The artificial intelligence industry faces a structural shift as developers exhaust open internet text repositories and confront tighter regulatory mandates around data consent and provenance. Addressing this bottleneck, the DATA Network and its Trace registry are joining the Sui blockchain infrastructure stack to scale the supply chain for AI training data. The integration introduces native protocol functionality, backed by a $30 million strategic investment from the Sui Foundation.
Under the migration plan, the DATA Network will upgrade to run natively as a protocol on Sui, retiring its independent chain. Concurrently, Walrus will become the default storage layer for applications operated by the DATA Foundation. The strategic alignment aims to combine high-performance transaction execution with robust data provenance tracking for frontier artificial intelligence models.
What Changed
The infrastructure overhaul transitions the independent DATA Network onto the Sui ecosystem. Rather than operating as a standalone chain, the DATA Network will function natively on Sui. As part of this transition, Walrus is designated as the default storage layer for applications managed by the DATA Foundation.
To facilitate the ecosystem expansion, the Sui Foundation is committing a $30 million investment into the DATA Network. Existing token holders will experience a seamless transition, as the DATA token carries over on a one-to-one basis to the Sui protocol. Holder economics and governance rights will remain at least equivalent to current standards, while locked and vesting positions will carry over unchanged.
The Trace registry, a core component of the network, currently processes significant verification volume. According to project data, Trace has registered more than 250 million contributions and averages over 3 million receipts per day. Applications actively writing to Trace include Kled, Numo, and Oto. Notably, Kled is described as the largest opt-in human data marketplace, with over 1.5 billion records currently being onboarded.
Context and Industry Drivers
Industry leaders emphasize that the evolution of machine learning models relies heavily on verified, compliant data inputs. The shift reflects broader regulatory pressures and practical constraints regarding open-web scraping.
“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,” said representatives involved in the stack integration. “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.”
Project architects further noted that future model training must account for human-sourced data origin. “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,” noted development contributors. They highlighted that joining the Sui stack pairs their registry with a major engineering organization and a well-capitalized strategic partner.
Technical and Business Implications
Migrating the supply chain to Sui leverages specific technical capabilities of the target network. Sui executes independent transactions in parallel and settles them in under a second, providing the throughput necessary for high-frequency receipt processing.
From a technical standpoint, the integration expands the scope of the registry beyond basic audit trails. “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,” project contributors explained.
Business implications center on establishing a trusted framework where frontier AI labs can acquire rights-cleared datasets. By combining traceable audit histories with scalable storage layers like Walrus, the ecosystem attempts to solve compliance requirements while ensuring contributors receive appropriate attribution and compensation.
Limitations and Uncertainties
While the roadmap outlines advanced infrastructure features, certain capabilities remain under development or subject to technical milestones. Specifically, the ability of Trace to hold an encrypted, immutable copy of the contributed file itself as a reference guarantee is described as a future capability. Additionally, the implementation of fully verifiable trusted execution environments (TEEs) for evaluations and fine-tuning operations is characterized as a potential future development rather than an immediate functional specification.
What to Watch Next
Observers will monitor the execution of the one-to-one DATA token migration to the Sui protocol and the integration progress of applications like Kled, Numo, and Oto. Further updates from the Sui Foundation and the DATA Foundation will clarify the timeline for deploying Walrus as the default storage layer and rolling out advanced reference file storage features.