Chainbase takes an application-first approach, emphasizing live, shareable data for dashboards, DAOs, and AI tools. Early users are putting it to work in three main areas:
1. Real-time DeFi primitives — Teams building DeFi dashboards are leveraging Chainbase for live TVL feeds, per-block APR recalculations, and hedging signals that require sub-minute accuracy. By querying Chainbase directly, they avoid the “stale data” issues that often plague analytics platforms.
2. Compliance & research — Compliance teams and VCs use Chainbase for address histories, cluster graphs, and streaming P&L tracking for on-chain portfolios. The structured data outputs make audits, back-tests, and KYC/AML checks much easier—without needing a ton of custom engineering.
3. AI & autonomous workflows — Chainbase positions itself as a “data layer for AI.” By delivering normalized, machine-ready datasets and real-time streams, it enables agents to make decisions using fresh on-chain signals—whether that’s portfolio rebalancing, avoiding liquidations, or market-making. Its Hyperdata Network and SDKs highlight this focus.
On the operations side, Chainbase supports streaming outputs to common enterprise stores like S3, Postgres, and Snowflake. This lets teams combine on-chain data with off-chain datasets for hybrid models, while also simplifying compliance and historical tracking without running costly node infrastructure.
In short: for any project that depends on timely, accurate, and cross-chain data, Chainbase takes care of the heavy lifting—indexing, normalization, and streaming—so teams can move faster and focus on building.
