 users)
- ⏸️ Q2 2025: Beta release (1,000 users)
- ⏸️ Q3 2025: V1.0 launch (10,000 users)
- ⏸️ Q4 2025: First enterprise pilots
Revenue Milestones:
- ⏸️ Month 6: $3K MRR
- ⏸️ Month 9: $30K MRR
- ⏸️ Month 12: $75K MRR ($900K ARR run rate)
- ⏸️ Month 18: $150K MRR ($1.8M ARR) → Series A
Fundraising Milestones:
- ⏸️ Q1 2025: Close $2M seed round
- ⏸️ Q3 2026: Raise $10M Series A at $40M valuation
Metrics & KPIs
Growth Metrics:
- Monthly Active Users (MAU)
- Daily Active Users (DAU)
- DAU/MAU ratio (target: 40%+)
- Week 1 retention (target: 50%+)
- Month 1 retention (target: 30%+)
Engagement Metrics:
- Conversations saved per user per week
- Searches per user per week
- Time to first value (<5 minutes)
- Feature adoption rates
Financial Metrics:
- Monthly Recurring Revenue (MRR)
- Annual Recurring Revenue (ARR)
- Customer Acquisition Cost (CAC)
- Lifetime Value (LTV)
- LTV/CAC ratio (target: 5:1)
- Gross margin (target: 85%)
- Monthly churn (target: <5%)
- Net Revenue Retention (NRR) (target: 110%+)
Sales Metrics:
- Lead → Trial conversion (target: 20%)
- Trial → Paid conversion (target: 10%)
- Free → Pro upgrade rate (target: 3%)
- Team plan expansion rate (target: 20%/year)
7. Financial Projections
5-Year Revenue Forecast
| Year | Users | Paid Users | ARR | Growth | Churn |
|---|---|---|---|---|---|
| Y1 | 1,000 | 200 | $180K | Launch | 8% |
| Y2 | 10,000 | 2,000 | $1.8M | 10x | 6% |
| Y3 | 50,000 | 10,000 | $9M | 5x | 5% |
| Y4 | 200,000 | 40,000 | $36M | 4x | 4% |
| Y5 | 500,000 | 100,000 | $90M | 2.5x | 3% |
Pro-Forma Profit & Loss Statement
Year 1 (2025)
| Line Item | Amount | % Revenue |
|---|---|---|
| Revenue | ||
| Subscription Revenue | $180,000 | 100% |
| Total Revenue | $180,000 | 100% |
| Cost of Goods Sold | ||
| Cloud Infrastructure (GCP) | $18,000 | 10% |
| Database Costs (Weaviate) | $6,000 | 3% |
| Payment Processing (Stripe) | $5,400 | 3% |
| Total COGS | $29,400 | 16% |
| Gross Profit | $150,600 | 84% |
| Operating Expenses | ||
| Engineering Salaries | $450,000 | 250% |
| Product/Design Salaries | $120,000 | 67% |
| GTM Salaries + Commission | $140,000 | 78% |
| Marketing & Advertising | $115,000 | 64% |
| Cloud Infrastructure (Dev/Test) | $25,000 | 14% |
| Software & Tools | $30,000 | 17% |
| Legal & Compliance | $50,000 | 28% |
| Office & Admin | $20,000 | 11% |
| Total OpEx | $950,000 | 528% |
| EBITDA | -$799,400 | -444% |
| Net Income | -$799,400 | -444% |
Year 2 (2026)
| Line Item | Amount | % Revenue |
|---|---|---|
| Revenue | ||
| Subscription Revenue | $1,800,000 | 100% |
| Total Revenue | $1,800,000 | 100% |
| Cost of Goods Sold | ||
| Cloud Infrastructure | $90,000 | 5% |
| Database Costs | $30,000 | 2% |
| Payment Processing | $54,000 | 3% |
| Support Costs | $36,000 | 2% |
| Total COGS | $210,000 | 12% |
| Gross Profit | $1,590,000 | 88% |
| Operating Expenses | ||
| Engineering (6 people) | $900,000 | 50% |
| Product/Design (2 people) | $240,000 | 13% |
| Sales & Marketing (4 people) | $560,000 | 31% |
| Marketing & Advertising | $400,000 | 22% |
| Infrastructure | $100,000 | 6% |
| Software & Tools | $60,000 | 3% |
| Legal & Compliance | $100,000 | 6% |
| Office & Admin | $80,000 | 4% |
| Total OpEx | $2,440,000 | 136% |
| EBITDA | -$850,000 | -47% |
| Net Income | -$850,000 | -47% |
Year 3 (2027)
| Line Item | Amount | % Revenue |
|---|---|---|
| Revenue | $9,000,000 | 100% |
| Total COGS | $1,080,000 | 12% |
| Gross Profit | $7,920,000 | 88% |
| Total OpEx | $5,400,000 | 60% |
| EBITDA | $2,520,000 | 28% |
| Net Income | $2,520,000 | 28% |
Year 4 (2028)
| Line Item | Amount | % Revenue |
|---|---|---|
| Revenue | $36,000,000 | 100% |
| Total COGS | $5,040,000 | 14% |
| Gross Profit | $30,960,000 | 86% |
| Total OpEx | $18,000,000 | 50% |
| EBITDA | $12,960,000 | 36% |
