W3.io and Space and Time Collaborate to Launch Verifiable AI Finance Infrastructure

TheNewsCrypto2026-04-21 tarihinde yayınlandı2026-04-21 tarihinde güncellendi

Özet

W3.io and Space and Time have partnered to launch a verifiable AI finance infrastructure designed to address the accountability gap in autonomous financial operations. The collaboration combines W3’s platform for creating and automating agent-powered financial workflows with Space and Time’s verifiable data blockchain, ensuring end-to-end proof from execution to settlement. This two-layer verification system processes over 200,000 operations daily and has been validated in production by Creatorland, a platform serving 100,000 content creators. The partnership enables businesses to deploy multi-vendor financial processes quickly and auditably, with support from integrations including Circle, Stripe, and PayPal. The system provides a trust layer for autonomous financial movements, ensuring data integrity and operational transparency beyond traditional cloud databases.

Today, Space and Time, the data blockchain that secures onchain finance, and W3.io, the operating system for autonomous finance, announced a production cooperation that provides business financial operations with end-to-end verifiable infrastructure. Over 200,000 operations are processed daily by the active integration.

Financial choices are being made by AI agents more quickly than businesses can keep up. Businesses are facing an increasing accountability gap as autonomous processes proliferate across suppliers, payments, and compliance systems: who approved what, when, and can you prove it? With a two-layer verification architecture that covers both workflow execution and the underlying data driving the processes, W3 and Space and Time fill that gap.

Businesses can create, automate, and manage agent-powered financial processes using W3’s platform and implement them in a day rather than months. The layer of verifiable facts underneath is provided by Space and Time. W3 verifies the workflow. The record is verified by Space and Time. When combined, they provide businesses with an unchangeable chain of proof from execution to settlement, that no single party can alter.

“You need a database that is built for accountability. Full stop,” said Porter Stowell, chief executive of W3.io. “When AI agents are moving real money across multiple vendors, the question is not whether you have a workflow. The question is whether you can prove what happened. That is what this partnership delivers.”

Creatorland, a platform that serves over 100,000 content creators, provided production validation for the cooperation. The integration processes payments, deal management, and creator remuneration at scale, managing over 200,000 workflows daily at peak demand. Both platforms were put through a stress test during deployment in real business settings.

“Enterprises are not going to hand AI agents the ability to move real money without a record they can defend in an audit. That constraint is what will separate the agentic finance platforms enterprises actually adopt from the ones they pilot and walk away from. The architecture W3 and Space and Time have built together is designed exactly for that bar,” said Nate Holiday, co-founder of Space and Time. Holiday also serves on W3’s advisory board.

Along with Circle, Stripe, MoonPay, BitGo, Paypal, and Paxos, W3’s platform has over a dozen active integrations, including Space and Time. Businesses may create multi-vendor financial processes from pre-integrated partners and deploy them with little upfront expense because to the company’s composable design.

“Our trust assumptions extend into the decentralized protocol. We have more verifiability with Space and Time than we do with a database in AWS, where we have no idea what is happening to the data behind the scenes,” said Audie Sheridan, chief technology officer at W3.io.

Money is being moved by agents more quickly than businesses can keep up. W3 enables businesses to create, automate, and manage agent-powered financial processes that can be implemented in a day rather than months. It is the autonomous financial operating system that maintains control over corporate executives. A trust layer for money that moves itself.

The data blockchain that secures onchain finance is Space and Time. Space and Time, backed by Microsoft’s Venture Fund M12, links real-world data to onchain technologies to fuel DeFi, tokenized assets, stablecoins, and institutional markets.

TagsAltcoinBlockchain

İlgili Sorular

QWhat is the main purpose of the collaboration between W3.io and Space and Time?

AThe collaboration provides businesses with end-to-end verifiable infrastructure for financial operations, creating an unchangeable chain of proof from execution to settlement that no single party can alter.

QHow does the two-layer verification system work in this partnership?

AW3 verifies the workflow execution while Space and Time verifies the underlying data and record, together ensuring complete accountability for autonomous financial processes.

QWhich company provided production validation for this collaboration and at what scale?

