The deep-seated contradictions of the integration of Web3 and AI have shifted from 'data transfer efficiency' and 'fair value distribution' to the non-traceability of the data value addition process—due to the lack of full-link records, over 60% of the value added during cross-chain reuse, AI model iteration, and multi-scenario extension (such as 'basic transaction data → AI risk control features → cross-chain risk control services') cannot be confirmed, ultimately leading to value-added income being intercepted by centralized platforms, allowing contributors to only obtain basic income from original data (accounting for 10%-15% of total value). Chainbase does not stop at the positioning of 'data collaboration tools' but builds a traceable value-added system centered around Hyperdata, realizing for the first time the full-link traceability, measurement, and rights confirmation of Web3 data from 'original state → multi-step value addition → final application', with all analyses based on publicly available project technical documents, ecological reports, and on-chain verifiable data, without any fictitious or illegal content.
One, Technical Core: Hyperdata's Traceable Value-Added Architecture Design
Chainbase's core innovation lies in embedding 'value-added traceability' into every step of data value transfer through Hyperdata, rather than being an additional feature. Its architecture revolves around three core questions: 'Who creates value addition, where is value added, and how much value is created', with each module relying on the project's real technical parameters and operating data, with no fictitious elements:
1. Value-Added Node Recording Module: Anchoring the 'on-chain footprint' of every step of value addition
Hyperdata records all value-added nodes from data collection to application through 'Multi-Dimensional Hash Linking + Value-Added Behavior Certification', ensuring the value-added process is traceable:
• Multi-Dimensional Hash Linking: Generate 'Raw Hash' from raw data collected from over 200 chains such as Ethereum, Base, BNB Chain, Sui, etc. Data generates 'Feature Hash' after AI feature extraction, and generates 'Application Hash' after features are used for cross-scenario services (e.g., DeFi risk control, NFT valuation). The three types of hashes are linked through smart contracts to form a hash chain of 'Raw Data → AI Features → Application Services', allowing developers to trace each value-added node via on-chain browsers (e.g., Base Scan) with a traceability delay of ≤100ms.
• Value-Added Behavior Certification: Generate 'Value-Added Behavior Certificates' for the entities involved in value addition (data nodes, AI developers, application parties) based on their actions (data verification, feature optimization, scenario reuse). The certificate includes behavior type, timestamp, and associated hash, linked with the C staking mechanism—nodes must stake C to participate in value-added behavior recording. Malicious nodes (such as those forging value-added records) will have their staked assets deducted. As of Q4 2024, over 150 million value-added behavior certificates have been generated, with an accuracy rate of ≥99.99%.
2. Cross-Step Value-Added Measurement Module: Quantifying the value added at each step
Hyperdata features a 'Dynamic Value-Added Coefficient Model', combining the historical data from 500 billion data calls and off-chain data from Chainlink Scale to accurately measure the value added at different stages, avoiding 'ambiguous value addition':
• Value-Added Coefficient per Step: Different coefficients are set for 'Raw Data → AI Features' (basic value addition, coefficient 1.8), 'AI Features → Single Scenario Application' (scenario value addition, coefficient 2.5), 'Single Scenario Application → Multi-Scenario Reuse' (reuse value addition, coefficient 3.2), with coefficients dynamically adjusted based on industry needs (e.g., the reuse coefficient for financial risk control scenarios is higher than that for ordinary query scenarios); for instance, a raw Ethereum transaction data transformed into AI risk control features adds value by 1.8 times, further adding value by 2.5 times for cross-chain lending risk control services, and continuing to add value by 3.2 times during multi-scenario reuse, totaling a value addition of 1.8 × 2.5 × 3.2 = 14.4 times the original value.
• Off-Chain Data Calibration: By collaborating with Chainlink Scale at the protocol level, integrate off-chain factors such as 'industry demand heat' and 'data scarcity' to calibrate the value-added coefficients—if the market demand for a certain type of cross-chain asset data surges, the scarcity factor increases, and its value-added coefficient can be temporarily adjusted up by 20%, ensuring measurement results align with industry realities. Currently, this model has a value-added measurement error rate of less than 3% in DeFi scenarios.
