Recently, Datai Network and Coreon MCP have declared a strategic alliance that would make the data on blockchain more practical when used by AI agents. The partnership combines the structured high-frequency blockchain data streams of Datai and the multi-step ToolCall implementation of Coreon.
🤝 CoreonMCP x Datai Network
We’re thrilled to announce our partnership with @datainetwork.
This collaboration takes us closer to unlocking real-time, AI-native Web3 intelligence for our community.@datainetwork delivers structured, high-frequency blockchain data streams,… pic.twitter.com/NSA6tsCLNm— Coreon (@CoreonMCP) September 12, 2025
This yields a network which offers cleaner context, higher ingestion rate, and more actionable intelligence to developers creating autonomous code in Web3.
What Datai Delivers
Datai is the firm that deals with converting raw blockchain activity into structured signals that can be consumed by AI systems.
Rather than raw logs and the generated noisy event dumps, Datai produces normalized data streams that capture the transactional trends, event associations and timing indicators.
The structure will lead to a reduction in preprocessing efforts and allow AI models to study market movement, token flows, and protocol events more precisely. Having predictable temporal integrity-based feeds can also enable developers to create monitoring dashboards, alerting systems and predictive agents more easily.
What Coreon Brings
Coreon is interested in agent workflows that are based on tools. Its multi-step ToolCall platform coordinates the sequence of function invocations enabling agents to package external APIs, smart contract interactions, and logic of decision making.
With high-frequency data stream integration into Datai, Coreon agents are able to execute more context-aware behaviour and respond to on-chain changes with very low latency. This combination performs intrinsic activities like identifying liquidity events, evaluation of possible risks, and defensive trades/notifications.
Coreon focuses on reproducibility and traceability and makes sure that automated interventions are efficient and able to be audited.
Why This Matters for Web3 AI
This team aims to solve two long-standing issues with Web3 AI: signal quality and tool execution. The AI agents need quality and timely data input in addition to effective orchestration to act on the findings.
To an extent, Datai and Coreon implement a feedback loop where improved signals yield smarter behavior and the behavior, in turn, yields improved information to be improved. In the case of an ecosystem that relies more on composable AI agents, this loop is critical in terms of safety as well as performance.
Early Use Cases and Future Outlook
The applications that may be made include financial and developer ecosystems. In the near future, plug-and-play agent templates based on Datai and Coreon integrations might be made available to the developers, which will decrease the costs and will simplify the process of engineering.
Going forward, the partnership is a major move by both companies to enable an increasingly robust AI x Web3 infrastructure, which is expected to transform autonomous agents to achieve faster, safer, and more reliable autonomy.
