I'll build a custom RAG chatbot that answers questions from your documents

About this Gig

I build custom RAG (Retrieval-Augmented Generation) chatbots — AI systems that answer questions using your actual documents, policies, product manuals, or knowledge base, instead of generic AI guesses. Every answer is grounded in your real content, with source passages cited, so there's no hallucination. What's included: Document ingestion and intelligent chunking (PDFs, and other formats on request) Semantic search setup using vector embeddings LLM-powered answer generation, tuned to stay grounded in your content A working, deployable chatbot you can plug into your website or internal tools Recent proof of work: I built and deployed Lumen, a full RAG application, entirely on my own — including solving real production challenges like memory optimization and provider migration. [Link to live demo / GitHub] I'm early in my freelance journey, so I'm focused on delivering excellent work and clear communication on every project — not coasting on a reputation I haven't built yet. Happy to start with a smaller-scoped task if you want to see quality before committing to a larger build.

Requirements

To get started, I'll need: The document(s) or content you want the chatbot to answer questions from (PDFs, text files, or similar) A few example questions your users are likely to ask, so I can tune retrieval accuracy Where you'd like the chatbot deployed or embedded (your website, an internal tool, Slack, etc.) Any specific tone or response style you want the AI to follow

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