Datrix

Problem Statement

The Web3 Data Access Problem:Web3 developers and data analysts face several significant challenges when trying to access and analyse cross-protocol blockchain data:Discovery Complexity -Must manually search through hundreds of subgraphs -No standardised way to find the most reliable data sources -Different versions of protocols across multiple chains -Time spent researching instead of buildingIntegration Overhead -Each protocol has unique schema structures -Need to write custom queries for each subgraph -Different naming conventions across protocols -Manual mapping required between different data formatsMaintenance BurdenSubgraphs get updated or deprecatedProtocols deploy to new chainsSchema changes break existing integrationsConstant monitoring neededTechnical RequirementsDeep knowledge of GraphQL requiredUnderstanding of each protocol's data structureExpertise in data transformationCross-chain data aggregation complexityThis impacts time to market for apps, risk of using outdated or unreliable data sourcesThe solution - Datrix: An intelligent system that autonomously curates and combines web3 data sources based on natural language requests. This agent-based platform simplifies access to cross-chain data by automatically analysing user requirements and orchestrating relevant subgraph combinations from The Graph protocol.🤖 Key Features-Natural language processing for web3 data requirements with semantic understanding -Autonomous data source discovery and combination with reliability scoring -Multi-chain data integration with automatic schema mapping -Dynamic subgraph selection and orchestration with version control -Real-time data aggregation capabilities -Custom API endpoint generation💡 How It WorksUsers describe their data needs in plain EnglishAI agent analyzes the request and identifies required data pointsSystem automatically discovers and evaluates relevant subgraphsData sources are combined to create a unified datasetResults are delivered in a ready-to-use format🎯 Perfect For-DeFi developers needing multi-chain data -Data analysts working with web3 metrics -AI/ML practitioners building web3-powered applications -Researchers requiring comprehensive blockchain data -Protocol teams tracking ecosystem metrics -Market analysts requiring cross-protocol insights🔑 Key Benefits-Reduces integration time by 90% -Eliminates manual subgraph discovery and maintenance -Ensures data reliability through automated validation -Handles cross-chain data consistency automatically

Solution

🛠 Tech Stack -AI-powered request analysis using Coinbase agent kit -The Graph Protocol integration for subgraph discovery and querying -Deployed on a TEE environment using Autonme -Multi-chain data aggregation -Autonomous agent architectureOur project automatically finds the best subgraph by identifying user requirements and doing a similarity search on all the existing subgraphs, then finds all the needed entities on each subgraph schema and stores all the queries needed with the transformations on a database, when a user requests data, retrieves all the queries, send then to the subgraphs, and merge and transforms the data needed to return it ready to consume to the user.