Solving Data Silos with AI: Role-Specific Chatbot for FinSolve Technologies

AI-Powered Internal Chatbot with Role-Based Access Control | FinTech RAG Project Demo

Welcome to my presentation for the Codebasics Resume Project Challenge!
In this video, I walk through my end-to-end implementation of a RAG-based internal chatbot built for FinSolve Technologies, a leading FinTech company. The chatbot leverages Role-Based Access Control (RBAC) to ensure secure, role-specific data access across departments like Finance, HR, Marketing, Engineering, and C-Level Executives.

🔍 What you’ll learn in this video:
✅ How I used FastAPI for secure authentication
✅ Implementing RAG (Retrieval-Augmented Generation) with vector search
✅ Integrating Large Language Models (LLMs) like GPT
✅ Creating a secure, user-friendly Streamlit interface
✅ Managing role-based permissions and handling natural language queries
✅ Structuring modular, production-ready Python code

📁 Tech Stack:

React+Typescript

Python

FastAPI

GPT-4 or LLaMA

Qdrant

Streamlit

Basic Auth with RBAC

🎯 Use Case:
This chatbot is designed to solve internal communication delays, streamline access to sensitive documents, and enhance productivity through AI-powered, context-aware responses—customized per user role.

👉 Like, Share, and Subscribe if you're interested in AI, LLMs, FastAPI, and full-stack projects!
🔗 [GitHub Repo Backend] – (https://github.com/prateeksharma1809/ds-rpc-01)
🔗 [GitHub Repo Frontend] – (https://github.com/prateeksharma1809/ds-rpc-01-frontend)
🔗 [Project Post on LinkedIn] – (Add your LinkedIn post link here)

#AIChatbot #FastAPI #RAG #RoleBasedAccess #FinTech #PythonProjects #ResumeProjectChallenge #LLM #GenAI #Streamlit #GPT4 #CodebasicsChallenge #RBAC #VectorSearch #FullStackAI #React #Typescript #Python

Видео Solving Data Silos with AI: Role-Specific Chatbot for FinSolve Technologies канала Prateek Sharma