Hive Intelligence and ARC have announced a new partnership aimed at advancing on-chain intelligence and AI orchestration of real-time blockchain data. This collaboration combines ARC’s attention to secure AI agent coordination with the real-time blockchain data infrastructure provided by Hive Intelligence, which creates a viable interface between artificial intelligence systems and live activity on the blockchain.
ARC × Hive Intelligence
We’re working with @Hive_Intel. This project is one that builds one of the most practical bridges between AI systems and real-time on-chain data.
Hive Intelligence enables AI agents to understand, query, and reason about dozens of blockchain activities… pic.twitter.com/NntDyPTzmu
— ARC (@ARCreactorAI) December 30, 2025
This partnership signals an industry-wide shift beyond stagnant analytics to AI agents that can explain, reason, and act on blockchain data in real-time. ARC and Hive Intelligence combine orchestration and intelligence layers to make next-generation distributed applications more autonomous.
Bridging AI agents and real-time blockchain data
Hive Intelligence positions itself as a platform that enables AI agents to learn and query blockchain activity on dozens of networks.
Rather than viewing on-chain data as raw input, Hive Intelligence packages this data so that AI systems can make inferences based on that input and transform it into actionable intelligence. Use cases include advanced analytics, automated monitoring, and real-time decision making.
Hive Intelligence will work with ARC to improve the interaction between AI agents and this data. The orchestration layer of ARC is concerned with helping agents plan, coordinate, and execute complex workflows in a secure manner. The two platforms work to resolve the tension between information access and intelligent implementation that has traditionally constrained on-chain automation.
ARC focuses on secure AI orchestration
ARC builds its platform on the premise that AI agents require robust orchestration to scale securely. Focuses on systematic reasoning, task coordination, and security in multi-agent systems.
ARC believes that as distributed systems become more complex, orchestration is necessary to achieve reliable and predictable results.
ARC’s privacy-preserving AI middleware is called Matrix. Matrix aims to facilitate secure execution and scalable coordination without revealing sensitive logic or data. Hive Intelligence leverages Matrix to power internal operations and future capabilities as part of a partnership that strengthens execution assurance across the ecosystem.
Enabling privacy protection and scalable AI systems
The main concerns with AI-based Web3 infrastructure are privacy and security. ARC and Hive Intelligence’s partnership focuses on privacy-friendly design without compromising real-time performance. By integrating Matrix, Hive Intelligence enables AI agents to infer data in the blockchain without risking execution integrity or user trust.
This design allows standard inference between networks and is scalable. As AI agents are able to make more decisions on-chain, including automated governance measures and financial policies, secure coordination becomes even more important. This partnership meets this requirement by bringing together data intelligence and coordination.
Moving Web3 towards autonomy and trust
Both teams say this collaboration is a transition to a real Web3 system. This collaboration opens a new dimension of trust in decentralized applications by leveraging on-chain intelligence and AI coordination.
This includes more intelligent automation, better analytics, and more robust agent-based systems that can run on many blockchains.
The partnership is supported by Hive Intelligence, which has a grant from a leading technology provider that brings infrastructure reliability to the partnership and allows ARC to provide orchestration expertise for long-term scalability. Collectively, they intend to demonstrate how AI agents can move into both experimental and integral parts of decentralized ecosystems.

