In 2026, the AI Hallucination Crisis is not only annoying but also dangerous. Single models still hallucinate at rates of up to 30% on complex queries, and the more precision you give them, the more bias you introduce. That is the fundamental training issue that has not been resolved by a centralized lab.
@Mira - Trust Layer of AI takes a completely different approach: it breaks down any AI output—text, code, analysis, even images—into hundreds of atomic factual claims rather than relying on a single model. After that, each claim is split up at random and sent to a diverse swarm of independent LLM verifiers on decentralized nodes. $MIRA only mints a tamper-proof cryptographic certificate on the chain when majority consensus is reached, which is secured by combining Proof-of-Work (AI inference tasks) and Proof-of-Stake ($MIRA staking and slashing).
Humans are not involved. There is no central curator bias. Just cryptoeconomically enforced truth. On verified outputs, early results already show an increase in accuracy from 70% for a single model to more than 95%. This isn’t another AI hype project. The entire agent economy has been waiting for this infrastructure layer. If you’re building agents that move real money, give medical advice, or make legal decisions, you need verifiable intelligence — not just powerful intelligence.
Klok app and whitepaper are now live.