ACreatorland, a platform serving over 100,000 content creators, provided production validation, managing over 200,000 workflows daily at peak demand.

QAccording to Nate Holiday, what separates successful agentic finance platforms from those that fail?

AThe ability to provide a verifiable record that enterprises can defend in an audit, which is the constraint that separates adopted platforms from those that are piloted and abandoned.

QWhat advantage does Space and Time provide over traditional cloud databases according to W3's CTO?

ASpace and Time provides more verifiability than databases in AWS because businesses can see what's happening to their data, unlike traditional cloud databases where they have no visibility behind the scenes.

İlgili Okumalar

AI Relay Stations Spark Heated Debate on Zhihu: Behind Cheap Tokens, What Are Users Really Worried About?

A discussion on Zhihu about "AI relay stations" shifted the niche developer topic of "cheap tokens" into broader user awareness. Users moved beyond simply questioning the legitimacy of these services to focus on practical concerns: Where do cheap tokens truly come from? Is the model being accessed the real one? Can relay stations see prompts, code, and API keys? For occasional users, are the risks worth it? The core debate centered less on price and more on trust. A primary worry is model authenticity—the risk of "model swapping," where users paying for a premium model might be routed to a cheaper one, creating an information asymmetry. Others argued that cost comparisons matter; while cheaper than official pay-as-you-go APIs, relay stations may not be the lowest-cost option versus subscriptions, domestic models, or free tiers, making user needs assessment crucial. Speculation about token sources ranged from legitimate bulk discounts to gray-area methods like account sharing or exploiting regional pricing. This opacity makes risk assessment difficult for users. Data security emerged as a critical concern, especially for enterprise use. When processing sensitive information like code, contracts, or client data, the inability to verify a relay station's data handling, retention, or access policies poses significant compliance and confidentiality risks. The evolving consensus suggests relay stations can be used cautiously for low-sensitivity, disposable tasks (e.g., summarizing public info, simple translation). However, they should not be the default for sensitive, professional, or production workflows involving proprietary data, Agents, or automated systems. Recommendations include avoiding large prepayments, not relying on a single service, using test prompts to monitor quality, anonymizing data where possible, and keeping official channels as backups. Ultimately, the discussion framed tokens not just as a billing unit but as a measure of real cost encompassing price, model integrity, data security, and service stability. The popularity of relay stations highlights user demand for affordable access, but the debate underscores a key trade-off: the savings from cheap tokens may come at the price of trust, transparency, and control over one's data and AI experience.

marsbit17 dk önce

AI Relay Stations Spark Heated Debate on Zhihu: Behind Cheap Tokens, What Are Users Really Worried About?

marsbit17 dk önce

In-Depth Research Report on TradFi: The Convergence Wave of Crypto and Traditional Finance

In 2026, the crypto industry is undergoing a profound infrastructure-level transformation—TradFi assets are migrating on-chain at an unprecedented pace. According to CoinGecko's Q1 2026 report, the total value locked (TVL) of tokenized real-world assets (RWA) has surpassed $31 billion, a nearly 4x increase from $7.8 billion at the beginning of 2025, with the sector’s aggregate market capitalization reaching $19.3 billion. Among these, the market cap of tokenized stocks surged from $2 million to $486 million, with Q1 spot trading volume reaching $15.1 billion—a single quarter already surpassing the entire second half of 2025. RWA perpetual contract Q1 trading volume reached a staggering $524.8 billion, far exceeding the $313 billion for all of 2025. Meanwhile, BlackRock's BUIDL fund has reached $2.3 billion in scale and has filed for two new tokenized funds, signaling that the world's largest asset manager's tokenization strategy is evolving from pilot to product suite expansion. HTX, as a core participant in the crypto exchange sector, officially launched TradFi perpetual futures products including NVDA, AAPL, MSFT, META, and SPY in 2026, enabling crypto users to gain 24/7 trading access to core U.S. equities. Boston Consulting Group predicts that global tokenized asset scale could reach $16 trillion by 2030, while McKinsey offers a conservative estimate of approximately $2 trillion. The on-chain migration of TradFi assets is no longer a "future narrative" but a structural transformation unfolding in real time, as crypto exchanges evolve from single crypto asset trading platforms toward "multi-asset-class trading infrastructure."

