The rise of AI-native infrastructure marks a pivotal shift in how artificial intelligence is developed, deployed, and monetized. Among the most anticipated projects in this space, one stands out for its foundational approach to building a decentralized AI ecosystem. By prioritizing real-world usage over hype, it aims to create a sustainable network where contributors are fairly rewarded and AI assets are truly decentralized.
This vision is not just theoretical. With a testnet already showcasing impressive adoption metrics and a clear roadmap for mainnet launch, the project is poised to transform how AI collaborates and creates value. Let’s explore its core architecture, unique positioning, and the incentive model designed for long-term growth.
A Foundation Built on Real Needs
Many AI projects focus on applying AI within Web3, but the real structural need lies deeper. The future of AI requires a foundational layer for ownership, collaboration, and value distribution. Centralized platforms currently control AI’s value chain, creating a closed system that limits participation and fairness.
This project addresses that gap by building a dedicated Layer-1 blockchain designed specifically for AI operations. It enables secure registration of data, models, and AI agents, ensuring transparent tracking and revenue sharing. Unlike projects using Web3 merely for fundraising, it embeds AI collaboration into its core protocol, making decentralized participation inherent to the system.
This foundational approach has garnered significant recognition, from major venture funding to listings on top global exchanges. The support stems from a clear vision: to create an open, equitable infrastructure for the AI economy.
Differentiating Through a Three-Layer Architecture
What sets this project apart is its comprehensive three-layer architecture, tailored for AI’s unique demands. Each layer serves a distinct function, together enabling a full lifecycle for AI assets.
Infrastructure Layer
The base layer consists of the main blockchain integrated with TEE (Trusted Execution Environment) and on-chain contracts. It handles the registration and verification of data, models, and agents, ensuring privacy and security during operations. Think of it as a trusted registry and execution system that resolves ownership, usage rights, and revenue distribution.
Application Layer
This layer includes practical tools like the AI Agent Builder, Data Service Platform, and AI Marketplace. Developers can upload data, train models, and deploy agents without coding, using modular components. The focus is on utility—enabling rapid development and monetization of AI applications within a single ecosystem.
Ecosystem Coordination Layer
The most forward-looking layer, it facilitates network effects by connecting Web3 protocols, Web2 applications, compute providers, and creators through standard interfaces. This ensures multi-party collaboration and shared value, creating a self-sustaining AI economy.
This structure is inherently scalable. As more AI applications emerge—whether from Web2 or Web3—they will require a chain for asset registration, tracking, and settlement. The system is designed to support not just individual apps, but an entire network of interoperable AI services.
Validating the Model: Testnet Success and Mainnet readiness
The testnet phase provided robust validation for the project’s model. With over 3.2 million wallets and 1.4 million daily active users, it demonstrated strong demand for decentralized AI collaboration. More than 200,000 community contributors participated in data labeling, validation, and interactive tasks, proving that AI collaboration is a tangible need.
Recently, the team launched public testing for two core modules: the AI Agent Builder and AI Marketplace. These allow users to create, deploy, and monetize AI agents without leaving the platform. The upcoming mainnet launch will close the economic loop, enabling full tracking of asset registration, model calls, revenue sharing, and user interactions.
The native token plays a central role here, functioning as the medium for payments, rewards, and governance. This economic design ensures that all participants—data contributors, developers, users—are incentivized based on actual usage and contribution.
Unleashing Data Value Through Usage Rights
While many projects focus on data ownership, this network emphasizes usage rights and monetization. Data is treated as a reusable asset that can be continuously called, composed, and applied in new training scenarios. Every interaction is recorded on-chain, enabling automatic revenue distribution.
The Data Service Platform (DSP) serves as the entry point. It allows users to contribute data, complete tasks, and earn rewards, all while transforming their data into traceable, licensable assets. This approach differs from simple确权 (ownership verification) projects by creating active value streams rather than static ownership records.
For enterprises, the platform offers a one-stop solution for data sourcing, pricing, and licensing. For individuals, it turns data into a source of ongoing revenue. This model forms the core of the project’s commercial potential and long-term viability.
Designing for Sustainable Incentives
A common challenge for Web3 projects is maintaining incentives after the initial token launch. This project avoids artificial subsidies by tying rewards to real usage and contributions. The system recognizes multiple roles—data contributors, agent builders, developers, users—and allows individuals to assume multiple roles for compounded rewards.
Incentives are automatically triggered by actions like model calls, data usage, and agent deployments. The more the system is used, the more value is generated and distributed. This creates a positive feedback loop where growth drives rewards, which in turn drive further participation.
👉 Explore sustainable incentive models
The Future of AI Layer-1 Blockchains
AI Layer-1s are not replacements for traditional blockchains but complementary systems designed for a specific asset class. While traditional chains excel with financial assets, AI chains handle dynamic assets like models, data, and agents along with their complex interactions.
This project pioneers the AI-native blockchain category—a new paradigm for open, collaborative AI networks. It addresses challenges like privacy, verifiability, and efficient execution while ensuring fair value distribution. The goal is to support a future where AI is democratized, and everyone can participate in its growth.
Frequently Asked Questions
What makes this AI blockchain different from others?
It is built from the ground up for AI assets, with a three-layer architecture that supports data registration, model training, agent deployment, and revenue sharing. Unlike generic blockchains, it handles AI-specific needs like privacy-preserving computations and complex asset interactions.
How can users earn rewards on the network?
Users can contribute data, complete labeling tasks, build and deploy AI agents, or use others' models. Rewards are distributed based on actual usage and contribution value, with multiple roles allowing for diverse income streams.
What is the role of the native token?
The token is used for payments, staking, governance, and receiving rewards. It facilitates all economic activities within the ecosystem, from paying for model calls to sharing licensing revenue.
How does the platform ensure data privacy?
The infrastructure layer uses TEE (Trusted Execution Environment) and on-chain contracts to secure data during processing. All operations are verifiable without exposing raw data, balancing transparency with privacy.
When will the mainnet launch?
The mainnet is scheduled for release in the upcoming season, following successful public testing of core modules like the AI Agent Builder and Marketplace.
Can enterprises integrate with this network?
Yes, the ecosystem coordination layer provides standard interfaces for Web2 and Web3 systems. Enterprises can leverage data, models, and agents while ensuring compliance and revenue sharing.
This project represents a bold step toward a decentralized AI future. By combining robust infrastructure with sustainable incentives, it aims to create a network where everyone can contribute to and benefit from artificial intelligence. As the mainnet launch approaches, the focus remains on real-world utility—proving that decentralized AI collaboration is not just possible, but inevitable.