Diligence — Adversarial AI Equity Research

Most AI research tools converge on a single confident answer. That's the failure. A 10-K is 300 pages. An earnings call is an hour of hedged language. Sell-side analysts looking at identical numbers reach 40% different price targets. The signal isn't in the consensus — it's in what bull and bear actually disagree about, and whether either side can point to a primary source when challenged. Diligence surfaces that line in six minutes. How it works. Submit a ticker. The system pulls the latest 10-K and 10-Q from SEC EDGAR, quarterly fundamentals, and the most recent earnings call. A tier-scored selector picks the issuer's own audio over aggregator reposts; Speechmatics diarizes it down to the speaker and second. Then the agents argue: — A Filing Analyst (Gemini 2.5 Pro on Vertex AI) extracts atomic claims from the SEC text with section-and-character citations. — A Call Analyst (Gemini 2.5 Pro) does the same for the diarized transcript, tagged by speaker and timestamp. — Bull and Bear agents (Qwen3-32B via Featherless) build the strongest case on each side. They can only cite claim IDs the analysts produced. Anything else is rejected at parse time. — A Reconciler (Gemini 2.5 Pro) diffs both cases, ranks every disputed fact by materiality, flags uncited assertions, and surfaces what both sides quietly concede. What ships. Adversarial by construction. One LLM smooths. Five debate. The disagreement is the signal. Citations all the way down. Every chip on the dashboard points back to a specific SEC section or a second in the audio. Click to verify. Live, auditable, replayable. Ranked disputes, diarized transcript, agent reasoning — all one click away. LangGraph orchestration. Pydantic-enforced outputs. Hosted on Vultr. About $1.25 per ticker, end to end. Read the dispute. That's where the alpha lives.

Note: the demo URL is substituted with the GitHub repository link.