Play 70
ESG Compliance Agent
Environmental, Social, Governance reporting automation with regulatory compliance.
Automated ESG reporting across four regulatory frameworks — GRI, SASB, TCFD, and EU CSRD. Azure Document Intelligence extracts data from corporate filings and sustainability reports, OpenAI maps extracted data to framework-specific disclosure requirements, AI Search provides regulatory knowledge retrieval, and Cosmos DB maintains compliance state. Generates board-ready ESG dashboards.
Architecture Pattern
RAG-powered compliance: document extraction → framework mapping → gap analysis → reporting
Azure Services
DevKit (.github Agentic OS)
- agent.md — root orchestrator with builder→reviewer→tuner handoffs
- 3 agents — ESG Builder (gpt-4o), Reviewer (gpt-4o-mini), Tuner (gpt-4o-mini)
- 3 skills — deploy (260 lines), evaluate (113 lines), tune (221 lines)
- 4 prompts — /deploy, /test, /review, /evaluate with agent routing
- .vscode/mcp.json — FrootAI MCP with OpenAI + AI Search inputs + envFile
TuneKit (AI Config)
- config/openai.json — regulatory document analysis prompts
- config/esg.json — framework rules, disclosure requirements, materiality matrix
- config/guardrails.json — audit trail, data lineage
- evaluation/eval.py — Framework coverage >90%, Data accuracy >95%
Tuning Parameters
Machine evidence
FrootAI evidence lifecycle
This is an internal evidence maturity label, not third-party certification, accreditation, legal compliance, or a production guarantee. Missing or expired evidence demotes automatically; catalog claims cannot promote a play.
This play currently has design evidence only. A runnable scenario, endpoint evaluation, and build receipts are the next contiguous gates.
Repo Intelligence
v1A no-clone, revision-pinned map for agents and humans. Observed evidence is separated from inferred flow so the output stays useful without pretending to be a full call graph.