I build production-oriented Retrieval-Augmented Generation

I build production-oriented Retrieval-Augmented Generation (RAG) systems that connect LLMs with your private documents and knowledge bases.

What I can build: • Document ingestion and intelligent chunking • Embeddings and semantic/vector search • ChromaDB / Pinecone / pgvector integration • LLM-powered question answering • Retrieval optimization and relevance improvement • Source-grounded responses to reduce hallucinations • FastAPI backend and API integration • Dockerized, maintainable architecture

Example: Built a Document Q&A system using Gemini + ChromaDB that retrieves relevant document context and generates grounded answers.

Ideal for companies looking to turn internal documents, knowledge bases, PDFs, or technical content into an AI-powered search and Q&A system.