I will build an ai document chatbot using rag and vector databases


About this gig
Unlock the power of AI with a custom Retrieval-Augmented Generation (RAG) system tailored to your business. I build intelligent AI assistants that can answer questions using your own documents, PDFs, websites, databases, APIs, or knowledge baseproviding accurate, context-aware responses instead of generic AI outputs.
Whether you need an internal knowledge assistant, customer support chatbot, document search system, or AI agent workflow, I deliver scalable, production-ready solutions.
What I Offer:
- AI Chatbots & AI Agents
- RAG Pipelines
- PDF & Document Chat
- Website & Knowledge Base Chatbots
- Vector Search (Qdrant, Pinecone, ChromaDB, FAISS)
- LangChain & LangGraph Workflows
- OpenAI, Gemini, Claude & Llama Integration
- FastAPI REST APIs
- Docker & Cloud Deployment
- Authentication & Multi-user Support
- Source Citations & Semantic Search
Why Choose Me?
- Clean, scalable architecture
- Modern AI frameworks and best practices
- Fast communication and reliable delivery
- Well-documented, production-ready code
Please contact me before placing an order so we can discuss your requirements and choose the best solution for your project.
Get to know Vijay Singh
Expert Full Stack Web Developer MERN Stack, NextJS, SQL, Tailwind, SEO
- FromIndia
- Member sinceMar 2023
- Avg. response time1 hour
- Last delivery1 year
Languages
Hindi, Urdu, English
My Portfolio
FAQ
What data sources can your AI chatbot use?
My AI solutions can work with PDFs, Word documents, websites, databases, APIs, Notion, CSV/Excel files, and other custom knowledge sources.
Which AI models and technologies do you support?
I work with OpenAI (GPT), Google Gemini, Claude, Llama, LangChain, LangGraph, Qdrant, Pinecone, ChromaDB, FastAPI, and Docker.
Do you deploy the project and provide the source code?
Yes. I can deploy your project to cloud platforms or your own server, and the complete source code is included unless otherwise agreed

