Email Triage Agentic Application
Problem
LLM-powered email assistant that monitors inbox, classifies emails as spam or legitimate, auto-replies to legitimate emails, and notifies the owner.
Outcome
Conceptualize, design, implement and test the application
- Designed and built a multi-agent LLM pipeline to classify inbound email, auto-drafts contextual replies, and notifies the owner, with per-email tracing of latency, token count, and classification confidence
- Engineered for cost and reliability: cut cost by routing classification to locally-hosted model; added cost/rate circuit breaker, crash-safe idempotency, and auto-reply-loop prevention; unit and E2E testing included
Technologies
Flask LangGraph Langfuse Ollama