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RAG & LLM Applications
Custom chatbots and document Q&A systems using Retrieval-Augmented Generation with ChromaDB, Pinecone, and vector databases.
Overview
I build Retrieval-Augmented Generation (RAG) pipelines that give LLMs access to your private documents, databases, and knowledge bases — without hallucination. The result is a chatbot or Q&A system that answers from your actual data, cites sources, and stays current. I handle everything from chunking strategy and embedding models to retrieval tuning and production deployment.
Tech Stack
LangChainChromaDBPineconeGoogle GeminiOpenAIStreamlitFastAPI
Use Cases
- ✓PDF and document Q&A systems
- ✓Internal knowledge-base chatbots
- ✓Customer-facing support bots grounded in product docs
- ✓Legal and compliance document search
- ✓Multilingual enterprise search
Ready to build with RAG & LLM Applications?
Tell me about your project and I'll get back to you within 24 hours.