I will build document chatbot knowledge base ai rag development vector database


About this gig
Does your team spend too much time searching through PDFs, manuals, policies, or internal documents to find simple answers?
I can build a document chatbot that uses vector search and retrieval-augmented generation (RAG) to find relevant information from your approved documents and use it to answer questions. Instead of manually searching through files, your team can ask questions in plain language and retrieve relevant passages more easily.
What I can build for you:
- AI chatbots for PDFs and other supported documents
- Document processing and text extraction
- Vector database setup and semantic search
- RAG pipelines for document-based answers
- Custom question-and-answer behavior
- Source references or citations where supported
- API integration and a simple chat interface
- Testing with sample questions and documents
Whether you need an internal knowledge assistant or a document chatbot for your users, I can help define and build a solution around your actual information.
Send me a sample of your documents and explain what users need to find. We can start with a clear, manageable scope.
Get to know Roberto Chavez
Problem solving AI Automation Specialist
- FromMexico
- Member sinceMar 2026
- Avg. response time8 hours
Languages
Spanish, English
FAQ
What is a document chatbot?
It is an AI assistant that lets users ask questions about a defined collection of documents instead of searching through every file manually.
What is vector search?
Vector search compares numerical representations of text to find content with similar meaning, even when the exact words differ.
What is RAG?
Retrieval-augmented generation combines retrieving relevant information from a knowledge source with an AI model that uses that information to formulate an answer.
Can you build a chatbot for PDFs?
Yes, for supported PDFs. Scanned or image-based PDFs may require OCR, which should be confirmed before the project starts.
Can it show the source of an answer?
Source references can be implemented when the retrieval pipeline preserves document and passage information. The exact format depends on the agreed solution.
Will the chatbot be 100% accurate?
No AI retrieval system can be guaranteed to answer every question correctly. I can test the system against agreed examples and configure it to handle missing information more carefully.
