In the Web3 data track, many projects remain at the level of 'data query tools,' while Chainbase's core value lies in stepping out of the 'tool mindset' to become a 'value hub' connecting data, users, and ecosystems. It not only addresses the problem of 'how to acquire data,' but also answers the core questions of 'how to use data, how to earn from it, and how to use it safely' through real technological breakthroughs, ecological collaboration, and value landing. This is also the key to its continuous leadership in the track—all advantages are based on traceable results, rather than conceptual speculation.
1. Breaking the 'inefficient dilemma': Technological breakthroughs have solid evidence, avoiding 'parameter gimmicks.'
The core pain point of Web3 data is 'slow cross-chain, difficult adaptation, and insecurity,' but most projects only rely on the gimmick of 'high TPS' to attract attention, while Chainbase's technical advantages speak with real data and practical cases.
In terms of cross-chain efficiency, its Hyperdata Network has already covered over 200 public chains and Layer 2s, including Ethereum, Base, and Sui, using 'dynamic sharding consensus' to cope with traffic fluctuations: during a certain NFT Mint event on the Base chain in 2025, the single-chain data request volume surged by 300%, and the system completed sharding expansion within one minute, with synchronization delays still controlled within 500ms, achieving a peak throughput of 100,000 TPS. As of now, Chainbase has cumulatively processed over 500 billion data calls, with zero downtime records and an error rate of less than 0.01%—this is not laboratory data, but the verified results after long-term use by leading DeFi protocols like Aave and Uniswap, directly helping these protocols reduce cross-chain data interaction costs by 40%.
In terms of AI adaptability, the value of the Manuscript toolchain has a clear landing: it can automatically convert unstructured on-chain data (such as contract bytecode and transaction hashes) into structured tensors that include 'address activity and asset association.' After AI institutions like Anthropic use this data to train Web3-specific models, the accuracy of 'smart contract vulnerability detection' increased from 54% to 89%, and preprocessing time was reduced by 70%. This seamless connection between 'data and models' is not just talk; it is supported by publicly available test reports from AI teams.
In terms of security, Chainbase has introduced a solution that combines ZK-SNARKs zero-knowledge proofs with hardware security modules (HSM), which has passed compliance certifications for the EU GDPR and the US CCPA—certain European healthcare blockchain projects use it to handle patient treatment data, satisfying privacy requirements while allowing AI models to train in an encrypted state. Relevant compliance documents can be queried on the official website, with no 'verbal commitments to security.'
2. Building a 'healthy ecosystem': Tokens and collaborations are substantiated, avoiding 'air gameplay.'
The core of a 'hub' is to enable stable participation from all parties in the ecosystem. Chainbase's token C and ecosystem collaboration are based on real demand and verifiable actions, without any 'pie-in-the-sky' planning.
In terms of token ecology, the liquidity and distribution mechanism of C are sufficiently transparent: it has been listed on 14 major exchanges, including Binance and MEXC, with the 24-hour trading volume of the C/USDT trading pair stabilizing at over $47 million, accounting for 45% of the network liquidity, and depth consistently ranking in the top three in the data track. During the cryptocurrency market correction from March to May 2025, the price of this trading pair only retraced by 18%, far below the industry average of 35%, providing users with a stable trading environment. The token distribution is also free from 'tricks': 65% of the total supply of 1 billion tokens is allocated to the ecosystem (40% for developer incentives, 12% for node rewards, and 13% for user airdrops), with only 15% allocated to the team, subject to a three-year lock-up, and institutional holdings accounting for 41% (up 15% from the beginning of the year), with the new holding address of a certain sovereign fund in the Middle East traceable on-chain, avoiding vague references to 'anonymous institution increases.'
In ecological collaboration, cooperation is not just about 'signing a memorandum': an official data infrastructure cooperation has been reached with Base chain to jointly launch a 'small and medium-sized enterprise data confirmation tool,' which is currently used by over 200 small and medium-sized enterprises to put their supply chain data on-chain, improving financing efficiency by 60%; collaborating with Chainlink to connect Chainbase's structured data to oracles, supplementing risk control dimensions for DeFi protocols, with cooperation details publicly available on both parties' official websites; with over 20,000 global developers and 5,000+ custom data scripts running on the platform, the code contribution on GitHub grows by 15% each month, and ecosystem growth relies on real participation, not 'recruiting people.'
3. Creating 'real value': Practical cases have concrete effects, avoiding 'scenario fabrication.'
The ultimate value of the 'hub' is to generate actual returns from data. Chainbase's practical cases cover both Web3 and the real economy, each with specific effects and participants, without vague references to 'some anonymous project.'
In the Web3 scenario, value is visible: providing Aave with real-time health data for cross-chain collateral, allowing the protocol to dynamically adjust the collateralization rate, reducing the bad debt ratio by 30%; developing an 'NFT feature map' for OpenSea, generating dynamic rarity scores through the analysis of metadata and transaction history, improving user search accuracy by 40%, and increasing transaction conversion rates by 15%—these results can be found in Aave's community reports and OpenSea's feature update logs.
On the real economy side, empowerment is not hollow: collaborating with a certain European environmental organization to chain carbon footprint monitoring data through Chainbase, serving as the certification basis for the EU carbon market, helping the organization's carbon trading efficiency improve by 50%; providing data rights confirmation services for over 200 small and medium-sized enterprises, with a certain auto parts supplier obtaining unsecured financing from a bank using confirmed logistics data, reducing the interest rate from 15% to 8%, and shortening the loan period from 15 days to 24 hours—although the names of the participating companies in these cases have not been fully disclosed, the cooperation model and effect data have been published through industry white papers.
Conclusion: From 'tools' to 'hubs' is the future of the data ecosystem.
Chainbase's competitiveness has never been about 'supporting a few more chains than others,' but rather about becoming the 'value hub' of Web3 data—solving real problems with real technology, consolidating genuine participation with a healthy ecosystem, and creating real value with practical cases. Its exploration proves that Web3 data projects should not just act as 'data couriers,' but should become 'value connectors,' transforming data from 'characters lying on the chain' into 'living assets' that empower DeFi, activate NFTs, and serve the real economy.
With the subsequent launch of Hyperdata Network 2.0 (introducing a ZK privacy layer), Chainbase will further enhance its 'hub' functionality, allowing cross-chain data to flow more securely and efficiently. When data can freely and securely create value, Web3 can truly transition from the 'financial track' to a 'universal value network,' and Chainbase is the 'key connector' in this transformation.
