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I will build ai chatbot with rag using openai langchain and vector database
Sanjay Kumar
About this gig
Looking for an AI chatbot that answers questions using your own business data instead of generic AI responses?
I will build a custom RAG (Retrieval-Augmented Generation) chatbot powered by OpenAI, Claude, Gemini, or Llama using LangChain, LangGraph, MCP, FastAPI, and vector databases like Pinecone, ChromaDB, or FAISS.
Your chatbot can understand PDFs, Word files, websites, FAQs, Notion, databases, and internal documents to provide fast, accurate, and context-aware responses. It's perfect for customer support, internal knowledge bases, SaaS products, employee assistants, and business automation.
What you'll get:
- Custom AI Chatbot with RAG
- Website & API Integration
- Secure Authentication
- Conversation Memory
- Source Citations
- Production-Ready Architecture
- Clean & Scalable Code
- Deployment Support
- Full Source Code Ownership
Every solution is tailored to your business requirements and built with scalability, performance, and long-term maintenance in mind.
Whether you need a website chatbot, document AI assistant, company knowledge bot, or enterprise RAG solution, I'm here to help.
Please contact me before placing an order so we can discuss your requirements and choose the best solution.
Get to know Sanjay Kumar
Sanjay Kumar
AI Automation Specialist
- FromIndia
- Member sinceJun 2023
- Last delivery10 months
Languages
Hindi, English
Hi, I’m Sanjay Vishwakarma — an AI automation developer specializing in voice AI agents, workflow automation, and intelligent business systems.
I help businesses automate sales calls, lead qualification, cold outreach, and backend workflows using AI tools like n8n, APIs, STT/TTS models, and custom integrations.
With strong experience in full-stack development and AI systems, I focus on building practical, scalable solutions that deliver real business results — not just demos.
If you're looking for someone who understands both technology and business logic, you're in the right place.
My Portfolio
FAQ
What is a RAG AI chatbot?
A RAG (Retrieval-Augmented Generation) chatbot uses your own documents, website, database, or knowledge base to answer questions accurately instead of relying only on general AI knowledge. This results in more reliable, context-aware responses for your business.
Which AI models do you support?
I can build chatbots using OpenAI (GPT), Claude, Gemini, Llama, and other compatible LLMs. I'll recommend the best model based on your requirements, budget, and expected performance.
What data sources can the chatbot use?
Your chatbot can work with: • PDFs • Word Documents • Websites • FAQs • Notion • Google Drive • Databases • APIs • CSV & Excel Files • Internal Knowledge Bases
Can you integrate the chatbot with my website or existing system?
Yes. I can integrate your chatbot with websites, FastAPI applications, CRM systems, WhatsApp, Slack, APIs, databases, and other business platforms depending on your requirements.
Do you provide deployment and source code?
Yes. Unless discussed otherwise, you'll receive the complete source code. I can also deploy the chatbot on cloud platforms, VPS servers, Docker, or your preferred hosting environment.
What information do you need before starting?
Please share your project requirements, preferred AI model (if any), data sources, website or API details, and any reference materials. If you're unsure, I'll help you choose the best approach.
Can you build custom AI assistants for my business?
Absolutely. I develop AI assistants for customer support, employee knowledge bases, sales, document search, business automation, SaaS platforms, and many other custom use cases.
Should I contact you before placing an order?
Yes. Every AI chatbot project is unique. Please send me a message before ordering so we can discuss your requirements and select the most suitable package for your project.
