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Background & Overview

The Need for Real-Time, Low-Cost, and Private Microtransactions

As autonomous agents increasingly populate digital ecosystems—from decentralized AI marketplaces to on-chain data networks—the ability to transact seamlessly, securely, and privately at scale has become essential. AI agents acting as data providers, model trainers, inference engines, or composite service brokers must exchange value continuously for computation, data, or services. These interactions often take the form of real-time, high-frequency microtransactions that traditional blockchain systems cannot handle efficiently or privately.

Public blockchains provide a base layer of trust and global verifiability but are fundamentally constrained by their design: every transaction must be broadcast, validated, and stored by the entire network. This results in high fees, multi-second latency, and full transparency of payment information. For competitive AI agents, such visibility exposes sensitive information—like pricing models, data valuations, or cooperative relationships—that should remain confidential.

State channels emerged as an elegant complement to on-chain systems. They allow two or more parties to exchange signed state updates entirely off-chain, using the blockchain only as a final arbiter if disputes arise. This design enables instant, near-zero-cost, and privacy-preserving transactions, where only the final settled outcome touches the blockchain. The result is a scalable and confidential transaction layer ideally suited for the emerging machine-to-machine economy.


Celer State Channels for the AI Agent Economy

The emerging AI agent ecosystem requires a transactional layer with millisecond responsiveness, negligible cost, and strong privacy. Agents continuously exchange value for computation, data, and services—settling payments per inference, per query, or per compute cycle. Traditional on-chain mechanisms cannot meet these requirements: gas fees make micropayments uneconomical, block confirmation latency disrupts real-time coordination, and public ledgers expose competitive information such as pricing or collaboration patterns.

Celer AgentPay extends Celer’s proven state channel technology into this AI-driven world, enabling real-time, private, and programmable payments at Internet scale. Built on a generalized off-chain state channel framework, AgentPay allows agents to transact in milliseconds for model inference, data streaming, or compute-for-token exchanges, with gas-free off-chain settlement and on-chain enforceability only when required.

Its architecture supports generalized conditional payments based on verifiable computation, oracle outcomes, or ZK proofs—allowing seamless integration with diverse AI and data services. Through multi-hop routing, agents can exchange value across chains and ecosystems without requiring direct connections. The State Guardian Network (SGN) autonomously monitors off-chain states and resolves disputes on behalf of offline agents, providing continuous security guarantees.

By combining sub-second latency, scalability, and privacy, AgentPay forms a high-performance payment backbone for fast, cost-efficient, and autonomous coordination among AI agents.


Use Cases

AgentPay powers real-time, programmable payments across a wide range of AI-driven interactions. Below are representative scenarios illustrating how autonomous agents and human users transact seamlessly through its decentralized off-chain payment network

  1. Real-Time Inference and API Marketplaces
    Model providers can expose inference or analytics APIs through autonomous agents, allowing consumers to pay per inference or per query in real time. Payments occur privately off-chain, hiding demand and pricing data from competitors while providers receive instant, final settlement.
  2. Federated Learning and Data Markets
    Participants in federated learning can be rewarded continuously and proportionally based on contribution quality or data volume. Off-chain conditional payments ensure fairness and confidentiality without revealing contributor earnings or timing on-chain.
  3. Autonomous Machine-to-Machine Transactions
    IoT devices, edge nodes, and robotic systems can autonomously negotiate and pay for resources such as compute cycles, bandwidth, or sensor data. Multi-hop routing enables global value exchange without pre-established connections, maintaining end-to-end privacy and trustless settlement.
  4. Layer-2 Settlement for AI Compute Rollups
    Verifiable compute networks and inference rollups can integrate AgentPay for reward distribution, staking, and internal fee settlement. Sensitive usage metrics and performance data remain off-chain, while cryptographic settlement proofs preserve auditability and accountability.
  5. Human–AI Collaboration
    Human users engaging with AI assistants, content creators, or simulation agents can subscribe, tip, or stream payments in real time—enabling rich, continuous value exchange between people and intelligent systems.

Summary

State channels provide the missing payment and privacy infrastructure for the emerging AI agent ecosystem—enabling real-time, granular, and confidential value exchange at Internet scale.

Built on Celer’s proven technology, AgentPay offers the most mature, scalable, and composable foundation for AI-to-AI and human–AI interactions, delivering instant settlement and programmable coordination across chains and ecosystems.

This architecture marks a natural evolution from static AI platforms to self-transacting, interoperable, and privacy-preserving AI economies, where intelligence and value flow freely, securely, and autonomously across the digital world.

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