Built by aegntic.ai. Veritas Operator runs a multi-agent, adversarially-reviewed research pipeline that synthesizes sources into a decision-grade, citation-backed brief. Designed for analysts, journalists, and operators who need ground truth fast.
Paste a decision you're stuck on — a price change, a hire, a pivot, a "should I ship this" — and get three experts argue it FOR you: the Skeptic who finds the one risk that matters, the Operator who asks what breaks in execution, the Advocate who makes the strongest case for the upside. A synthesis then names the single question that resolves it. Reasons from your input + domain knowledge only — no invented numbers, no browsing. For founders and PMs tired of arguing with themselves alone.
Can't choose between options? Three independent AI lenses build the strongest cited case for each one, cross-examine the evidence, and name a winner.
Hands-on prompt engineering and LLM evaluation. Built around a diagnose-then-ship loop: forensic transcript critique ▎ that names the exact failure mode, paired with a fixer that produces complete, deployment-ready rewrites — not ▎ vague advice.
Who wins? What's the score? Professional football data and statistical modeling, powered by deep AI reasoning — delivering objective, probability-based analysis of match outcomes and scorelines, updated in real time.
Know if a betting record is luck or skill. Paste any betting history — get a full statistical audit: ROI with 95% confidence interval, the probability a losing bettor would show the same record, drawdown analysis, risk of ruin, and curation red flags. Retrospective analysis only — never predictions.
Turn any chargeback into a submission-ready rebuttal letter in minutes — no percentage fees, no contract.
Turn a vague success claim into one sourced metric, then blur a client name lacking permission.
Check AI-generated claims against your approved Fact Sheet and flag changed quantities, expanded scope, dropped attribution, and unsupported mappings — deterministic, local, and no AI guessing.