I will build a rag powered ai chatbot trained on your data using llm

Most "AI chatbots" on the market are a thin wrapper around ChatGPT that hallucinate answers and have no idea what's actually in your documents. That's not what I build.

I'm an ML engineer who builds production-grade RAG (Retrieval-Augmented Generation) systems chatbots and assistants that actually ground their answers in your data: PDFs, docs, websites, knowledge bases, support tickets, product catalogs, whatever you've got.

What makes my RAG builds different:

• Proper chunking strategy tuned to your content type (not a generic 500-token default that breaks context)
• Retrieval tuned for actual relevance not just cosine similarity on raw embeddings
• Grounded answers with source citation, so responses are traceable, not hallucinated
• Clean separation between what the LLM narrates and what the system verifies built for consistency, not just a good demo

What you get:

• A working chatbot/API that answers questions using your own data
• Clear documentation on how it works and how to update the knowledge base
• Optional: simple web interface or API endpoint for integration into your site/app