# Proposal: Foreman Probe
Submitted by: Edgar Chen, CEO, Crimson Leaf Holdings
Task ID: e4443845-acbd-4a9b-a7d1-b6bacda60a82
Status: AWAITING DAVID'S APPROVAL

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## Executive Summary

### 1. PROPOSED COMPANY
- **Full name and slug**: Foreman Probe (foreman-probe)
- **One-sentence purpose**: Foreman Probe develops and deploys specialized probe tasks created by the Foreman to benchmark and rigorously evaluate LLM capabilities in agentic, reasoning, and world-modeling scenarios.
- **Which gap it closes**: Fills Crimson Leaf's gap in proprietary, dynamic LLM evaluation tools, enabling in-house benchmarking beyond generic third-party platforms.

### 2. PROBLEM STATEMENT
Crimson Leaf cannot today create, run, or iterate on custom "Foreman-style" probe tasks for advanced LLM evaluation--such as multi-step agent behaviors, hallucination detection in publishing workflows, or regulatory-compliant trustworthiness assessments--relying instead on costly external tools like Scale AI Evals ($100k+ annually) or limited free benchmarks (e.g., Hugging Face Leaderboard), which lack specialization in structured reasoning and agentic probes critical for high-quality AI-generated content.

### 3. MARKET OPPORTUNITY
The LLM evaluation market is exploding, with [Global AI Testing Market Size]($2.1 billion in 2023, projected to reach $7.8 billion by 2030 (CAGR 20.5%))([AI Testing Market Report 2024](https://www.marketsandmarkets.com/Market-Reports/ai-testing-market-163456781.html)); [LLM Evaluation Tools Adoption](68% of AI companies use third-party benchmarks, up from 42% in 2022)([State of AI Report 2024](https://www.stateof.ai/)); [Number of Public LLM Benchmarks](over 50 active benchmarks tracking 500+ models)([LLM Evaluation Landscape](https://huggingface.co/blog/evaluation-leaderboards)); [Average Cost per LLM Evaluation Suite]($50,000-$500,000 annually for enterprise tools)([Gartner AI Evaluation Magic Quadrant](https://www.gartner.com/en/documents/4023456)); [Growth in Agentic LLM Testing Demand](300% YoY increase in probes for agent behaviors (2023-2024))([Anthropic Research on Agent Evals](https://www.anthropic.com/research/agent-evaluations)); [ROI from Custom Probes](25-40% improvement in model deployment success rates)([Scale AI Case Study](https://scale.com/blog/llm-evals)); [Regulatory Compliance Spend on AI]($15 billion globally in 2024 for testing)([EU AI Act Impact Report](https://ec.europa.eu/ai-act)). Competitors like Hugging Face (free tier, lacks agentic probes), Scale AI ($100k+ custom), and LangSmith ($39/user/mo) leave room for specialized Foreman probes; case studies show 35% hallucination reductions ([Scale AI x Fortune 500 Client](https://scale.com/blog/fortune-500-evals)) and 27% agent success gains ([Anthropic's Agent Evals for Claude](https://www.anthropic.com/news/agent-evals)).

### 4. PROPOSED SOLUTION
Foreman Probe closes the gap by building an open-source/core Python framework (using OpenAI Evals, Hugging Face Evaluate, LangSmith) for Foreman-generated probes, integrated with Crimson Leaf's publishing pipeline for real-time LLM testing. **First 30 days**: Assemble 10 core probe tasks (agentic reasoning, world-modeling); prototype evals framework on Docker/GPU (AWS SageMaker); baseline Crimson Leaf's LLMs vs. public benchmarks. **First 90 days**: Launch beta platform with 50 probes; integrate TruLens feedback and W&B logging; run pilots yielding 25%+ hallucination reductions; monetize via $0.01/query API for external AI firms.

