Struggling with AI systems that hallucinate, lose context, or fail at multi-step tasks? I build robust, production-ready multi-agent systems and Agentic RAG pipelines using LangGraph and FastAPI.
What You Get:
- Custom LangGraph multi-agent architectures with state management and persistent memory.
- High-accuracy RAG workflows featuring semantic chunking, hybrid search, and context re-ranking.
- Tool calling, structured JSON/Pydantic outputs, and strict guardrails to eliminate errors.
- Production-ready async FastAPI backend integration with vector and relational databases.
Why Choose Me:
- Proven record of reducing LLM inference costs and hallucination rates by 70%.
- Experience scaling automated data pipelines to 10,000+ records per month.
- Clean, documented, and production-tested Python code.
Tech Stack: Python, LangGraph, LangChain, FastAPI, OpenAI API, Qdrant, PostgreSQL, Supabase, Langfuse.