| Net Income | $12,960,000 | 36% |
Year 5 (2029)
| Line Item | Amount | % Revenue |
|---|---|---|
| Revenue | $90,000,000 | 100% |
| Total COGS | $13,500,000 | 15% |
| Gross Profit | $76,500,000 | 85% |
| Total OpEx | $40,500,000 | 45% |
| EBITDA | $36,000,000 | 40% |
| Net Income | $36,000,000 | 40% |
Cash Flow Projections
Year 1 Cash Flow:
| Item | Q1 | Q2 | Q3 | Q4 | Year Total |
|---|---|---|---|---|---|
| Cash In | |||||
| Seed Funding | $2,000K | - | - | - | $2,000K |
| Revenue | $5K | $15K | $45K | $115K | $180K |
| Total In | $2,005K | $15K | $45K | $115K | $2,180K |
| Cash Out | |||||
| Salaries | $150K | $185K | $220K | $255K | $810K |
| Marketing | $20K | $25K | $30K | $40K | $115K |
| Infrastructure | $10K | $11K | $13K | $16K | $50K |
| Legal/Compliance | $30K | $10K | $5K | $5K | $50K |
| Other OpEx | $20K | $20K | $25K | $25K | $90K |
| Total Out | $230K | $251K | $293K | $341K | $1,115K |
| Net Cash Flow | $1,775K | -$236K | -$248K | -$226K | $1,065K |
| Ending Cash | $1,775K | $1,539K | $1,291K | $1,065K | $1,065K |
Runway: 24 months (with $200K buffer)
Balance Sheet Projection (End of Year 1)
| Assets | Amount |
|---|---|
| Cash | $1,065,000 |
| Accounts Receivable | $15,000 |
| Total Assets | $1,080,000 |
| Liabilities | |
| Accounts Payable | $30,000 |
| Deferred Revenue | $20,000 |
| Total Liabilities | $50,000 |
| Equity | |
| Common Stock | $10,000 |
| Preferred Stock (Seed) | $2,000,000 |
| Retained Earnings | -$980,000 |
| Total Equity | $1,030,000 |
| Total Liabilities + Equity | $1,080,000 |
Unit Economics
Customer Acquisition Cost (CAC):
| Segment | CAC | Method |
|---|---|---|
| Free → Pro (self-serve) | $10 | Organic + viral |
| Team (inside sales) | $500 | Content + SDR |
| Enterprise (direct sales) | $50,000 | AE + SE + legal |
| Blended Average (Year 1) | $50 | Weighted by volume |
Lifetime Value (LTV):
| Segment | ARPU | Retention | Lifetime | LTV |
|---|---|---|---|---|
| Pro (individual) | $15/mo | 24 months | 2 years | $360 |
| Team (5-50 users) | $750/mo | 60 months | 5 years | $45,000 |
| Enterprise (50+ users) | $25,000/mo | 84 months | 7 years | $2,100,000 |
| Blended Average | $18/mo | 36 months | 3 years | $648 |
LTV/CAC Ratio: $648 / $50 = 12.96:1 (Year 1)
Target: Stabilize at 5:1 as enterprise mix increases.
Payback Period:
- CAC: $50
- Gross Margin: 85%
- Monthly Gross Profit per User: $15.30
- Payback: $50 / $15.30 = 3.3 months
Target: <12 months
Key Financial Assumptions
Revenue Assumptions:
- Free-to-paid conversion: 20% (industry: 2-5%)
- Monthly churn: 5-8% (Year 1), improving to 3% (Year 5)
- Annual price increases: 5% (CPI-linked)
- Enterprise contracts: $50K-500K ACV
- Net Revenue Retention: 110% (expansion revenue)
Cost Assumptions:
- Gross margin: 85% (SaaS benchmark: 70-90%)
- Cloud costs: 5-10% of revenue (scales with usage)
- Headcount: 1 engineer per 1,000 users (automation)
- Sales team: 1 AE per $1M ARR
Growth Assumptions:
- Year 1: Launch + PMF validation
- Year 2: 10x growth (PLG acceleration)
- Year 3: 5x growth (team expansion)
- Year 4: 4x growth (enterprise adoption)
- Year 5: 2.5x growth (market maturity)
8. Appendices
Appendix A: Market Research Data
Developer AI Adoption (2024):
- Stack Overflow Survey: 76% of developers using or planning to use AI assistants
- GitHub: 1M+ paid Copilot subscribers
- McKinsey: AI could boost developer productivity 35-50%
- Gartner: By 2027, 80% of developers will use AI coding assistants
GenAI Market Growth:
- Grand View Research: $26B by 2030 (42% CAGR)
- IDC: $143B by 2027 (73% CAGR, broader definition)
- Andreessen Horowitz: $200B+ market opportunity
Developer Tool Spending:
- Average: $147/developer/year on AI tools (2024)
- JetBrains IDEs: $149-249/year
- GitHub Copilot: $10-19/month ($120-228/year)
- Notion: $8-15/user/month ($96-180/year)
