Brief Overview:

In this use case, I demonstrated the integration of Google’s NotebookLM and Vertex AI to build a retrieval-augmented chatbot powered by a 2 TB+ domain-specific knowledgebase on Taxation and Law. The solution enables contextual, real-time Q&A, stock research, and financial advisory using GenAI, RAG, and autonomous AI Agents.

Problem Statement:

Traditional financial research and compliance advisory are fragmented, time-consuming, and often not tailored in real-time. Professionals lack tools that can process structured and unstructured documents and respond intelligently.

Solution Components:

1. Google’s NotebookLM:
2. Uploaded TCS Annual Report, Technical Analysis, Q4 Results, and news articles. MindMap, FAQ generation, and query resolution via embedded LM.
3. AI Agent Features:
4. Uploaded 2TB+ financial, tax, and law blogs to create a smart agent.
5. Agent could take autonomous actions like summarizing annual reports, answering FAQs, and providing buy/sell recommendations.
6. Google Cloud Vertex AI – GenAI RAG Model:
7. Used RAG (Retrieval-Augmented Generation) to create a custom LLM over uploaded content.
8. Powered a chatbot on my platform for real-time client engagement.

Demo Highlights:

1. Search for Budget 2025 in chatbot: Returns expert-verified data from Tax blogs.
2. "Should I buy TCS today?": AI processes Annual Report, Q4 earnings, and news sources for a decision.
3. MindMap from NotebookLM: Visually clickable data nodes linked to sources.
4. Realtime Podcast of 20 mins by 2 AI Agents of all the Knowledge Sources

Tech Stack:

1. Google Cloud Vertex AI
2. Gen AI RAG
3. NotebookLM
4. Custom Tax & Law Knowledgebase
5. Chatbot Framework
6. AI Agents (Autonomous Workflow + Task Execution)

Impact & Future Scope:

1. Virtual Tax Assistant & Financial Research Bot
2. Autonomous Agent-based compliance guidance
3. Integration with MSMEs, NRIs, and MFDs
4. Scaling APIs to govt bodies for rural/farmer-focused advisory

Screenshots / Demos: