Sui Foundation Invests $30M in DATA Network to Scale AI Training Data

The Sui Foundation is investing $30 million into the DATA Network to establish a verifiable supply chain for rights-cleared AI training data. This represents the largest institutional stake in the project to date. As part of this migration, the DATA Network will transition to operate as a native protocol on the Sui blockchain. The project's independent chain will be retired, and the $DATA token will undergo a one-to-one migration.

"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 Adeniyi Abiodun, Co-Founder and Chief Product Officer at Mysten Labs, in a statement regarding the partnership.

Scaling the Trace Registry

The integration centers on Trace, an onchain registry designed to verify the origin and consent status of data used for training artificial intelligence models. Since its launch in June 2026, the registry has recorded over 250 million contributions. The platform currently processes an average of more than 3 million verification receipts per day. This transition to Sui and the decentralized storage protocol Walrus is intended to support this volume as demand for audited datasets grows.

"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," said SY Lee, Chairman of Poseidon and CEO of PIP Labs.

Why Data Provenance Matters for AI

The shift toward onchain data registries addresses the tension between AI model performance and regulatory compliance. AI developers face scrutiny regarding the copyright and licensing status of their training materials. Consequently, the ability to provide an auditable trail of data ownership has become a requirement for enterprise-grade applications.

"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," said Andrea Muttoni, CEO of DATA Foundation.

By leveraging the Sui blockchain's architecture, the DATA Network aims to provide the throughput necessary to manage these datasets. This ensures that provenance information remains immutable and accessible throughout the lifecycle of an AI model's development.