Play 53
Legal Document AI
Very High✅ Ready
Contract review, clause extraction, and risk identification with audit trails.
Legal document analysis agent for contract review, clause extraction, risk identification, and compliance checking. Uses RAG architecture with Azure AI Search over legal document corpus with privilege detection and redline comparison. Maintains full audit trails in Cosmos DB for regulatory compliance. Employs deterministic validation for high-stakes legal conclusions.
Architecture Pattern
RAG + deterministic validation: high-stakes legal analysis with audit logging
Azure Services
Azure OpenAI (gpt-4o)Azure AI SearchBlob StorageCosmos DBKey Vault
DevKit (.github Agentic OS)
- agent.md — root orchestrator with builder→reviewer→tuner handoffs
- 3 agents — Legal AI Builder (gpt-4o), Reviewer (gpt-4o-mini), Tuner (gpt-4o-mini)
- 3 skills — deploy (223 lines), evaluate (124 lines), tune (188 lines)
- 4 prompts — /deploy, /test, /review, /evaluate with agent routing
- .vscode/mcp.json — FrootAI MCP with OpenAI + Doc Intelligence inputs + envFile
TuneKit (AI Config)
- config/openai.json — low temperature for precise legal analysis
- config/guardrails.json — high groundedness, privilege detection
- evaluation/eval.py — Clause accuracy >90%, Risk recall >85%
Tuning Parameters
Clause extraction confidenceRisk threshold scorePrivilege detection sensitivityRedline match precisionAudit retention period
Estimated Cost
Dev/Test
$70–110/mo
Production
$2K–6K/mo