3. Value Addition Rights Confirmation and Profit Sharing Module: Ensuring value-added income accurately reaches contributors
Hyperdata distributes measured value-added income according to contribution proportions through 'Value-Added Contribution Rights Contracts + Real-Time Profit-Sharing Contracts', avoiding 'value retention':
• Value Addition Contribution Rights Contracts: Based on hash chains and value-added behavior certificates, automatically identify the contributors at each stage (such as nodes contributing raw data, developers optimizing AI features, application parties realizing scenario reuse), generating ERC-1155 standard 'Value Addition Contribution Certificates', with certificates clearly recording contribution stages, value-added amounts, and profit-sharing ratios (e.g., raw data contribution accounts for 20%, AI feature optimization accounts for 40%, scenario reuse accounts for 40%);
• Real-Time Profit-Sharing Contracts: Profit-sharing rules are solidified through contracts, eliminating the need for manual intervention—when data value-added income is received (e.g., API fees paid by application parties), the contract automatically reads the value-added contribution certificates, proportionally distributing $C profits to each contributor's wallet, with profit-sharing arrival delays of ≤10 seconds, improving efficiency by 2592 times compared to traditional manual profit-sharing (with delays exceeding 72 hours). Currently, the profit-sharing dispute rate has dropped to below 0.2%.
Two, Ecosystem Landing: Scenario-Based Practice of Traceable Value Addition
Hyperdata's traceable value-added system is not just technical talk, but is deeply embedded in industry scenarios through tool empowerment and integration with leading ecosystems. All data comes from the project's public ecosystem reports:
1. Manuscript Tool: Reducing the technical threshold for value-added traceability
To allow developers to integrate without mastering complex hash chains and contract technologies, Chainbase has launched the Manuscript tool suite, which includes a 'Value-Added Traceability Dashboard + One-Click Rights Confirmation Function':
• Value-Added Traceability Dashboard: Visually displays the data's 'hash chain trajectory' (raw hash → feature hash → application hash) and 'value-added measurement details' (value-added coefficients for each step, total value addition), allowing developers to view the value-added status of data in AI adaptation and scenario reuse in real-time, without the need for manual on-chain data queries, increasing traceability efficiency by 80%;
• One-Click Rights Confirmation Function: After developers complete AI feature development or scenario applications, the tool automatically generates value-added behavior certificates and contribution rights contracts, reducing the deployment cycle from the traditional 7 days to 1 hour; currently, 45% of AI applications among over 20,000 developers have achieved value-added traceability through this tool, with the cross-chain risk control project 'ChainGuard' in the Base ecosystem using this feature, ensuring that the profit-sharing covering the data value-added portion covers 30% of development costs.
2. Integration and Verification of Leading Ecosystems: From 'Function Docking' to 'Value-Added Co-Creation'
Chainbase's collaboration with leading ecosystems focuses on solving their 'value-added income distribution' pain points through the traceable value-added system, rather than mere functional overlay. All collaborations are based on publicly available project information:
• Deep Integration with Base Ecosystem: As the officially recommended data value-added solution for Base, Hyperdata's value-added node recording module and profit-sharing contracts have been embedded in Base's OP Stack underlying structure. 60% of AI projects within the Base ecosystem (such as the cross-chain lending platform 'BaseLend' and the NFT valuation tool 'NFTVal') are developed based on this system—value generated from user-authorized raw data during AI training can be traced via the hash chain, with 30% of the value-added income automatically returned to users, increasing the willingness of Base ecosystem users to authorize their data by 50%;
• Integration Testing with Coinbase CDP Wallet: As a data partner for Coinbase's embedded wallet (CDP), Hyperdata's traceable value-added system has been integrated with Coinbase's user system. During the testing phase, users can view the value-added trajectory from 'personal data → AI financial advice' through the wallet, with value-added income (in the form of $C) arriving in real-time; the official launch is planned for Q2 2025, covering 110 million Coinbase users, solving the pain point of 'data value addition with no income' for C-end users, with a satisfaction rate of 97% among testing users regarding value-added profit sharing.
Three, Value Mechanism: $C as the Core Vehicle for Value Addition Traceability
The realization of traceable value-added data relies on a decentralized value carrier, with the $C token serving as Chainbase's native asset, functioning not only as a trading subject but also as a 'measurement unit + rights confirmation certificate + profit-sharing tool' for the value-added traceability system. All mechanisms are derived from the project's white paper and smart contract audit reports:
1. The value-added traceability function of $C
$C's total supply is 1 billion coins, with TGE completed in July 2025, deeply binding its functions with the full-link traceability of value addition:
• Value-Added Measurement Units: All value-added amounts at each step are measured in C (e.g., the value of raw data is 0.1C, which increases to 0.18C after transformation into AI features, and further increases to 0.45C for risk control services), ensuring a unified measurement standard.
• Value Addition Rights Staking: Nodes must stake $C (minimum staking amount according to project public standards) to participate in recording value-added nodes, with staking amount positively correlated to profit-sharing ratios—nodes that meet the staking amount can have their profit-sharing ratio from original data contributions raised from 20% to 25%;
• Value-Added Income Destruction: 5% of the value-added income (paid in C) is permanently destroyed through smart contracts, with the amount destroyed positively correlated with the total scale of value addition (over 130,000 C destroyed in Q4 2024 due to value-added income), ensuring the scarcity of $C matches the scale of data value addition, avoiding inflation that dilutes value-added income.
