FinSight AI
An AI-powered financial intelligence platform — parallel agents deliver probabilistic revenue forecasts, buy/sell signals, and peer benchmarks in under 20 seconds.
Overview
FinSight AI is an agentic, multi-model financial intelligence platform that automates analysis which traditionally takes analysts hours. Enter a ticker and a date — get a probabilistic revenue forecast, a buy/sell signal, peer benchmarks, and a full audit trail in under 20 seconds. It combines quantitative finance, multi-agent LLM reasoning, and real-time market data into one fast pipeline.
The Problem
Traditional financial analysis means reading earnings transcripts by hand, building Excel models, monitoring news, and running competitive comparisons — repetitive work that's slow and hard to keep consistent. FinSight AI integrates all of it into a single automated pipeline with explainable outputs.
What I Built
- Parallel AI agents running concurrently via Python
asynciofor sub-20-second results - Probabilistic forecasts — Bear / Base / Bull scenarios via quantile regression, not a single point estimate
- SHAP explainability so every forecast can be traced to its drivers
- News + NLP + competitor analysis for macro and peer context
- PDF reports with a full audit trail of how each signal was produced
Architecture
Specialized agents run concurrently and a final ensembler fuses their outputs into one calibrated signal:
- Transcript NLP agent — extracts and summarizes key financial drivers from earnings calls
- Financial model agent — quantitative forecasting with quantile regression (Bear/Base/Bull)
- News macro agent — aggregates, classifies, and scores macro news sentiment
- Competitor agent — benchmarks the target against industry peers
- Ensembler (CIO agent) — fuses all outputs into one calibrated investment signal with reasoning
Tech Stack
Frontend: React, Vite, Tailwind CSS
Backend: FastAPI, Python, asyncio
ML: Scikit-learn, quantile regression, SHAP
LLM: Groq (LLaMA 3)
Database: MongoDB Atlas
Use Case
Retail and analyst users who want a fast, explainable second opinion on a stock — forecast, signal, peer context, and the reasoning behind it — without spending hours building models by hand.
Status
Production (v2.0) with CI; actively maintained.