The deep bottleneck in the integration of Web3 and AI is not the lack of data tools, but rather the absence of programmable capabilities for data value collaboration—cross-chain data lacks a unified programmable interaction standard, requiring redundant development of collaborative logic, increasing development costs by 45%; raw on-chain data lacks programmable interfaces for AI adaptation, with 70% of feature engineering needing to be completed offline manually; data value distribution lacks a decentralized programmable mechanism, with profit settlement delays exceeding 72 hours, and centralized platforms intercepting over 60% of the added value. Chainbase does not stop at the level of 'data aggregation tools', but instead builds a three-layer collaborative system of 'programmable access - programmable adaptation - programmable profit distribution' centered around the Hyperdata Network, fundamentally addressing the structural issues of 'collaboration difficulties, adaptation difficulties, and profit distribution difficulties'. All analyses are based on the project's publicly available technical white papers, ecosystem reports, and on-chain verifiable data, with no fictitious content.
I. Technical Core: The Programmable Collaborative Architecture of Hyperdata
The core innovation of Chainbase is upgrading Web3 data collaboration from 'static tool stitching' to 'dynamic programmable protocols' through Hyperdata, with each layer of architecture defining clear programmable specifications, achieving the 'codification, automation, and decentralization' of data value collaboration:
1. Programmable data access: The 'codified lane' for cross-chain collaboration
Hyperdata achieves standardized programmable access to over 200 chains (including Ethereum, BNB Chain, Sui, Base, etc.) through 'dynamic programmable node networks + lightweight access contracts (LAC)', solving the cross-chain collaboration problem of 'no unified code interface':
• Dynamic programmable node network: Nodes obtain data validation permissions by deploying $C staking contracts, with collaborative logic written onto the chain in the form of smart contracts (supporting Solidity/Move). Node scaling can be automatically triggered based on on-chain data volume (with peak node count exceeding 5000), ensuring cross-chain data synchronization latency of ≤100ms and data validation accuracy of ≥99.9%; malicious nodes will have their stakes automatically confiscated by the contract, requiring no human intervention, ensuring decentralized trust in collaboration.
• Lightweight access contracts: For small to medium chains and Layer 2 solutions like Scroll and Aptos, there is no need to modify their underlying code; deploying standardized access contracts alone can complete the programmability of data interfaces, shortening the average industry connection cycle from 30 days to 7 days, and reducing access code volume by 60%. By Q4 2024, Hyperdata has cumulatively processed over 500 billion programmable cross-chain calls. Through the 'Homogeneous Data Indexing Contract (HDIC)', developers can call multi-chain homogeneous data with one line of code (e.g., the same user's cross-chain assets), improving query efficiency by 90% without needing to repeatedly write cross-chain interaction logic.
2. Programmable AI adaptation: The 'codified interface' for data-AI collaboration
Hyperdata comes with built-in 'AI Feature Programmable Generation Contracts (AFGC)', which codifies and automates AI adaptation logic, filling the 'programmable gap' between data and AI:
• Real-time programmable feature generation: Feature extraction logic is codified in the form of contracts, automatically triggering feature generation after data access (e.g., conditions like 'cross-chain asset holding duration > 30 days' and 'contract interaction frequency > 10 times' can be dynamically adjusted through contract parameters), generating standardized feature vectors compatible with TensorFlow and PyTorch, allowing AI developers to skip writing feature engineering code, improving adaptation efficiency by 400%;
• Scenario-based programmable templates: For high-frequency scenarios such as DeFi risk control and NFT valuation, predefined feature combination contract templates (e.g., 'cross-chain asset volatility coefficient × Chainlink security score') allow developers to call them simply by modifying template parameters, reducing the model training cycle from 15 days to 2 days.
In addition, Hyperdata and Chainlink Scale achieve programmable integration through 'On-chain + Off-chain Data Fusion Contracts (ODFC)', allowing off-chain data such as macroeconomic indicators and asset safety ratings to be automatically integrated into the feature generation process via contracts. This improves the bad debt rate prediction accuracy of DeFi risk control models from 82% to 98%, and optimization logic can be upgraded through contracts for automated iteration.
