Ant Digital Tech Proposes New Architecture for Agent Economy, Covering Four Layers: Identity, Payment, Risk Control, and Compliance

marsbit2026-04-20 tarihinde yayınlandı2026-04-20 tarihinde güncellendi

Özet

Ant Digital Technologies (Ant Digital) has introduced a new architectural framework for the agentic economy, named the "4R Full-Stack Architecture," at the Hong Kong Web3 Festival. The framework is designed to address four core challenges in AI agent operations: identity, payment, risk control, and compliance. The four layers include: - **Agentic Runtime**, featuring DTClaw with the CARLI security model to enforce behavioral constraints and ensure controllability and auditability; - **Payment Rails**, which provide on-chain payment channels supporting smart decision-making, verifiable credentials, instant settlement, and cross-chain asset transfers; - **Agent Registry**, leveraging DIDs and the ERC-8004 standard to assign verifiable on-chain identities to agents; - **Root Infrastructure**, built on Jovay Layer2 and ZKVM technology to enable high-speed micro-payments and trusted off-chain computation with on-chain verification. According to CTO Yan Ying, the architecture aims to resolve fundamental gaps in the current agent economy—such as execution vulnerabilities, identity issues, payment barriers, and trust deficits—by redesigning underlying infrastructure rather than applying superficial fixes. The initiative builds on Ant Digital’s extensive experience in financial-grade security, privacy computing, and blockchain.

On April 20, Ant Digital Tech introduced the "4R Full-Stack" architecture concept for the agent economy at the Hong Kong Web3 Festival, encompassing four layers: Agentic Runtime, Payment Rails, Agent Registry, and Root Infrastructure. This framework aims to provide AI agents with a technical infrastructure covering identity, payment, risk control, and compliance.

Ant Digital Tech CTO Yan Ying pointed out in her speech that the current foundation of the agent economy suffers from "four gaps": execution failures due to prompt logic vulnerabilities, responsibility vacuums caused by AI's lack of credible identity, transaction barriers from payment gateways designed for humans, and collaboration risks arising from a lack of trust between unfamiliar agents. "These cannot be resolved by simply patching software; they require a redesign from the underlying infrastructure level," she said.

According to Yan Ying, the core product of the Agentic Runtime layer is DTClaw, which incorporates the CARLI security model to enforce constraints on agent behavior at the execution level. It supports multi-model compatibility and financial-grade compliance standards, aiming to make every AI operation controllable, auditable, and recoverable.

The Payment Rails layer builds native on-chain payment channels, integrating agent intelligent decision-making with verifiable credential chain technology. This ensures precise payment intent recognition and full-link security control while achieving transparency and immutability in the transaction process. For high-frequency micro-transaction scenarios, the platform constructs a native instant settlement network that supports cross-chain, multi-asset seamless flow, and intelligent routing, significantly improving capital turnover efficiency. Additionally, by providing a standardized development toolchain and a seamless wallet integration experience, the solution greatly reduces development barriers and user costs, forming a payment closed-loop that balances financial-grade security and an optimal user experience.

The Agent Registry layer issues on-chain identities for each agent based on DID (Decentralized Identity) and the ERC-8004 standard, ensuring that every collaboration between agents is documented. The Root Infrastructure layer serves as the architectural foundation, utilizing Jovay Layer2 to achieve 120-millisecond confirmation times to support AI micro-payments, and combining ZKVM technology to enable off-chain computation and on-chain verification, addressing the trust issues in AI economy computing power. Yan Ying stated, "The Root Infrastructure uses blockchain and privacy computing technologies to provide agents with an immutable contract execution environment. Even two unfamiliar AIs can establish trust based on code and conduct transactions with confidence."

Currently, AI is evolving from the era of Chat and Action to the era of the agent economy. Yan Ying believes that the qualitative change in the third stage lies not in AI becoming smarter, but in it beginning to possess assets and transaction rights. She noted that over the past decade, Ant Digital Tech has accumulated extensive engineering practices in financial-grade security, privacy computing, blockchain, and compliance systems, and the 4R architecture is built upon this foundation with全新研发和设计 (entirely new research and design).

İlgili Sorular

QWhat is the '4R Full-Stack' architecture proposed by Ant Digital Tech, and what are its four layers?

AThe '4R Full-Stack' architecture is a framework for the agentic economy proposed by Ant Digital Tech. Its four layers are: Agentic Runtime, Payment Rails, Agent Registry, and Root Infrastructure.

QAccording to Ant Digital Tech's CTO, what are the 'four fractures' in the current foundation of the agentic economy?

AThe 'four fractures' are: 1) Execution loss of control due to prompt logic vulnerabilities, 2) A responsibility vacuum caused by AI's lack of a trusted identity, 3) Transaction barriers from payment gateways designed for humans, and 4) Collaboration risks from a lack of trust between unfamiliar agents.

QWhat is the core product in the Agentic Runtime layer and what is its primary function?

AThe core product in the Agentic Runtime layer is DTClaw. Its primary function is to enforce mandatory constraints on agent behavior at the execution level, making every AI operation controllable, auditable, and recoverable.

QHow does the Payment Rails layer facilitate transactions for AI agents?

AThe Payment Rails layer builds native on-chain payment channels that integrate agent intelligent decision-making with verifiable credential chain technology. It ensures precise payment intent recognition, full-link security, transparency. It also features an instant settlement network for high-frequency micro-transactions, supporting cross-chain, multi-asset flow and smart routing.

QWhat technologies are used in the Root Infrastructure layer to support the agentic economy?