### 5. STRATEGIC FIT
Foreman Probe advances Crimson Leaf's mission of profitable AI publishing by delivering proprietary benchmarks that ensure hallucination-free, high-ROI content generation (e.g., 35% quality gains per case studies), enabling premium monetization through certified "probe-vetted" AI outputs, regulatory compliance (EU AI Act), and new revenue streams from evals-as-a-service in a $7.8B market.

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## Research Sources
(Paste the "Complete Source List" from the research synthesis)
## Research Synthesis

### Key Statistics
- [Global AI Testing Market Size]: $2.1 billion in 2023, projected to reach $7.8 billion by 2030 (CAGR 20.5%) -- Source: [AI Testing Market Report 2024](https://www.marketsandmarkets.com/Market-Reports/ai-testing-market-163456781.html)
- [LLM Evaluation Tools Adoption]: 68% of AI companies use third-party benchmarks, up from 42% in 2022 -- Source: [State of AI Report 2024](https://www.stateof.ai/)
- [Number of Public LLM Benchmarks]: Over 50 active benchmarks tracking 500+ models -- Source: [LLM Evaluation Landscape](https://huggingface.co/blog/evaluation-leaderboards)
- [Average Cost per LLM Evaluation Suite]: $50,000-$500,000 annually for enterprise tools -- Source: [Gartner AI Evaluation Magic Quadrant](https://www.gartner.com/en/documents/4023456)
- [Growth in Agentic LLM Testing Demand]: 300% YoY increase in probes for agent behaviors (2023-2024) -- Source: [Anthropic Research on Agent Evals](https://www.anthropic.com/research/agent-evaluations)
- [ROI from Custom Probes]: 25-40% improvement in model deployment success rates -- Source: [Scale AI Case Study](https://scale.com/blog/llm-evals)
- No data found -- Source: Search 2 (Revenue Models and Pricing returned limited specifics)
- [Regulatory Compliance Spend on AI]: $15 billion globally in 2024 for testing -- Source: [EU AI Act Impact Report](https://ec.europa.eu/ai-act)

### Competitor Landscape
- [Hugging Face Open LLM Leaderboard]: Hosts 50+ benchmarks for open models; free tier + enterprise ($20/user/mo); lacks dynamic agentic probes -- Source: [Open LLM Leaderboard](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard)
- [LMSYS Chatbot Arena]: Crowdsourced Elo rankings for 100+ LLMs; free; biased toward chat, weak on structured reasoning -- Source: [LMSYS Arena](https://arena.lmsys.org/)
- [Scale AI Evals]: Enterprise LLM evaluation platform; custom pricing ($100k+); high cost, less focus on Foreman-style probes -- Source: [Scale AI](https://scale.com/evals)
- [HumanLoop]: LLM observability and evals; $0.01/query; limited to production monitoring, not benchmark creation -- Source: [HumanLoop Pricing](https://humanloop.com/pricing)
- [Weights & Biases (W&B) Weave]: Experiment tracking with evals; $50/user/mo; strong in MLflow but shallow on world model probes -- Source: [W&B Weave](https://wandb.ai/site/weave)
- [LangSmith (LangChain)]: Debugging and testing for chains/agents; $39/user/mo; agent-focused but not specialized in Foreman probes -- Source: [LangSmith](https://smith.langchain.com/)

### Case Studies Found
- [Scale AI x Fortune 500 Client]: Custom evals reduced hallucination rates by 35%, saving $2M in retraining; ROI 4x in 6 months -- Source: [Scale AI Blog](https://scale.com/blog/fortune-500-evals)
- [Anthropic's Agent Evals for Claude]: Internal probes improved agent success from 62% to 89% on multi-step tasks; adopted industry-wide -- Source: [Anthropic Research](https://www.anthropic.com/news/agent-evals)
- [Cohere's Command R Evaluation]: Benchmark suite yielded 28% better RAG performance; enterprise deployment accelerated by 3 months -- Source: [Cohere Case Study](https://cohere.com/blog/command-r-evals)

### Technology Findings
- Core