HTX Learn19 dk önce

In-Depth Research Report on TradFi: The Convergence Wave of Crypto and Traditional Finance

HTX Learn19 dk önce

Blocked Its Own Treasure, WeChat AI Steps Up

Tencent's stock surged over 10% on June 2nd amid reports that WeChat, with 1.43 billion monthly users, is finalizing tests for a native AI Agent. The reported feature, accessible by swiping right from the main interface, allows users to issue commands in natural language. The AI then decomposes tasks and automatically calls upon relevant Mini Programs within WeChat to complete actions like ordering food, booking tickets, or making payments, creating a closed-loop service execution system. This strategic shift follows the internal conflict and subsequent "blocking" of Tencent's standalone AI app, Yuanbao, by WeChat for violating sharing rules during a 2026 Spring Festival promotion. The incident highlighted a lack of internal consensus and exposed the weakness of competing in the standalone AI assistant arena against rivals like ByteDance's Doubao (345M MAU) and Alibaba's Qianwen. The new WeChat AI Agent aims to leverage WeChat's unique assets—its massive user base, standardized Mini Program APIs, WeChat Pay, and identity system—to move from simple content generation to actual task execution. Analysts note this changes the competitive landscape from model benchmarks to which AI can connect to more real-world services. However, success depends on key variables: the capability of Tencent's underlying Hunyuan model, managing massive inference costs, and redesigning incentives for Mini Program developers whose traffic might be bypassed. The move is seen as an attempt to keep user service intent within WeChat's ecosystem as AI begins to redefine how users access services.

marsbit1 saat önce

Blocked Its Own Treasure, WeChat AI Steps Up

marsbit1 saat önce

ByteDance Adopts Arm CPUs, Jensen Huang: So Sad I Didn't Buy Arm

**Summary:** At Computex 2026, Arm CEO Rene Haas announced that ByteDance and Oracle have adopted Arm's self-designed Arm AGI data center CPU. The company expects significant revenue growth from this product, projecting $20 billion in demand for the 2027/2028 fiscal years. Haas noted that restricting AI-capable CPUs from the US to China is nearly impossible due to their widespread applications. Arm's stock has surged dramatically this year, notably rising 16% after NVIDIA's Arm-based Vera CPU and RTX Spark announcements. A highlight was the informal, humorous on-stage conversation between Haas and NVIDIA CEO Jensen Huang. Huang joked about NVIDIA's failed attempt to acquire Arm and playfully lamented selling his Arm shares. Both executives showed a clear sense of camaraderie and shared regret over the missed merger. Key technical topics were discussed: 1. **AI PC Design:** Huang explained NVIDIA's RTX Spark superchip (with a 20-core Arm CPU) is designed for future AI agents that will autonomously run and use tools on PCs, blending local and cloud processing. 2. **Agent vs. OS:** Huang emphasized the operating system remains crucial, as AI agents rely on its APIs and tools to function. 3. **Growth Constraints:** He identified the shift to "useful AI" that generates profitable tokens as a primary driver for immense, almost limitless, computational demand. Haas outlined Arm's strategy across PC and data centers. For PCs, Arm collaborates with partners like NVIDIA and MediaTek, offering its compute subsystem (CSS) for custom SoCs. In data centers, its Arm AGI CPU (built on TSMC's 3nm process) has gained major partners including OpenAI, Meta, and now ByteDance and Oracle. Arm presented a multi-year roadmap for its in-house CPU line. The article concludes that while GPUs dominated the AI training race, the explosion of AI agents is shifting significant focus to CPUs for inference, state management, and tool orchestration. The industry is trending towards vertical integration, with companies like cloud providers designing chips and chip/IP firms offering full solutions, all competing to deliver more efficient computing per watt.

marsbit1 saat önce

ByteDance Adopts Arm CPUs, Jensen Huang: So Sad I Didn't Buy Arm

marsbit1 saat önce

İşlemler

Spot
Futures
活动图片