ZetaChain and AnumaAI are evolving projects @ZetaChain @ZetaChain_KR @AnumaAI @AnumaAI_KR Rather than operating as separate initiatives, ZetaChain and AnumaAI are developing in a structure where ZetaChain builds the infrastructure connecting AI and Web3, while AnumaAI demonstrates real user experiences on top of it. A key focus is expanding their scope to include private memory, multimodal models, agents, and access control. When viewed together, ZetaChain and AnumaAI clearly move far beyond the traditional image of cross-chain projects. ZetaChain’s vision is to unify AI and Web3 into a single, integrated environment. Previously, blockchains were fragmented per chain, and AI models were siloed per system—forcing users to reconnect and re-provide data every time they switched services. ZetaChain aims to reduce these fractures by creating infrastructure that connects multiple chains and multiple AI models within one unified environment. In this context, AnumaAI’s role is critically important. Anuma enables users to interact with multiple AI models within a single service, ensuring continuity of user memory and conversational context—even when switching models. Recently, it has introduced Council Mode, allowing simultaneous queries to multiple models for comparison or consolidated responses, along with integrations to external services like Slack. But personally, the most significant aspect remains Memory. As you use AI continuously, information accumulates—what tasks you’re working on, how you prefer responses, past decisions you’ve made. The problem so far has been that this data remains trapped within individual AI services. Anuma’s private memory seeks to solve this by giving users direct control: encrypting memories and enabling their reuse across models, while letting users manage exactly which apps or agents can access specific information. Ultimately, ZetaChain’s vision is not simply about moving AI onto blockchains—it’s about unifying memory, identity, permissions, payments, and agents into a single infrastructure. In particular, as AI agents evolve beyond answering questions to executing trades or interacting with multiple services, permission management and payment infrastructure will become indispensable. ZetaChain provides the foundational layer capable of operating across multiple chains, while Anuma delivers tangible, user-facing AI experiences—each playing a distinct yet complementary role. Therefore, when evaluating their future potential, it’s not enough to focus solely on Anuma’s user growth or the number of new AI models added. What matters more is how personal memories and agent experiences generated within Anuma will integrate with ZetaChain’s infrastructure—and how other developers will leverage this structure to build entirely new services. Significant challenges remain. As AI models diversify, securely managing personal data and permissions becomes more critical. When agents begin handling real assets or services, verification of execution and clear accountability structures become essential. Nevertheless, the direction ZetaChain and AnumaAI are taking is unmistakably clear: ZetaChain is addressing fragmentation not just between chains, but between AI models and applications; Anuma is ensuring that user memory and experience remain continuous within this unified AI environment. Ultimately, the future won’t be defined merely by how intelligent AI becomes—but by how well the AI you use understands you, and whether you retain direct control over those memories while connecting them across services. The path ZetaChain and AnumaAI are forging is one worth watching closely as AI and Web3 converge.