DATA Network joins Sui and Walrus to scale the supply chain for AI training data. Chainwire | Publish date: 10/11/2026 (Last updated: October 11, 2026 11:01 PM) Palo Alto, United States, October 12th, 2026, Chainwire Trace, the onchain registry for rights-cleared AI training data with more than 250 million verifiable receipts, brings its training data to Sui and Walrus to power the next generation of AI models. Sui Foundation and The DATA Foundation today announced that the DATA Network and its Trace registry are joining the Sui stack, bringing a live supply of rights-cleared AI training data onto the infrastructure Sui has built for AI workloads. Walrus, the data platform with integrity proofs anchored on Sui, becomes the default storage layer for applications operated by DATA Foundation. Separately, the DATA Network will be upgraded to run as a protocol natively on Sui. The upgrade gives AI labs a single place to source real-world training data they are allowed to use, with its provenance recorded by Trace and the original file stored and access-controlled on Walrus. The data AI needs next The next generation of AI models is constrained by access to real-world data. The open internet has been scraped, and the data that comes next must be sourced from people, with consent and with provenance that regulators and legal teams will accept. The EU AI Act and ongoing litigation over training data have made provenance a procurement requirement for labs. The data those models need sits with people rather than on the open web: a nurse describing a patient's night in her own words, a dashcam recording of a rainy commute in Jakarta, a factory technician's hands as they diagnose a fault, or a customer call conducted in Bengali. It is personal and often regulated, and it belongs to the people who generated it. Trace, launched by DATA Foundation in June as an onchain registry for AI training data, was built for exactly this kind of data. It records the origin of each contribution and the rights attached to it, and settles payment to the person who contributed it. It has registered more than 250 million contributions since launch and now processes over 3M receipts per day on average. Applications writing to Trace include Kled, the largest opt-in human data marketplace with over 1.5 billion records being onboarded, along with Numo and Oto, applications that already license data to frontier AI labs and robotics companies. Why Sui and Walrus Sui represents every asset as a programmable object, allowing datasets and their licenses to be managed onchain like tokens. Independent transactions execute in parallel and settle in under a second, making the network capable of handling millions of daily registrations. Walrus extends this capability to large files: it stores massive AI datasets efficiently and ensures data is only readable by licensed buyers. No other network offers storage, access control, and ownership tracking built natively into a single ecosystem, together with verifiable compute. Trace now adds a flagship supply of rights-cleared data, with existing demand from the AI labs that license it today. The result of the integration will be stronger provenance guarantees and tamper evidence. Today a Trace record proves that a file was registered and when, and with Walrus, Trace will be able to hold an encrypted, immutable copy of the contributed file itself as a reference guarantee. The hash of the record can be regenerated from the data itself rather than from metadata an application supplied, and any later processing of the file can be checked against the original. The upgrade is backed by a long-term strategic investment. Sui Foundation is investing $30 million in the DATA Network, establishing the largest institutional stake in the network, alongside the continuing holdings of PIP Labs and the DATA Foundation. Furthering the alignment, SY Lee, Chairman of Poseidon and CEO of PIP Labs, joins Sui Foundation as Strategic Advisor. The protocol upgrade DATA Network will be upgraded to run as a protocol natively on Sui, and its independent chain will be retired. $DATA continues as the token of the DATA protocol on Sui, carried over one-to-one, with holder economics and governance rights at least equivalent to today. Locked and vesting positions carry over unchanged. In parallel, Walrus becomes the default storage layer for DATA Foundation applications. Adeniyi Abiodun, Co-Founder and Chief Product Officer at Mysten Labs, the original contributor to Sui and Walrus, said: "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, Chairman of Poseidon and CEO of PIP Labs, said: "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, said: "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." The existing DATA Network will continue to operate until the upgrade is complete, and a detailed timeline and holder transition plan will be published prior to the upgrade. About DATA Foundation DATA Foundation supports the DATA Network, the protocol for tracking provenance of the real-world data AI models need. Through Trace, each contribution is registered with its provenance receipt and a full audit trail. Applications building on the network include Kled, Numo, Oto, and others. Formerly Story Foundation, the organization refocused on AI training data in June 2026. The DATA Network is being upgraded to run as a protocol on Sui. Sui, where money moves as freely as messages, is a next-generation Layer 1 blockchain built for onchain finance and agentic infrastructure. Founded by the core team behind Meta's stablecoin initiative and powered by an object-centric model, Sui makes assets, permissions, and user data programmable and verifiable. Sui's primitives offer everything necessary to create high-performance finance and AI-native applications. Learn more at sui.io. About Walrus Walrus is the data platform built for the demands of AI. It lets builders, enterprises, and AI agents move data across apps and models, protect it with built-in access rules, and make it verifiable by anyone. As AI takes actions with consequence, the data it runs on has to be provable. Created by the cryptographers and distributed systems engineers behind Sui and Meta's first stablecoin initiative. walrus.xyz Media contacts Contact. Head of Communications HV DATA Foundation [email protected] New York, United States, April 11th, 2023, ChainwireLocation-based NFT... Delaware, USA, March 28th, 2024, ChainwireIn a move to... Paris, France, 22nd March, 2022, ChainwirePokmi, NFT emerging brand...

