Triall

Triall is a verification platform that addresses AI hallucination by submitting your queries to three independent AI models that blind peer-review each other's responses. Rather than trying to fix individual AI systems, Triall puts them on trial—using consensus, contradiction detection, and real-world verification to separate reliable answers from confident fabrications. The platform employs a multi-layered approach: pre-analysis flags hidden assumptions, parallel model responses expose different failure patterns, and blind peer review explicitly checks for false confidence and fabricated details. Real-time web search provides current information, while convergence analysis detects the most dangerous hallucinations—cases where models confidently agree despite lacking evidence. An adversarial refinement loop challenges answers until they're robust, and final claim verification checks specific statements against live web sources rather than relying on AI-to-AI fact-checking. Triall recognizes that AI hallucination isn't a bug but an inherent feature of how language models are trained—the drive to produce acceptable answers. By using architectural diversity, external sources, and systematic adversarial testing, Triall makes hallucinations visible and measurable. Key features: Three independent AI models, blind peer review, real-time web verification, anti-sycophancy detection, adversarial refinement, and devil's advocate counterarguments. Available as a Claude, ChatGPT, and general AI assistant integration. Free tier includes 3 sessions with no signup required.