Palo Alto, United States, October 12th, 2026 - The DATA Foundation is moving a major component of its provenance infrastructure for AI training data onto the Sui stack, announcing that Trace, its onchain registry with more than 250 million verifiable receipts, will operate using Sui’s infrastructure while Walrus will serve as the default storage layer for DATA Foundation applications.
The change brings Trace’s live catalog of rights-cleared training contributions onto the same suite of technologies Sui and Walrus provide for AI workloads. As part of the integration, the DATA Network itself will be upgraded to run as a protocol natively on Sui and the independent chain that currently hosts DATA Network will be retired. The foundations of provenance, storage, and access control will be consolidated inside a single technology ecosystem.
Trace was launched by DATA Foundation in June as an onchain registry to record the origin and rights associated with real-world data contributed for AI training. The registry has recorded over 250 million distinct contributions and is processing in excess of 3 million receipts per day on average. Applications currently writing contributions and receipts to Trace include Kled, which the DATA Foundation identifies as a large opt-in human data marketplace with over 1.5 billion records being onboarded, as well as Numo and Oto, both of which already license data to frontier AI labs and robotics firms.
The data AI needs next
DATA Foundation framed the move as a response to a shifting supply landscape for model training material. The foundation argues that the generative and large-scale models that follow current architectures will require access to real-world, person-generated data that is consented and provably sourced, rather than further scraping of the open web. According to the organization, provenance and consent have become procurement essentials for AI labs in light of regulatory developments such as the EU AI Act and ongoing litigation relating to training data.
Practical examples cited by the foundation underline the character of the material Trace aims to register: first-hand accounts such as a nurse’s narration of a patient’s night, dashcam footage of a commute, a technician’s recorded troubleshooting, or a customer service call in a specific language. DATA Foundation says Trace registers each contribution with a receipt that captures provenance and the rights attached to that contribution, and that the system settles payments to contributors.
Why Sui and Walrus
DATA Foundation and Sui Foundation presented the technical rationale for the migration in complementary terms. Sui was described as representing each asset as a programmable object, which allows datasets and associated licenses to be managed onchain with token-like semantics. Sui supports independent transactions that can execute in parallel and settle in under a second, capabilities the organizations say are necessary to handle millions of daily registrations.
Walrus, developed by the same engineering contributors behind Sui, extends this stack to large files. The platform stores substantial AI datasets in an efficient manner and enforces access controls so that data is readable only by licensed buyers. The integrated proposition, as outlined by the parties involved, pairs onchain provenance and ownership tracking with native storage and access control, and adds verifiable compute capabilities.
By integrating Trace with Walrus, the foundation says provenance guarantees will be strengthened and tamper evidence improved. Where a Trace record today proves that a file was registered and records when that registration occurred, the new configuration will allow Trace to hold an encrypted, immutable copy of the contributed file itself as an encrypted reference. This permits re-derivation of the record hash from the data rather than from supplied metadata, and makes it possible to verify any later processing of the file against the original reference.
Investment and governance alignment
The technology integration is paired with a strategic capital commitment. Sui Foundation is investing $30 million in the DATA Network, establishing what the announcement describes as the largest institutional stake in the network, alongside existing holdings from PIP Labs and the DATA Foundation. As part of that alignment, SY Lee, Chairman of Poseidon and CEO of PIP Labs, will join Sui Foundation in a Strategic Advisor role.
The announcement clarifies how the protocol upgrade will treat token economics and governance. The DATA Network will migrate to Sui as a native protocol; $DATA will remain the DATA protocol token on Sui and will be carried over on a one-to-one basis. The statement indicates that holder economics and governance rights will be at least equivalent to current arrangements, and that locked and vesting positions will carry over unchanged. Simultaneously, Walrus will become the default storage layer for applications built by the DATA Foundation.
Reactions from contributors and leadership
Adeniyi Abiodun, Co-Founder and Chief Product Officer at Mysten Labs, the original contributor to Sui and Walrus, provided a statement explaining the rationale from Sui’s perspective: "The AI industry has reached the point where the open internet has been read, and the next frontier is defined by access to datasets with the consent and provenance that regulators require. Sui and Walrus were built to be the home where AI data is stored, licensed, and paid for, capable of operating at the scale these systems demand. The migration of DATA Network and Trace to our stack now brings massive volumes of high-quality, rights-cleared data that is already serving the world’s frontier AI labs."
SY Lee added: "The next generation of AI will be trained on data that lives with people rather than on the open web, and that data needs consent and provenance built in, along with a way to pay the people it comes from, and Trace was built to be that layer. It now becomes part of the Sui stack alongside Walrus, backed by one of the strongest engineering organizations in the industry and with Sui Foundation as the network’s largest strategic holder. This is the right home for the network we built, and I am looking forward to helping Sui make it the data layer for AI."
Andrea Muttoni, CEO of DATA Foundation, framed the migration in terms of operational capability for AI safety and dataset quality: "Training data is critical for continuously expanding the frontier, and making sure it is traceable, auditable and cleared to use is just as important for AI safety as it is a precursor for data quality. With Trace, we have been tracking hundreds of millions of data assets. Joining forces with Sui now allows us to build out more of the stack, offering more than just an audit trail, like encrypted reference file storage and potentially fully verifiable TEEs for evals and fine tunings in the future."
Operational transition and next steps
The current DATA Network will continue to operate through the migration process. The organizations said a detailed timeline and a holder transition plan will be published prior to completing the upgrade. No specific dates for the retirement of the independent chain, nor operational deadlines for the migration, were provided beyond the commitment to publish further transition details.
Organizational descriptions
DATA Foundation supports the DATA Network protocol for tracking provenance of real-world data contributed for AI model training. The foundation’s Trace registry registers contributions with provenance receipts and a full audit trail. Applications integrated with the network include Kled, Numo, Oto, and others. The organization, formerly called Story Foundation, announced a refocused effort on AI training data in June 2026. The current public announcement reiterates that the DATA Network is being upgraded to run as a protocol on Sui.
Sui is presented in the announcement as a next-generation Layer 1 blockchain engineered for onchain finance and agentic infrastructure. The network uses an object-centric model, and according to the announcement, it makes assets, permissions, and user data programmable and verifiable, offering primitives intended to support high-performance finance and AI-native applications.
Walrus is described as a data platform created to meet AI demands. The platform enables builders, enterprises, and AI agents to move data across applications and models, safeguard information with native access rules, and make data verifiable. The announcement attributes Walrus’s engineering to cryptographers and distributed systems engineers who previously contributed to Sui and Meta’s first stablecoin initiative, and it positions Walrus as the tailored storage and access-control component of the Sui stack for AI datasets.
What remains limited or undecided
The public communication does not specify a concrete migration timeline in this announcement, other than confirming the existing network will stay active until the upgrade is complete and that further details will be provided. The announcement also notes potential future capabilities such as fully verifiable trusted execution environments (TEEs) for model evaluation and fine-tuning, but does not provide a roadmap or commitment for when those capabilities will be available.
Contact and media information
The announcement provides media contact points for DATA Foundation and Sui Foundation in support of the transition. DATA Foundation listed an email for general press inquiries and individual contacts associated with communications at PIP Labs. Sui Foundation provided a general communications email as well.
This is a report based on statements issued by DATA Foundation, Sui Foundation, and related participants. The organizations responsible for the technology and the network have supplied the details summarized here.