Investment Research for 1.6 Million Investors: AI at Scale for a Leading Indian Broking Firm
An AI-powered financial intelligence platform combining conversational research, RAG-based document intelligence, and automated technical analysis.
What made this hard.
- Financial research requiring extensive manual analyst effort.
- Investors navigating complex reports and technical indicators.
- Data fragmented across NSE, BSE, and financial databases.
- Complex analysis requiring specialist expertise.
- Need to serve both retail and institutional investors.
How we engineered the solution.
AI-native platform consolidating market data and research in one place.
RAG framework producing source-backed answers from annual reports and disclosures.
Live NSE and BSE feeds with automated technical and fundamental analysis.
Interactive visualizations combining NLP, SQL, and charting.
The biggest shift wasn't automating research. It was making every AI answer explainable. RAG was chosen precisely because it delivers source-backed responses with traceability built in.
What this engagement proved.
AI in finance simplifies complexity rather than replacing expertise.
RAG excels where explainability and traceability are critical.
Structured market data + unstructured documents improve analysis depth.
Democratizing research improves engagement while reducing analyst dependency.
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