AI Coach — Conversational Health Agent Platform

Rebuilt a production conversational health-coaching agent's orchestration layer, then built its core nutrition capabilities on top.

Rebuilt the AI Coach's agent orchestration layer — replacing an initial LangGraph state machine and dual-layer Mem0 memory setup with the Vercel AI SDK's bounded tool-calling loop and a single HindSight episodic-memory layer. Built a 2-channel (WhatsApp, Telegram) conversational agent on a 13-step-max tool-calling loop with a YAML-defined skill registry, driven by 16+ Kafka-consumed event domains for real-time patient state. On that foundation, built a single-call 3-tier meal-logging resolution engine (personal history → pgVector search → LLM fallback), an LLM-driven diet-plan generator combining ClickHouse history with agent memory, and a 4-state glucose feedback engine closing the log → feedback → plan loop.