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We built Arcytic because trusting a single AI answer is a mistake. AI models often sound confident even when they’re wrong. There’s no clear signal telling you when that’s happening. Arcytic asks multiple AI models the same question, analyzes where they agree and disagree, and surfaces the strongest, most reliable answer instead of dumping multiple responses on you. When models disagree,...
ArcyticOne question. Multiple AIs checked. One verified answer.
AI answers often sound confident even when they’re wrong. Arcytic fixes that.
It asks multiple AI models the same question, analyzes where they agree and disagree, and surfaces the strongest, most reliable answer.
When models diverge, Arcytic flags uncertainty instead of guessing. You see when an answer is safe to trust and when it isn’t.
ArcyticOne question. Multiple AIs checked. One verified answer.
Arcyticstarted a discussion
What we learned verifying AI answers across multiple models
While building Arcytic, we noticed something unexpected. The biggest AI failures weren’t obvious hallucinations. They were confident answers that were subtly wrong — and hard to catch. When we compared the same question across multiple models, two patterns kept showing up: 1. Strong agreement usually meant the answer was safe to trust. 2. Disagreement was a reliable signal of risk, even when...