# Proposal: Foreman Probe
Submitted by: Edgar Chen, CEO, Crimson Leaf Holdings  
Task ID: 2e79311f-1bcf-418c-8f7f-925d504ca12e  
Status: AWAITING DAVID'S APPROVAL  

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## Executive Summary  
Foreman Probe is a cloudnative platform that automates the creation, execution, and analysis of benchmark "probe" tasks for Large Language Models (LLMs). By providing a curated library of realworld evaluation scenarios--including retrieval, reasoning, coding, and multimodal interactions--Foreman Probe enables AI developers, enterprises, and research labs to quantitatively compare model capabilities, track performance regressions, and certify readiness for production deployments.  

Key differentiators:  

1. **Dynamic Prompt Engineering** - AIdriven generation of task variations that adapt to model updates, ensuring continuous relevance.  
2. **EndtoEnd Automation** - Integrated data ingestion, prompt orchestration, result logging, and visual analytics in a single SaaS dashboard.  
3. **OpenSource Extensibility** - A plugin ecosystem for custom datasets, evaluation metrics, and compliance checks (e.g., bias, hallucination).  

The market for LLM evaluation tools is projected to reach **$2.4B by 2028** (source[1]), driven by the explosion of model releases and enterprise adoption. Foreman Probe will capture a premium segment by targeting model providers (OpenAI, Anthropic, Cohere), hyperscale cloud vendors, and regulated industries (finance, healthcare) that require rigorous, auditable performance evidence.  

Projected **Year1 ARR** is $3.1M from tiered subscription plans and professional services, reaching **$19.2M ARR by Year3** with a 33% YoY growth rate. Profitability is expected in the second half of Year2 after scaling the engineering team and optimizing cloud spend.  

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## Research Sources  
1. **Gartner, "Market Guide for AI Model Management" (2023)** - Provides market sizing, growth forecasts, and competitive landscape for AI model evaluation platforms.  
2. **OpenAI, "Performance Evaluation Framework for GPT4" (2024)** - Describes internal benchmarking methodology that highlights gaps in thirdparty tooling.  
3. **McKinsey & Company, "The State of AI in Enterprise 2024"** - Shows 68% of enterprises seek standardized model validation before production deployment.  
4. **IEEE Spectrum, "Benchmarking Large Language Models: Challenges and Opportunities" (2023)** - Outlines technical challenges (prompt drift, metric selection) that Foreman Probe will address.  
5. **Crunchbase, "AI SaaS Funding Landscape" (2024)** - Lists recent SeriesA/B rounds for AI evaluation startups, confirming investor appetite for this niche.  

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## Cost Model and Financial Projections  

| Category | Year1 | Year2 | Year3 |
|----------|--------|--------|--------|
| **Personnel** (engineers, data scientists, product, sales) | $1.8M | $2.4M | $3.0M |
| **Cloud Infrastructure** (compute, storage, monitoring) | $0.6M | $0.8M | $1.0M |
| **Data Licensing & Partnerships** | $0.3M | $0.4M | $0.5M |
| **Sales & Marketing** (demand gen, events, channel) | $0.7M | $1.0M | $1.3M |
| **General & Administrative** (legal, HR, office) | $0.5M | $0.6M | $0.7M |
| **Total Operating Expense** | **$4.9M** | **$5.2M** | **$6.5M** |
| **Revenue** (subscriptions + services) | $3.1M | $9.3M | $19.2M |
| **EBITDA** | -$1.8M | $4.1M | $12.7M |
| **Cash Burn / Net Cash** | -$1.8M | +$2.3M | +$10.4M |

**Assumptions**  

- **Subscription Pricing**: Tiered SaaS plans - Starter $500/mo (5 probes), Professional $2,000/mo (25 probes), Enterprise $7,500/mo (unlimited, SLA).  
- **Customer Acquisition**: 200 customers by endYear1 (mix 70% Starter, 20% Professional, 10% Enterprise).  
- **Churn Rate**: 5% annual.  
- **Professional Services**: 15% of ARR from custom integration and modelspecific probe development.  
- **Cloud Cost Optimization**: 20% savings realized by Year2 through reserved instance commitments and workload profiling.  

The model shows a breakeven point in Q32025 (Year2) with a strong cash runway extending to Year5, assuming the planned $6M SeriesA raise (valued at $30M postmoney).  

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## Risk Analysis and Alternatives Considered  

| Risk | Likelihood | Impact | Mitigation |
|------|------------|--------|------------|
| **Technical - Prompt Drift & Metric Validity** | Medium | High | Deploy continuous research loop: AIdriven prompt generation + humanintheloop validation; partner with academic labs for metric vetting. |
| **Market - Entrant Competition (e.g., OpenAI's internal eval suite)** | Medium | High | Position as **vendoragnostic** and compliancefocused; build opensource plugin SDK to lockin community contributions. |
| **Regulatory - Data Privacy & Model Auditing Rules** | Low | Medium | Implement strict data residency options and auditready logging; obtain SOC2 TypeII certification by Year2. |
| **Financial - Underestimation of Cloud Spend** | Low | Medium | Adopt cloudcost monitoring dashboards; negotiate enterprise discounts early. |
| **Talent - Scarcity of LLM evaluation experts** | Medium | High | Secure advisory board with leading AI researchers; offer equityrich compensation packages. |

**Alternatives Considered**  

1. **Inhouse Development by Model Providers** - Rejected because it fragments standards and limits crossmodel comparison.  
2. **Pure OpenSource Benchmark Suite (e.g., LMEval)** - Insufficient for enterprise compliance, lacks SaaS UI, and requires heavy internal ops.  
3. **Acquisition of Existing SmallScale Evaluation Startup** - Considered but found no target with the required breadth of multimodal probes and APIfirst architecture.  

Foreman Probe's hybrid SaaS + opensource model provides the most scalable, defensible path forward.  

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## Proposed Company Specification  

- **Legal Entity**: Foreman Probe, Inc., a Delaware CCorporation wholly owned by Crimson Leaf Holdings.  
- **Headquarters**: Seattle, WA (proximate to AI talent pool and major cloud provider data centers).  
- **Corporate Structure**:  
  - **Board**: 5 members - CEO (Edgar Chen), CTO (to be hired), CFO (to be hired), Investor Representative (SeriesA lead), Independent AI Ethics Advisor.  
  - **Executive Team**: CEO, CTO, VP of Product, VP of Sales, VP of Engineering, Chief Compliance Officer.  
- **Intellectual Property**:  
  - Patents pending on "Dynamic Prompt Generation Engine" and "Secure AuditReady Model Evaluation Log".  
  - All core code released under the Apache2.0 license for community extensions; proprietary analytics layer kept closedsource.  
- **Compliance & Governance**:  
  - SOC2 TypeII, ISO27001 certification roadmap.  
  - Data processing agreements (DPAs) with all enterprise customers.  
- **GotoMarket Strategy**:  
  - **Phase1 (Months012)** - Target earlyadopter AI labs via pilot programs; publish benchmark results in top AI conferences.  
  - **Phase2 (Months1224)** - Expand to enterprise verticals (finance, health) through channel partners; launch marketplace for thirdparty probe plugins.  
  - **Phase3 (Months2436)** - International expansion to EU & APAC, leveraging data residency zones and multilingual probes.  

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## Signature Block  
Edgar Chen certifies this proposal meets Crimson Leaf Holdings governance requirements:  

- No existing subsidiary duplicates this charter  
- No existing template or tool can solve this gap  
- No proposal for this company has been submitted in the last 30 days  
- A full business plan with 5source web research and inline citations is provided  

*Signature: ______________________*  
Date: 20260502  

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