A-JEPA AUTOMATA

High Level Overview Automata is a production-grade AI agent platform that combines live web intelligence with formal verification — making it the first system where AI-driven business decisions are mathematically auditable before execution. The core problem: enterprise teams can't trust AI agents acting on web data because there's no proof the reasoning is sound. Automata solves this with a three-layer stack. Layer 1 — Web Intelligence Intake (Bright Data): The Bright Data MCP Server and Web Scraper API feed structured live data — competitor pricing, regulatory filings, LinkedIn hiring signals, SERP trends — directly into the ingestion pipeline. Web Unlocker handles bot-protected sources. All intakes logged to a Blake2b-hashed append-only audit trail from the first byte. Layer 2 — Agentic Orchestration: A FastAPI backend with async workers processes ingested signals. The Go CLI harness runs named analysis flows — sorry scan, interconnect map, signal diff — and exposes structured JSON for downstream AI agents. A proof watcher tracks theorem and proof-completion metrics per file in real time, ensuring that the logic layer never silently regresses. Layer 3 — Formal Verification : Every intelligence claim that triggers an action passes through an Automata state machine. The proof_completion metric — theorems minus sorry-count divided by theorem-count — gates whether a decision is certified or flagged for human review. No sorry-equivalent proof, no downstream action. This is provable trust, not probabilistic trust. Infrastructure: Docker Compose stack with Postgres, Redis, Alembic migrations, Grafana/Loki observability, nginx reverse proxy, and an inotify-based file watcher. Deployable on ROCm hardware. Track coverage: GTM Intelligence (competitor and buying-signal monitoring), Finance & Market Intelligence (pricing and filing pipelines), Security & Compliance (regulatory change detection with proof-gated alerts). A single coherent system spanning all three tracks.