AI agents are making decisions with no audit trail. XYO and Theta just built the fix — Markus Levin, Co-Founder

AI hallucinations aren't a model problem — they're a data problem. When AI systems have no way to verify what's real in the physical world, they fill the gaps with guesses. And when AI agents act on those guesses autonomously, there's no record of what happened or why. DATA PROVENANCE is the missing layer, and XYO just shipped it. Markus Levin, Co-Founder of XYO, breaks down two major announcements: Data Lakes — now live at xyo.network/data-lakes — and a partnership with Theta Network that pairs XYO's verifiable on-chain data infrastructure with Theta's decentralized media and delivery layer. Markus explains why AI hallucinations are fundamentally a data provenance problem, what the absence of an audit trail means as AI agents become financial managers, logistics coordinators, and healthcare decision-makers, and how XYO's AI SDK lets developers add cryptographic proof to agent decisions and model outputs today. From why enterprise regulators are demanding verifiable data to what the XYO x Theta partnership creates that neither network could build alone, this is the accountability infrastructure conversation that AI needs to have.
You'll learn:

• Why AI hallucinations are a data provenance problem — and how XYO's verified physical-world data layer addresses it at the source
• What XYO Data Lakes unlocks for enterprises that need auditable, tamper-proof records of real-world operations and AI agent decisions
• How the XYO x Theta partnership combines verifiable data infrastructure with decentralized media delivery — and what that creates for developers building AI applications

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