An AI-driven multi-agent automation workflow comprising 4 specialised concurrent AI personas for automated clinical decision support. Built via LangGraph with state machine precision.

• 4 concurrent AI personas — each a specialised clinical domain expert
• Self-correcting reflection loop prevents infinite API loops
• Strict state schemas enforce secure inter-agent data transfer
• Deterministic execution guaranteed across all agent paths

Distributed Multi-Format AI Orchestration. A ClassifierAgent dynamically routes inputs (email, JSON, PDF) to 3 specialised processing agents based on detected format and intent.

• ClassifierAgent routes inputs across 3 format-specific processor agents
• ActionRouter triggers CRM escalation, fraud alerts, compliance flags
• Persistent MemoryStore logs every decision end-to-end via SQLite
• Full session auditability with background task execution

A high-accuracy RAG pipeline querying 10,000+ vectorised chunks of dense clinical text using a local ChromaDB vector database with engineered citation tracking.

• 10,000+ vectorised clinical text chunks in local ChromaDB
• Citation-tracking prompts reduce hallucinations by over 80%
• 95%+ factual reliability on medical Q&A benchmarks
• Fully local inference — no cloud API dependency