ZetaChain 2.0 Officially Launches as the AI Interoperability Layer
(Source: ZetaChain)
On January 27, ZetaChain formally introduced its 2.0 architecture, marking a strategic shift from a sole focus on cross-chain technology to the AI application layer. With this update, ZetaChain repositions itself as an interoperability blockchain purpose-built for AI.
In version 2.0, ZetaChain addresses a critical industry challenge: AI applications often rely on a single model and closed backends, leading to model lock-in, high scaling costs, and limited user control over contextual data. ZetaChain 2.0 empowers developers to build applications and AI Agents that run across multiple AI models—without the need for traditional backend infrastructure—enabling rapid global deployment and commercialization.
Core Architecture I: AI Portal as Unified Execution Gateway
The first core module in ZetaChain 2.0 is the AI Portal. This layer acts as a unified routing and execution gateway, allowing applications to seamlessly switch between different AI model providers without being locked into a single model or ecosystem. Through the AI Portal, developers can abstract model selection, request distribution, and execution strategies.
The system features built-in availability management, model fallback options, and dynamic optimization strategies for cost and performance. This design enables applications to select the optimal model for execution in real time. For the first time, AI applications gain cross-model capabilities—models become interchangeable and composable, all without impacting user experience.
Core Architecture II: Private Memory Layer Reshapes Data Sovereignty
Another key innovation is the Private Memory Layer—an encrypted memory system built at the protocol level. This layer securely stores user context and enables persistent AI experiences across sessions and models.
Unlike traditional AI applications that store context in centralized backends, the Private Memory Layer leverages access controls and encryption as foundational features. Only user-authorized applications or AI Agents can access stored memory data. This not only mitigates risks of data leaks and misuse, but also establishes user control over contextual data as the default—reshaping data sovereignty in AI applications.
Anuma: The First Consumer-Grade Application on ZetaChain 2.0
With the launch of the 2.0 architecture, ZetaChain has also introduced Anuma—the first AI application built on this new layer. Anuma serves as a large-model aggregation platform. Its beta version is now available for testing, and a public waitlist is open for early access.
Anuma’s standout feature is seamless access to multiple leading AI models within a single workflow, allowing users to switch between models without losing context. All memory data is governed by a user-controlled, privacy-by-default principle, making Anuma the first real-world validation of ZetaChain 2.0’s practical potential.
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Conclusion
ZetaChain 2.0 represents more than a technical upgrade—it delivers a comprehensive solution to two major challenges in AI: cross-model operation and user data sovereignty. By integrating the AI Portal and Private Memory Layer, ZetaChain offers developers greater flexibility in model selection and returns control of contextual data to users. With Anuma’s debut, this architecture has moved from concept to real-world deployment. Its future potential for AI Agents, autonomous applications, and the broader Web3 ecosystem warrants close attention.
