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Investment Analytics

AI-Powered Stock Screening Platform

ClientSeries B Fintech Startup
IndustryInvestment Management
Duration4 months
Team3 engineers
80%
Faster Research
Reduced per-stock analysis time from 3 days to 4 hours
10x
Coverage Increase
Expanded from 50 to 500+ stocks under active coverage
5,000+
Stocks Analyzed
Full market coverage with daily screening updates

The Challenge

A growing investment advisory firm was manually analyzing stocks, taking 3 days per company. Their research team of 5 analysts could only cover 50 stocks effectively, limiting their ability to identify opportunities across the broader market. They needed to scale research coverage from 50 to 500+ stocks without hiring 10x more analysts, while maintaining the quality and depth of their fundamental analysis.

Our Solution

Built an intelligent stock screening platform that automatically pulls data from 12 sources including financial statements, analyst reports, and alternative data. The system calculates 45+ financial ratios, applies ML-based scoring models trained on historical outperformers, and generates analyst-ready reports with key insights highlighted.

Our Approach

1

Conducted deep-dive sessions with research analysts to understand their workflow and decision criteria

2

Designed data pipeline architecture to ingest and normalize data from multiple sources in real-time

3

Built ML models using historical data to identify patterns associated with outperforming stocks

4

Created intuitive dashboards with drill-down capabilities for detailed analysis

5

Implemented automated alerting system for stocks meeting specific criteria

Technology Stack

PythonTensorFlowPostgreSQLReactAWSAirflowRedis

Ready to Achieve Similar Results?

Let's discuss how we can help transform your operations.