FinsightAI is a secure, role-based AI assistant built for FinSolve Technologies to empower different departments with instant, accurate, and context-rich insights using RAG (Retrieval-Augmented Generation).

Domain: FinTech
Function: AI Engineering

FinSolve Technologies is a leading FinTech company offering innovative financial services to individuals and enterprises. However, communication delays and siloed data across departments (Finance, Marketing, HR, Engineering, and C-Level) have caused major bottlenecks in decision-making and project execution.

To tackle this, a digital transformation initiative was launched to build FinsightAI — a secure, role-aware AI chatbot using RAG (Retrieval-Augmented Generation) and Role-Based Access Control (RBAC). The assistant helps teams access accurate, department-specific insights instantly and securely.

Traditional workflows in FinSolve suffer from:

• Communication delays
• Data silos across departments
• Inefficiencies in decision-making

These gaps reduce productivity and impact strategic outcomes.

FinsightAI was built to:

• Authenticate users and assign roles (e.g., HR, Finance, Engineering)
• Use RAG to retrieve and contextualize internal data
• Respond to queries using CSV files + vector store (ChromaDB)
• Enforce role-based access to data

• Python 3.11
• FastAPI (Backend)
• OpenAI GPT-4o-mini (LLM)
• ChromaDB (Vector Store for documents)
• LangChain + Pandas (CSV agents)
• Streamlit (Chatbot UI)

1. Clone the repo: git clone https://github.com/yourusername/ds-rpc-01.git

2. Set up virtual environment and install dependencies: pip install -r requirements.txt

3. Start the backend: uvicorn main:app --reload

4. Start the Streamlit frontend: streamlit run app.py

5. Visit: http://localhost:8501