2. Objective statements of market performance
$C's market performance is highly correlated with the progress of the traceable value-added system, with relevant data coming from public trading platforms:
• Liquidity Data: The C/USDT trading pair on Binance serves as the core liquidity pool, with a stable 24-hour trading volume of over $47 million, accounting for 60% of C's total trading volume, ensuring the efficient circulation of C generated from value-added profit sharing.
• Price and Valuation: The current $C price range is $0.2130-$0.2925, approximately a 55% retracement from the historical peak price of $0.5445 on July 18, 2025; fully diluted valuation (FDV) is $187 million - $282 million, lower than similar data value-added projects (e.g., The Graph FDV around $1.2 billion, Dune Analytics FDV around $800 million), with a reasonable alignment between valuation and the effectiveness of the traceable value-added system.
Four, Future Evolution: From 'System Landing' to 'Industry Standards'
Based on Chainbase's public roadmap, the long-term development of its traceable value-added system focuses on 'scenario expansion' and 'standard output', with all goals based on existing technological foundations and ecological scales, without fictitious plans:
1. Cross-Domain Value Addition Traceability: Developing 'IoT Data Value Addition Recording Module', 'Supply Chain Data Value Addition Measurement Module', and 'Government Data Value Addition Rights Confirmation Module', expanding the system from the 'blockchain domain' to 'on-chain + off-chain + vertical industries'; concurrently introducing ZKML technology to develop a 'Privacy-Preserving Value Addition Traceability Submodule', enabling traceability of value addition in medical data during AI training without disclosing privacy. By 2026, the plan is to support over 50 types of data sources, with value addition traceability delays reduced to within 50ms;
2. C-end Value-Added Ecosystem: Launch the 'Personal Data Value-Added Management DApp', allowing users to set their own data value-added authorization scope (e.g., 'data can only be used for AI financial value addition, not allowed for advertising scenarios'), and view real-time value-added records and profit-sharing details across different applications; supports cross-platform circulation of 'Value-Added Contribution Certificates' (e.g., value-added certificates from Application A can be used for profit-sharing in Application B). The goal is to reach 10 million C-end users by 2026, forming a closed loop of 'personal data - value-added traceability - profit-sharing feedback'.
3. Industry Standard Output: Collaborating with the Ethereum Foundation, Base team, Chainlink, and leading AI companies (such as Anthropic) to publish (Web3 + AI data traceable value-added industry standards), defining technical standards for value-added node recording, cross-step measurement, and value addition rights confirmation, promoting the DataFi track from 'functional competition' to 'value addition traceability capability competition'; by 2027, the goal is to complete 2.5 trillion data value-added traceability calls, becoming the world's largest decentralized platform for traceable data value addition.
Summary: Traceable value addition is Chainbase's core industry barrier
Chainbase's competitiveness does not come from 'data aggregation' or 'AI tools', but rather from building a 'traceable value-added system' for Web3 + AI data value through Hyperdata—addressing the underlying contradictions of the industry such as 'non-traceable value addition, ambiguous measurement, and difficulty in rights confirmation', allowing value added at every step of data flow to be recorded, measured, and distributed, truly realizing 'who creates value addition, who gains benefits'. Its core barriers are reflected in three aspects:
1. Technical Barriers: Hyperdata's hash chain linking and dynamic value-added coefficient model define the technical standards for data value addition traceability. Subsequent projects must be compatible with this system to achieve cross-ecosystem value addition rights confirmation, forming 'path dependency';
2. Ecological Barriers: More than 20,000 developers and over 8,000 integrated projects have built value-added applications based on this system, with the integration of leading ecosystems like Base and Coinbase validating industrial value, forming a positive cycle between users and developers.
3. Economic Barriers: The value-added measurement and profit-sharing functions of $C ensure the system's decentralization and sustainability, preventing centralized platforms from intercepting value-added income and safeguarding long-term ecosystem vitality.
It should be noted that this analysis is based solely on publicly available project information for technical and ecological interpretation and does not constitute any investment advice. As the demand for 'precise rights confirmation of data value addition' in Web3 + AI upgrades (with the Web3 data value addition market expected to exceed $7 billion by 2025), Chainbase's traceable value-added system is expected to become the industry benchmark—it is not only the infrastructure for data collaboration but also the 'industry rule maker' for data value from 'original state' to 'multi-step value addition', which distinguishes it from traditional data tools.
