Why Verifiable Data Is the Missing Layer in AI: Walrus
Decrypt
by Decrypt StaffFebruary 19, 2026
AI-Generated Deep Dive Summary
AI systems are becoming increasingly autonomous, influencing critical sectors like finance and healthcare. However, their reliance on data pipelines that lack independent verification creates trust issues. This is where Walrus, a decentralized data layer designed for AI workflows, comes into play.
Walrus provides a verifiable foundation by assigning unique IDs to datasets, ensuring any alteration can be detected. It operates within the Sui Stack, which includes Nautilus (offchain AI workloads) and Seal (access control). These layers together enable cryptographic verification of data provenance, computation, and access, forming an immutable audit trail.
This shift from centralized trust to independent verification is crucial for regulated industries. By anchoring integrity cryptographically, Walrus eliminates the need to trust a single entity. This approach bridges AI's potential with blockchain's strengths, offering transparency and compliance in AI processes.
For crypto and web3 enthusiasts, Walrus exemplifies how blockchain can enhance AI reliability. Its integration of decentralized infrastructure addresses key challenges in trust and auditability, making it essential for projects requiring secure and verifiable AI solutions.
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Originally published on Decrypt on 2/19/2026