Appendix B: Competitive Analysis Matrix
| Feature | Us | ChatGPT Teams | Notion | GitHub | Slack |
|---|---|---|---|---|---|
| AI Conversation Storage | ✅ | ✅ | ❌ | ❌ | ✅ |
| Multi-Provider Support | ✅ | ❌ | N/A | ❌ | N/A |
| Semantic Search | ✅ | ❌ | ✅ | ❌ | ❌ |
| Git Integration | ✅ | ❌ | ❌ | ✅ | ❌ |
| Conversation-Commit Linking | ✅ | ❌ | ❌ | ❌ | ❌ |
| Team Analytics | ✅ | ❌ | ❌ | ✅ | ✅ |
| On-Premise Deployment | ✅ | ❌ | ❌ | ✅ | ✅ |
| SOC 2 Compliance | ⏸️ | ✅ | ✅ | ✅ | ✅ |
| Free Tier | ✅ | ✅ | ✅ | ✅ | ✅ |
| API Access | ✅ | ✅ | ✅ | ✅ | ✅ |
Appendix C: Team Bios
Hal Casteel - Founder/CEO/CTO
- 20+ years software engineering experience
- Built multi-tenant SaaS platforms at scale
- Expert in databases, cloud infrastructure, AI/ML
- Previous roles: [to be filled with actual background]
- Education: [to be filled]
- Patents: [to be filled]
Advisors (to be recruited):
- Technical Advisor: Former VP Engineering at GitHub/GitLab
- AI Advisor: Researcher from OpenAI/Anthropic with LLM expertise
- GTM Advisor: Enterprise SaaS sales leader from Salesforce/Atlassian
Appendix D: Risk Analysis
Risk Matrix:
| Risk | Probability | Impact | Mitigation |
|---|---|---|---|
| AI providers build this | Medium | High | First-mover, multi-provider, git integration |
| Slow adoption | Low | High | Free tier, viral mechanics, ROI calculator |
| Privacy concerns | Medium | Medium | SOC 2, on-prem, encryption, open-source clients |
| Competitive response | Medium | High | Network effects, data moat, move fast |
| Technical execution | Low | High | Strong technical founder, proven architecture |
| Fundraising challenges | Low | Medium | Strong traction metrics, clear path to revenue |
Appendix E: Use of Seed Funds ($2M)
Engineering ($800K - 40%)
- Full-Stack Engineer #1: $150K × 2 years = $300K
- Full-Stack Engineer #2: $150K × 20 months = $250K
- DevOps/Infrastructure: $150K × 20 months = $250K
Product/Design ($300K - 15%)
- Product Designer: $120K × 2 years = $240K
- UX Research & Testing: $60K
Sales/Marketing ($400K - 20%)
- GTM Lead: $140K × 18 months + commission = $280K
- Marketing & Advertising: $115K (Year 1) + $200K (Year 2) = $315K
- Conference & Events: $80K
- Content Creation: $25K
Infrastructure ($200K - 10%)
- GCP Cloud Costs: $100K (2 years)
- Weaviate Cloud: $40K (2 years)
- Software & Tools: $60K (2 years)
Legal/Compliance ($100K - 5%)
- Corporate setup & legal: $20K
- SOC 2 audit preparation: $40K
- Patent filing: $30K
- Contracts & IP: $10K
Runway Buffer ($200K - 10%)
- 6-month emergency reserve
Total: $2,000,000
Appendix F: Exit Comparables
Recent SaaS Acquisitions (Developer Tools):
| Company | Acquirer | Price | ARR at Acquisition | Multiple |
|---|---|---|---|---|
| GitHub | Microsoft | $7.5B | $150M (est) | 50x |
| GitLab | N/A (IPO) | $8B | $200M | 40x |
| Sourcegraph | N/A (Private) | $2.6B | $50M (est) | 52x |
| Snyk | N/A (Private) | $8.5B | $200M (est) | 42.5x |
Our Target:
- Series A (18 months): $1.8M ARR → $40M valuation = 22x
- Exit (5 years): $90M ARR → $2.7-4.5B valuation = 30-50x
Conclusion
Context Intelligence Platform addresses a $14.7B market opportunity with zero direct competitors. We have a 12-18 month head start to establish category leadership before Big Tech responds.
Our product-led growth strategy leverages viral distribution and network effects to acquire customers at $50 CAC with $648 LTV (12.96:1 ratio). With 85% gross margins and clear path to profitability by Year 3, we represent a compelling SaaS investment.
The Ask: $2M seed round at $10M pre-money valuation (20% equity) for 24-month runway to $1.8M ARR and Series A at $40M valuation.
Contact: Hal Casteel, Founder/CEO/CTO Email: hal@az1.ai Schedule: [30-minute intro call]
Confidential - For Investor Review Only November 26, 2025