The @brevis_zk first usage example was on Kaito. One of the biggest challenges in the Web3 world is whether AI-driven data can truly be trusted. The verifiable mindshare markets approach that @KaitoAI launched on Polymarket introduces a new category of prediction markets based on metrics like popularity, sentiment analysis, and mindshare. But this brings up a critical question:How can participants be sure these metrics arenât being manipulated.
Mindshare scores are calculated using Kaitoâs own algorithms. This system canât be fully opened because the algorithm is the companyâs intellectual property. However, for prediction markets to remain sustainable, traders need some form of proof that these calculations are done correctly.
This is exactly where Brevis comes in. Brevis uses ZK proofs to verify that Kaitoâs mindshare calculations are accurate without revealing anything about the underlying algorithm. In this way, Brevis acts as a trustless computation oracle.
A trustless computation oracle is a system that proves to on chain smart contracts that an external computation was performed correctly, without requiring trust in any third party.
And with @eigencloud making AI inferences verifiable, the entire process becomes trustworthy end to end.
Kaitoâs mindshare driven prediction markets reach on chain transparency standards and become fully auditable.
Brevis sits at the center of this transformation by making even closed systems verifiable.

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