Chainbase: Hyperdata-driven Web3+AI Trusted Data Collaborative Infrastructure

In the integration of Web3 and AI, data collaboration is always constrained by the contradiction of 'trustworthiness' and 'efficiency': cross-chain data is difficult to trace, AI adaptation logic is opaque, and value distribution is hard to verify, with trust costs accounting for over 35% of development investment. Chainbase, centered on the Hyperdata Network, builds a 'trusted + efficient' collaborative infrastructure, with all discussions based on publicly available project data.

Its core consists of a three-layer trusted architecture: data collection end, achieving traceability of data from 200+ chains (such as Ethereum, Base, etc.) through hash evidence + distributed nodes (requiring staking of $C), with a verification accuracy rate of ≥99.99% and latency ≤100ms; AI adaptation end, with feature hashing and processes fully on-chain, combined with Chainlink off-chain data, making model decision bases verifiable; value distribution end, with contribution rights confirmation + smart contract profit sharing, profit sharing delay ≤10 seconds, and dispute rate reduced to below 0.5%.

In terms of ecosystem, the Manuscript tool lowers the barrier, serving over 20,000 developers and integrating with over 8,000 projects; in-depth cooperation with Base and Coinbase, with 60% of AI projects in the Base ecosystem relying on its data. In the market, $C has a 24-hour trading volume exceeding $47 million on Binance, with a price range of $0.2130-$0.2925, and an FDV of $187 million - $282 million, which is reasonably valued.

The core barrier of Chainbase is embedding 'trustworthiness' into the entire collaborative link, providing trust infrastructure for Web3+AI, not just a simple tool, meeting the industry's strong demand for trusted data, with long-term value in becoming a standard for collaborative trust. @Chainbase Official #Chainbase