Your documents have answers — but nobody can find them. I build production-grade Retrieval-Augmented Generation (RAG) systems that let your team or customers ask questions in plain English and get accurate answers grounded in your real documents.

I use the same stack I ship at Techloset Solutions for enterprise clients: LangChain + MongoDB Vector Search for retrieval, FastAPI for the backend, and Next.js for a clean chat interface.

Document ingestion pipeline (PDF, DOCX, websites, Notion, Google Drive)

Vector database setup on MongoDB Atlas (or alternative of your choice)

LangChain retrieval pipeline with re-ranking for accuracy

LLM integration — OpenAI GPT-4, Google Gemini, or Claude (your choice)

Responsive chat UI built in Next.js with real-time streaming

Docker containerization and deployment

Setup documentation so your team can maintain it

Best for: SaaS companies, customer support teams, legal/medical/HR teams, internal knowledge bases, FAQ bots.