Animoca-backed Origins secures $8M to develop AI-focused blockchain, enabling verifiable compute and auditable agent decisions using Proof of Computation model

Origins Network, a modular blockchain project focused on artificial intelligence, has raised $8 million in strategic funding to develop an AI-centric chain that supports verifiable compute and auditable AI agent decisions using a Proof of Computation (PoC) model. The round is led by Animoca Brands with participation from TBV, Candaq FinTech Group, Castrum Capital, Coinvestor Ventures and other Web3 and institutional backers, positioning the project at the intersection of blockchain infrastructure, AI agents, and large cloud providers. Origins Network is building a modular public blockchain tailored for AI agents, where heavy AI workloads such as model inference run off-chain on GPU-rich infrastructure while succinct cryptographic proofs of that computation are verified and settled on-chain. Under its PoC design, AI agents submit tasks to an off-chain execution layer—leveraging partners including AWS, Tencent Cloud, and Alibaba Cloud—and then post proof that the computation was performed, allowing applications to verify that a given model actually ran on specific inputs without forcing every node to re-execute the workload. This architecture aims to make AI outputs auditable, transparent, and trustless, addressing the “black box” problem in AI while avoiding the scalability issues of running AI directly on a general-purpose L1. The newly raised capital will be directed toward expanding Origins’ decentralized compute node network, improving developer tooling and ecosystem support, and funding global go-to-market efforts for AI and Web3 integrations. The project is positioning itself as infrastructure for the emerging “agentic AI” stack, where autonomous agents interact with on-chain systems and other services, with verifiable computation serving as the trust layer for AI-driven decisions in areas such as DeFi, gaming, and broader Web3 applications.

✨ AI-generated background, compiled from web sources — not editorial content.

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