II. Ecosystem Landing: Tools and Scenario Validation for Programmable Collaboration
The ecological value of Chainbase lies in transforming Hyperdata's programmable capabilities into tools that developers can directly reuse while expanding collaborative scenarios through programmable integration with leading ecosystems. All data comes from the project's publicly available ecosystem reports:
1. Manuscript Programmable Toolchain: The 'low-code entry' for collaborative capabilities
To lower the threshold for developers, Chainbase has launched the Manuscript toolkit (including a GUI programmable configuration platform and CLI contract generation tool), which encapsulates Hyperdata's programmable collaborative logic into low-code components:
• Visual programmable configuration: Developers can generate a complete collaborative process of 'cross-chain data access - AI feature generation' by dragging and dropping components, with tools automatically converting the configuration logic into smart contract code (supporting Solidity/Move), eliminating the need to manually write cross-chain interaction and feature processing scripts, enhancing development efficiency by 60%;
• Contract-based debugging and monitoring: Built-in on-chain contract debugging panel allows real-time viewing of the execution status of collaborative contracts (e.g., data access progress, feature generation logs). Abnormal situations can trigger automatic rollback of the contract, reducing issue identification time from 24 hours to 10 minutes.
Currently, Manuscript has served over 20,000 developers, with 40% focused on AI-driven Web3 application development; over 12,000 programmable collaborative contracts deployed through this tool cover three core scenarios: DeFi (35%, such as cross-chain lending risk control contracts), NFT (28%, such as asset valuation contracts), and AI infrastructure (22%, such as on-chain behavior analysis contracts).
2. Programmable Integration of Leading Ecosystems: The 'codified expansion' of collaborative scenarios
The collaboration between Chainbase and leading ecosystems is not just a superficial functional integration, but rather embeds the programmable collaborative capabilities of Hyperdata into the underlying ecosystem contracts, achieving the code-based collaboration of 'data-application':
• Programmable integration of Base ecosystem's OP Stack: As the officially recommended data collaboration protocol for Base, Hyperdata's access contract and feature generation contract have been integrated into the underlying OP Stack of Base, allowing Base ecosystem developers to directly use cross-chain collaboration capabilities by calling built-in contracts in the OP Stack; currently, 60% of AI projects in the Base ecosystem (such as cross-chain asset monitoring tools and on-chain credit assessment platforms) are developed based on this integration, with the frequency of data collaboration accounting for 28% of the total data demand in the Base ecosystem, and the collaborative logic can be upgraded through OP Stack contracts for automated iteration;
• Programmable profit-sharing integration of Coinbase CDP wallet: As one of the first data partners for Coinbase's embedded wallet (CDP), Hyperdata's profit-sharing contract has been integrated with the CDP user system. Once users authorize on-chain data, the profits generated from data collaboration can be distributed to user wallets in real-time through profit-sharing contracts (in $C). The profit-sharing ratio and settlement cycles can be dynamically adjusted through contract parameters without human intervention. Currently, this integration is in the testing phase, with plans for formal launch in Q2 2025.
III. Value Mechanism: Programmable Economic Design of the $C Token
The core of data programmable collaboration is the 'programmable allocation of value'. Chainbase constructs a decentralized programmable profit-sharing system using the $C token, with all rules codified through smart contracts, leaving no room for centralized intervention. Relevant parameters come from project white papers and smart contract audit reports:
• Programmable codification of token distribution: The total supply of C is 1 billion tokens, with the TGE (Token Generation Event) completed in July 2025. The distribution ratio is permanently codified through the genesis contract: 65% for ecosystem programmable incentives (40% allocated to developers through integration contracts, 12% rewarded to verification nodes through node contracts, 13% distributed to users through airdrop contracts), and 35% for long-term development (17% allocated to early investors through locked contracts, linear unlocking over 3 years; 15% allocated to core members through team contracts, linear unlocking over 3 years; 3% deployed to Binance/Uniswap through liquidity contracts). Any distribution adjustments require a proposal vote via the C governance contract to ensure decentralization;
• Programmable execution of profit sharing: Data collaborative profit sharing is automatically executed through 'profit sharing contracts': Each time a node completes a cross-chain collaboration, the contract automatically issues basic C rewards; when data is called by AI, the contract automatically calculates the profit-sharing ratio based on the calling scenario parameters (e.g., financial risk control scenario coefficient of 2.5, regular query scenario coefficient of 1) and real-time distributes it to the node and developer wallets; 5% of the API call fee (paid in C) is permanently destroyed through a destruction contract, with destruction records verifiable on-chain in real time. As the scale of collaboration expands (with API calls expected to exceed 1 trillion by 2026), the scarcity of $C continues to increase;
• Objective verification of market performance: $C has been listed on major exchanges such as Binance, MEXC, and Bithumb, with the C/USDT trading pair on Binance being the core liquidity pool, maintaining a 24-hour trading volume of over $47 million, accounting for 60% of the total trading volume of $C. The current price range of $C is $0.2130-$0.2925, down about 55% from its historical peak price ($0.5445) on July 18, 2025. The fully diluted valuation (FDV) is $187 million-$282 million, lower than similar programmable data projects (like The Graph with FDV around $1.2 billion), with a reasonable match between valuation and collaborative capabilities.
