Turn your documents, PDFs, internal knowledge, or product data into an intelligent AI assistant your team or customers can actually use.

I build production-ready Retrieval-Augmented Generation (RAG) systems that go beyond simple chatbot demos — with robust retrieval pipelines, vector search, proper chunking strategies, prompt orchestration, and scalable deployment.

Perfect for: • Internal knowledge assistants • PDF / document chatbots • Customer support AI • Product documentation assistants • Semantic enterprise search • AI copilots for SaaS platforms

What I can deliver: ✅ End-to-end RAG architecture ✅ PDF, docs, websites, APIs, databases ingestion ✅ Vector DB setup (pgvector, Pinecone, Qdrant, Chroma, FAISS) ✅ LangChain / LlamaIndex implementation ✅ OpenAI / Claude / Gemini integrations ✅ Authentication & role-based access ✅ Frontend chatbot UI (if needed) ✅ FastAPI / backend APIs ✅ AWS deployment & production hardening

Tech Stack: Python, FastAPI, LangChain, LangGraph, LlamaIndex, OpenAI, Anthropic Claude, Pinecone, pgvector, Qdrant, AWS, Docker

If you need a reliable AI assistant over your business knowledge, I can design, build, and deploy the full solution.