Autonomous AI agent generating professional market research reports in 10 minutes
Traditional market research is labor-intensive, requiring analysts to manually gather data, extract financials, analyze GitHub metrics, and compile comprehensive reports. This process is slow, expensive, and doesn't scale.
An intelligent multi-agent system that autonomously researches companies, extracts structured financials from news using AI, analyzes GitHub metrics, identifies 4 "Hidden Signals", and generates investment-grade PDF reports.
Multi-Agent orchestration with 4 independent agents coordinating through clear interfaces (Data Gathering → Analysis → Synthesis → Report Generation). Each agent has single responsibility with comprehensive error handling.
Phase 1: Foundation - API integration (Alpha Vantage, Finnhub, SEC, Serper, GitHub) with authentication
Phase 2: AI Agents - Gemini + FinBERT integration with agent communication framework
Phase 3: Advanced Capabilities - Private company financial extraction using structured prompts, GitHub ecosystem metrics
Phase 4: Report Generation - Professional PDF generation with ReportLab, proper formatting
Phase 5: Deployment - Streamlit UI, HuggingFace deployment, intelligent caching for cost optimization
Transferable skills and capabilities beyond the technical implementation
Coordinated 4 independent AI agents with complex dependencies. Built robust communication framework with clear interfaces and comprehensive error handling at each boundary.
LLM API costs could exceed $500/month. Built intelligent caching reducing API calls by 70%, selected free-tier APIs strategically. Achieved $0/month operating cost at production quality.
Private companies don't report financials publicly. Built AI extraction with exact output format specifications: "FUNDING: [amount with source] or Not disclosed". Achieved 70-85% accuracy.
Nobody else extracts private company financials this way with free APIs. Source attribution and confidence levels build trust. Depth over breadth creates unique value.