Decideria

Decideria runs a multi-agent AI advisory board against a decision, question, or proposal you describe. You set the topic, pick two to six expert roles from prebuilt templates or a custom panel, then watch the agents debate in turn — challenging each other by name, building on prior arguments, and flagging contested assumptions. The session ends with a structured executive report covering insights, risks, and action items, exportable as a PDF. The vendor states the full cycle from question to report runs in under five minutes.

The intervention layer separates Decideria from a one-shot prompt. You can redirect an agent mid-debate, inject new context the panel should factor in, or stop the session early once you have what you need. The live session demo on the vendor page shows a CTO reversing a build-vs-buy recommendation in real time after a resource constraint is injected — the agents update their positions rather than continuing a fixed script. That mid-session steering is what keeps the output calibrated to your actual situation rather than the situation you described at the start.

The tool fits decisions where structured adversarial framing adds value and speed matters more than deep domain precision: startup pitches, spec reviews before a build sprint, pre-meeting preparation for investor or client pushback. It does not fit decisions where the critical variable is proprietary market data, live financials, or technical depth that requires actual practitioner judgment. In those cases the agents produce plausible-sounding challenges that miss the specific failure modes a domain expert would surface immediately — at which point teams running high-stakes diligence move to a workflow that incorporates primary research or real advisor input.