The team behind DATA Network, previously known as Story, announced plans to close its dedicated blockchain and transition its AI training data protocol to the Sui platform. The move will see the Trace registry – a system that logs the provenance and licensing of training data – become part of Sui’s ecosystem, while Walrus, a decentralized storage solution native to Sui, will serve as the default storage layer for applications built by the DATA Foundation and its collaborators.
Why the Shift Was Chosen
Operating a blockchain that supports a single functional area entails ongoing expenses for validator incentives, network security, and underlying infrastructure. Project representatives explained that replicating the storage and access-control capabilities already available on Sui would have required rebuilding components that exist in Walrus and the Seal framework. The decision follows a rebranding effort earlier this year, during which the organization pivoted from licensing intellectual property to constructing a comprehensive stack for AI training data.
Growth of the Trace Registry
Since its launch in June, the Trace registry has recorded more than 270 million entries in roughly four months. This rapid adoption highlighted the scalability challenges of maintaining a bespoke chain for a narrowly focused use case, prompting the foundation to seek a more efficient solution.
Transition Plan and Timeline
The existing DATA Network chain will remain operational until the migration is finalized. The foundation has pledged to release a detailed schedule and a holder transition roadmap before the upgrade goes live, ensuring participants have clear guidance on how to move assets and continue using the services.
Role of the Sui Foundation Investment
Separately, the Sui Foundation has committed $30 million to support the partnership. While the funding is a distinct element of the collaboration, it underscores the strategic alignment between the two projects and provides financial backing for the integration effort.
Why it matters
Consolidating a specialized AI data protocol onto a larger, more mature blockchain reduces overhead and leverages existing decentralized storage solutions. This migration could set a precedent for niche networks to join broader ecosystems, potentially accelerating the development of AI-centric decentralized applications while lowering operational costs for developers and users alike.
