This project focuses on delivering a custom AI chatbot powered by large language models and retrieval-augmented generation (RAG). The chatbot is designed to handle customer support, lead qualification, and internal knowledge-base queries with accurate, context-aware responses grounded in your own data. Built using Python, FastAPI, and models like GPT-4, Claude, or open-source LLMs, the solution is tailored to your specific business needs and brand voice.

At the completion of the project, you will receive a fully operational, production-ready chatbot with a custom knowledge base, vector search, and API integration into your website, app, or internal tools. Full documentation, post-deployment support, and maintenance will be provided to ensure the chatbot continues to perform accurately as your business and data evolve.

What's included

Custom AI Chatbot Development: A fully functional AI-powered chatbot built with GPT, Claude, or other LLMs, tailored to your specific business needs, with personalized, on-brand conversation flows.

RAG Pipeline and Knowledge Base Integration: A retrieval-augmented generation pipeline connecting the chatbot to your own documents, FAQs, and databases using vector search, so responses stay accurate and grounded in real business data.

Python and FastAPI Backend: A Python and FastAPI-powered backend for custom logic, API integrations, and advanced conversational features beyond standard chatbot platforms.

Testing and Quality Assurance: Complete testing of chatbot flows and edge cases to ensure accurate, reliable responses before launch.

Detailed User Documentation: A user-friendly guide for your team to manage, update, and retrain the chatbot and its knowledge base going forward.

Deployment and Integration: Full deployment of the chatbot to your live environment, including integration with your website, app, or internal tools.

Post-Deployment Support and Maintenance: Ongoing support for a fixed duration post-launch to troubleshoot issues, retrain the model on new data, and keep the chatbot performing well.

Analytics and Reporting Setup: Conversation analytics and reporting so you can track user interactions, resolution rates, and areas to improve.