Haotian | CryptoInsight
Haotian | CryptoInsight|Jul 19, 2025 03:29
Previously, @ ChainbaseHQ, which had received exclusive investment from Tencent and had been working on the full chain AI data infrared track for a long time, recently completed TGE and achieved a triple jump in Binance Alpha, contract, and spot in just a few days. Its Staking Reward APY also performed exceptionally well. So, from a technical perspective, how should we view Chainbase? 1) Traditional web3 data infrastructure faces three challenges: low willingness to pay on the demand side, high supply side costs, and severe product homogenization. Everyone is working on data indexing and API services, but with only so many users and such a large market, it is difficult for everyone to achieve internal competition in the end. The breakthrough point of Chainbase is that it did not continue to compete in the existing market, but targeted the incremental market of AI+Crypto. The pain point is simple: if you want an AI agent to perform on chain decision analysis, you need to first convert various formats of blockchain data into a standard format that AI can understand. This demand is truly essential, and the market space is large enough. 2) Think about it, currently AI agents need to retrieve raw data from various chains before cleaning and standardizing it in order to call on on chain data for decision analysis. The complexity and cost of this process are not suitable for large-scale applications. In response to this pain point, Chainbase has designed a four layer architecture, specifically: The data access layer is responsible for efficient aggregation of multi chain data and supports real-time data calls from multiple blockchain networks; The data integrity layer utilizes distributed ledger technology and encryption algorithms to ensure data security and immutability; The data format standard layer is the core innovation, which achieves unified standardization of cross chain data through the Manuscript Protocol; The native AI layer on the chain directly integrates AI technology into the blockchain network, outputting AI compatible smart contracts and data analysis services. Among them, the manuscript protocol is considered a technological innovation point, equivalent to a programmable "AI translator" that can convert raw blockchain data into standardized and AI compatible formats in real time. In addition, it has designed a "novel dual chain technology architecture" to achieve high performance and high security. At first glance, a four layer architecture may sound complex, but its core lies in solving three problems: how to aggregate data, how to standardize it, and how to make AI work. The CometBFT consensus layer and EigenLayer AVS execution layer actually achieve high throughput and instant finality, and enhance security through double staking (C+ETH LST). above. To be honest, Chainbase's combination of punches is indeed quite complex in terms of technical complexity, because AI applications have high requirements for real-time, accuracy, and standardization of data, which traditional data services cannot meet. It also requires a long time of operation and challenge to complete the aggregation and matching. From a business perspective, Chainbase's timing is also good. Tencent exclusively led a $15 million Series A investment, which is the only AI data project Tencent has invested in the Web3 field. This endorsement carries significant weight. More importantly, the hard indicators of 500 billion data calls, 20000 developers, and 8000 projects prove that the demand is also real. Overall, Chainbase's new positioning is no longer aimed at traditional data query services, but at data infrastructure service providers in the AI era. This positioning transformation can not only revive the traditional data service track, but also explore a sustainable commercialization path for the track with its newly defined concept of DataFi.
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