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AI hallucination isn't a bug that better training will fix. Research shows AI models have built-in over-compliance circuits that prioritize sounding confident over being accurate — and no single model can catch its own blind spots. Triall solves this architecturally. Three AI models answer the same question independently, then blindly peer-review each other's responses — no model knows who wrote what. The highest-ranked response gets synthesized, refined through iterative critique loops, challenged by a devil's advocate stage, and optionally fact-checked against live web sources. Every step is transparent and exportable. The platform includes over-compliance risk scoring (flagging when models are being confidently wrong), model diversity analysis, and a full walkthrough showing exactly what was caught and corrected. Built for professionals where accuracy isn't optional — legal, finance, research, strategy. Three presets: Full Power (Claude Opus + Grok + Gemini), a free Test Run with lighter models, and Custom mode with 120+ models via OpenRouter.
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