I will rag ai chatbot knowledge base vector database

Have documents, FAQs, or internal knowledge that your team or customers keep asking about? I build AI chatbots that answer directly from your own content not generic responses, but answers grounded in your actual documents.

I'm a full-stack AI engineer working with Retrieval-Augmented Generation (RAG), vector databases, and embeddings to build chatbots that search your knowledge base in real time and respond using OpenAI or Gemini. Whether it's product documentation, support FAQs, internal SOPs, or a growing set of PDFs, I structure the content so the chatbot retrieves the right information before generating a response reducing made-up answers and keeping replies accurate to your material.

Builds can be embedded on your website, connected to Slack or Microsoft Teams for internal use, or linked to your existing database or CRM. Source code is included from the Standard package up, so you're not locked into me for every future change.

Before starting, I'll ask about your documents, how they're structured, and where the bot needs to live, so the setup matches how your team actually works rather than a one-size-fits-all template.

Not sure if RAG is the right approach for your use case?