IV. Future Evolution: Expansion of Programmable Collaboration Boundaries and Industry Standards
Based on Chainbase's public roadmap, its long-term development focuses on 'expanding the boundaries of programmable collaborative capabilities', with all goals derived from existing technological foundations and ecosystem scales, with no fictitious plans:
1. Programmable collaboration of global data: Integrating data sources from vertical fields such as the Internet of Things (IoT), supply chain logistics, and government compliance through 'Cross-Domain Programmable Access Contracts (CDAC)', achieving unified programmable collaboration of 'on-chain + off-chain' data; simultaneously introducing ZKML (Zero-Knowledge Machine Learning) technology, developing 'Privacy-Preserving Programmable Contracts (PPPC)', enabling AI adaptation collaboration in sensitive areas such as healthcare and finance while ensuring data privacy. The plan is to support over 50 types of data sources by 2026, with collaboration latency reduced to within 50ms;
2. Programmable sovereignty of C-end data: Launching 'Personal Data Programmable Collaborative Contracts (PDCC)', allowing users to self-define the scope of data authorization through contracts (e.g., 'only open trading trends for the last 30 days, not open specific amounts'), with authorization logic codified on-chain. Data collaborative profits are distributed in real-time to user wallets through contracts; simultaneously developing a 'Data Sovereignty Management DApp', allowing users to view collaboration records in real-time and adjust authorization parameters. The goal is to reach 10 million C-end users by 2026, forming a closed loop of 'personal data - programmable collaboration - AI services - profit feedback';
3. Establishing industry programmable standards: In collaboration with the Ethereum Foundation, Base team, Chainlink, and leading AI companies (such as Anthropic), we will publish the (Web3+AI Data Programmable Collaborative Industry Specification), defining technical standards and contract templates for programmable access, programmable adaptation, and programmable profit distribution, shifting the DataFi track from 'tool competition' to 'programmable capability competition', with a goal of completing 2 trillion programmable collaborative calls by 2027, becoming the largest decentralized data programmable collaborative platform globally.
Summary: Programmable collaboration is the core barrier of Chainbase
The competitiveness of Chainbase does not stem from 'data aggregation' or 'AI tools', but from making Web3 data value collaboration 'programmable' through Hyperdata—codifying cross-chain collaborative logic, automating AI adaptation processes, and decentralizing value distribution mechanisms, fundamentally addressing structural contradictions in the industry. Its barriers are reflected in three aspects:
1. Technical barriers: Hyperdata's three-layer programmable protocol defines the code standards for data collaboration. Subsequent projects must be compatible with this protocol to access the ecosystem, forming a 'path dependency';
2. Ecological barriers: Over 20,000 developers and more than 8,000 integrated projects built on the programmable toolchain, with programmable integrations in leading ecosystems like Base and Coinbase expanding collaborative scenarios;
3. Economic barriers: The programmable profit-sharing mechanism of $C ensures the long-term benefits of ecosystem participants, avoiding value interception by centralized platforms.
Although $C is currently in a price correction cycle, combining the growth prospects of the Web3+AI industry (with the market size expected to exceed $10 billion by 2025), Chainbase's first-mover advantage in the programmable collaboration field, and a reasonable valuation of $187 million to $282 million, its long-term value lies in becoming the industry standard for Web3+AI data value programmable collaboration, rather than merely a data tool—this is the core logic that distinguishes it from similar projects and is also the key foundation supporting its long-term development.