AI x crypto roundup - decentralized agents, compute, and verifiable AI. September 1, 2026 · openai/gpt-oss-120b Tl;dr. AI agents are moving from hype to real economic activity: decentralized compute networks (Akash, Thicket, Scale), on-chain agent identities and payment rails (TermiX, x402, Kaspa), and verifiable AI inference (Walrus, Bittensor, CyAI) are being shipped and generating measurable revenue. Verifiable AI inference and standards. * Walrus launched a Verifiable Trading Standard that makes market data machine-readable and auditable, and released tutorials for adding portable Walrus Memory to Claude and TypeScript SDKs, enabling agents to retain context across calls @WalrusProtocol. * Bittensor's subnet upgrades introduced an Emission Gate that ties TAO emissions to actual market-set demand thresholds, shifting tokenomics from speculative rewards to revenue-backed emissions @0xifreqs. * CyAI announced that its verifiable inference network is live, delivering requests on a public, auditable infrastructure @cysic_xyz. * BTTInferGrid described a Challenge-Based Verification Layer where validators inject random audit tasks into GPU workloads, ensuring miners cannot cheat without incurring a detection risk @Multi_mike01. * OpenMayhem (Trac Network) released an open-source, permission-less inference router that lets providers earn in fiat or native tokens while the underlying economy remains crypto-driven @TracNetwork. Decentralized compute marketplaces. * Akash reported that after four years it earned its first $1 M in compute spend, and the sixth million was reached in just 157 days, demonstrating rapid compounding usage of its DePIN compute network @akashians_. * Thicket highlighted that its network already supports 1,500+ nodes, executed 400,000+ tasks, and enables AI agents and builders to pay for workloads directly with the native THKT token, removing the need for credit-card billing @thicket_rh. * Scale Network announced a mobile app that lets everyday users mine SCALE tokens by contributing compute resources to a coordinated, decentralized AI infrastructure, positioning the token as fuel for the network rather than a final product @ScaleNetworkAI. * io.net claimed to be #1 in Solana DePIN revenue by building a GPU-demand-driven network that generates real workload revenue @ionet. On-Chain agent identities, reputation, and payments. * TermiX's Agent Autonomous Commerce Protocol (AACP) provides on-chain identity, job discovery, escrow, reputation, and settlement for AI agents, with the mainnet reporting 374,771 agents, 229,160 jobs, $12.37 M in transaction volume and $247 K protocol revenue in August @akashroy1k. * TermiX's founder emphasized that the protocol forces agents to stake collateral that can be slashed for dishonest behavior, turning reputation into programmable economic incentives @Yaaaati_M1. * x402 infrastructure enables agents to pay for services in USDC with single-block settlement, and early work is already integrating Kaspa support (still in development) @KaspaScopio. * TermiX's marketplace, Agent Family, allows agents to both offer and consume services, creating a micro-economy where agents can hire other agents for specialized tasks @Aashir_beyg. * TermiX's AACP also supports on-chain reputation that tracks completed work, results, and interactions, laying a foundation for machine-to-machine trust @iam_islandboi. * TermiX's Genesis and Guardian Badge holders can claim AI balance rewards to spend on an on-list model marketplace, demonstrating token-gated access to AI models @xos_labs. Zero-Knowledge and provenance for AI outputs. * Beldex discussed a zero-knowledge age-verification protocol that proves eligibility without revealing personal data, illustrating how ZK proofs can protect privacy in AI-driven identity checks @hossainriad64. * The ARCTERMINAL architecture claims to prove the exact model that generated a result, preventing silent model swaps and enhancing trust in AI services @0xRiRoyal. * Jasmy's authentication system proposes attaching a cryptographic fingerprint to video content at creation, enabling provenance verification and AI-assisted deep-fake detection @BainaA17. * Teneo reported that 55,000+ agents now hold ERC-8004 identities on Base, with 1.2 M transactions processed, and that confidential model tokens can return hardware attestations for each inference call @teneo_protocol. Agent economy infrastructure and marketplaces. * AgentNet's founder highlighted a marketplace for AI agents, skills, plugins, and services that enables agents to discover, delegate, and execute work across a decentralized network @Amank1412. * Swarms announced its platform as the fourth-largest launchpad on Solana, focusing on tokenizing agents and prompts to create an on-chain capital market for the emerging agent economy @swarms_corp. * TriplePlus (TPT) introduced a single-intent matching engine that ranks available agents and backs the chosen match with capital, reducing the friction of selecting the right model from a fragmented marketplace @HuuHoang88. Takeaway: The AI-crypto space is transitioning from speculative token chatter to concrete infrastructure: verifiable inference layers, decentralized GPU compute markets, on-chain agent identities with escrow and reputation, and privacy-preserving proof systems are all being deployed and, in several cases, already generating revenue.