AThe Root Infrastructure layer utilizes Jovay Layer2 to achieve 120-millisecond confirmation times to support AI micro-payments, and combines ZKVM technology to enable off-chain computation with on-chain verification, solving the trust problem in AI economy computing power.

İlgili Okumalar

When Doing Cryptocurrency Payment, the First Thing is Licenses, What is the Second?

When launching a crypto payment business, obtaining the necessary licenses is the crucial first step. However, the second, and arguably more critical, step is designing a comprehensive operational framework that forms a coherent business loop. This loop must be clearly understood and executable by all stakeholders: banks, payment partners, exchanges, on-chain analytics providers, regulators, and your internal team. Many projects mistakenly believe a single license permits all operations. Licenses merely grant entry; they don't define how the specific business functions. The real challenge lies in detailing every aspect of the workflow. This involves clarifying the customer base, the flow of fiat and crypto assets, the settlement process, and establishing clear lines of responsibility for risks like AML compliance, sanctions screening, chargebacks, and regulatory inquiries. A robust framework must answer seven core questions: Who are the clients and merchants? Who collects fiat and crypto? Who handles conversion and custody? And who is ultimately accountable for compliance and risk management? Projects often fail not from a lack of licensing, but during due diligence when they cannot convincingly explain these operational details. Therefore, beyond securing licenses, the priority must be constructing a closed-loop system. This system ensures the business model is transparent, risks are managed, responsibilities are delineated, contracts are aligned, and the entire process is comprehensible to partners and regulators. The true competitive edge in crypto payments lies not in acquiring a license quickly, but in integrating licensing, banking, compliance, and operations into a sustainable and executable whole.

marsbit47 dk önce

When Doing Cryptocurrency Payment, the First Thing is Licenses, What is the Second?

marsbit47 dk önce

Arthur Hayes Analysis: AI Bubble Nears Burst, Crypto Market Faces Short-Term Pressure

Arthur Hayes argues that the current AI market is a bubble poised to burst, which will exert downward pressure on the crypto market in the near term. The core trigger is rising oil prices due to the US-Iran conflict and a blockade of the Strait of Hormuz. Higher energy costs directly increase the operational expenses of AI data centers, squeezing profit margins for companies like Google, Anthropic, and OpenAI. Hayes predicts that persistent inflation from high oil prices will force Trump, in a bid to win the November election, to turn public sentiment against the AI industry. He may propose regulations and taxes on data centers and AI companies to appeal to voters concerned about costs and job displacement. Such political rhetoric could shatter market confidence. Furthermore, the market is unlikely to healthily absorb the massive concurrent IPOs of SpaceX, Anthropic, and OpenAI, which together seek valuations in the trillions. The combination of soaring energy costs, overwhelming equity supply, and negative political pressure will puncture the AI bubble. Hayes notes that nearly all new USD liquidity since 2022 has flowed into AI, leaving crypto like Bitcoin behind. When the AI bubble bursts, liquidity will contract sharply, pulling down all risk assets, including cryptocurrencies. In response, Hayes's fund, Maelstrom, has sold all AI-related stocks and non-core cryptocurrencies. It maintains core positions in Bitcoin and Ethereum while increasing exposure to energy sector equities, betting on rising oil and gas prices. He expects Bitcoin to bottom after the AI-led market decline, before rallying again with future monetary easing.

Foresight News1 saat önce

Arthur Hayes Analysis: AI Bubble Nears Burst, Crypto Market Faces Short-Term Pressure

Foresight News1 saat önce

To C, To B, and the Next Big Thing Called To A

After To C and To B, the Next Wave is To A: Serving AI Agents In a recent quarterly earnings call, Meituan's Wang Xing introduced a new concept: To A (To Agent), signifying that future business services will increasingly target AI Agents as primary clients, not just consumers or merchants. This shift implies that internet giants must now consider how to make their services more appealing for AI Agents to recommend, fundamentally altering traditional distribution logic. This "To A era" is prompting an unusual trend of alliances among major tech companies. Unlike previous competitive battles, firms like Meituan, Tencent, JD.com, Huawei, OPPO, and OpenAI are rapidly forming partnerships. The reason is strategic: as AI Agents become the primary user interface, handling tasks from a single command (e.g., "Book a Japanese restaurant for tomorrow"), the risk for platforms is being bypassed entirely. Companies are positioning themselves within this new value chain. Three primary strategies are emerging: 1. **Super-Entry Points + Service Providers:** Platforms like Tencent's Yuanbao, WeChat, and ChatGPT aim to be the first-stop Agent, integrating various services (food delivery, shopping, travel) from partners like Meituan and JD.com. 2. **Apps as Callable Services:** Companies like Meituan, JD.com, and Uber are ensuring their core services remain accessible and callable by external Agents, shifting from front-end apps to back-end capabilities. 3. **System-Level Agent Entry Points:** Smartphone makers (Huawei, Honor, OPPO) are leveraging their OS-level AI assistants to control the initial user command, redistributing it to relevant service apps. While alliances offer mutual benefit—entry points gain service capabilities, and service providers gain traffic—inherent conflicts of interest exist. A dominant Agent platform could eventually attempt to connect directly with suppliers (restaurants, hotels), bypassing current aggregators like Meituan or Ctrip. Other unresolved challenges include the potential for Agent recommendations to become a new form of paid ranking and unclear accountability for faulty recommendations. The current rush to form alliances is a defensive move by service providers to secure their position before the landscape solidifies. In this To A-driven restructuring, the greatest risk is not losing the race but failing to hear the starting gun.

marsbit1 saat önce

To C, To B, and the Next Big Thing Called To A

marsbit1 saat önce

İşlemler

Spot
Futures
活动图片