Anuj Patel@byanujpatel

AlphaAudit is an institutional-grade pre-earnings predictive intelligence engine engineered for Track 2 (Finance & Market Intelligence). It bridges the gap between what corporations claim in official disclosures and the reality occurring on the live web. Built on a stateful, self-healing cyclic LangGraph workflow, the system uses two Gemini reasoning nodes to: (1) scrape recent SEC filings/earnings call transcripts to extract literal guidance claims regarding talent growth, pricing power, and supply chain bottlenecks, and (2) audit those claims concurrently using remote Bright Data SSE MCP search and scrape tools. If alternative data (LinkedIn professional headcount growth, retail product discounts, cargo backlogs) reveals a discrepancy greater than 15%, the agent launches the remote Scraping Browser to capture visual evidence (e.g. active promo banners, job board freezes) and saves it locally. It calculates a numerical "Decoupling Coefficient" (0% = Honest, 100% = Extreme Corporate Spin) and compiles a structured "Warren Buffett-Lens" Pre-Earnings Arbitrage Signal. Outcomes are streamed live via Server-Sent Events (SSE) to a premium React glassmorphic dashboard featuring circular glowing dials, split-screen claims-vs-reality panels, and an interactive screenshot evidence deck.

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