Trade

Problem Statement

Project OverviewReal-World Data Marketplace for AI Agentsis a full-stack decentralized marketplace that enables secure, token-gated trading of AI training data. The platform combines blockchain technology, decentralized storage, and AI agents to create a comprehensive ecosystem for data monetization and access control.Core Problem & SolutionProblem: AI companies struggle to access high-quality training data due to:Data silos and lack of standardizationTrust issues between data providers and consumersNo secure way to monetize valuable datasetsDifficulty verifying data quality and provenanceSolution: A decentralized marketplace that:Tokenizes datasets as ERC-721 NFTs (DataCoins)Uses Lighthouse for encrypted, token-gated storageImplements AI agents for discovery, negotiation, and validationProvides transparent provenance tracking via BlockscoutTechnical Architecture🏗️ System Components1. Frontend (Next.js)React-based marketplace interfaceWallet integration with wagmi/RainbowKitReal-time chat with AI agentsTransaction verification and provenance display2. Smart Contracts (Solidity)DataCoin.sol: ERC-721 NFT representing data ownershipMarketplace.sol: Atomic swap marketplace with royaltiesToken-gated access controlValidator attestation system3. Backend API (Express.js)Lighthouse integration for file storageMCP adapter for Blockscout queriesAgent orchestration endpointsTransaction logging and monitoring4. AI Agents (Fetch.ai Integration)Seller Agent: Handles dataset upload, minting, and listingBuyer Agent: Discovers datasets and facilitates purchasesValidator Agent: Performs quality checks and creates attestationsMeTTa Knowledge Graph: Stores structured metadata5. Storage & VerificationLighthouse: Encrypted file storage with access controlBlockscout: Transaction verification and provenance tracking1MB.io: DataCoin tokenization platformKey Features🔐 Token-Gated Access ControlDatasets are encrypted and stored on LighthouseOnly token holders can decrypt and access dataGranular permissions based on NFT ownershipAutomatic access revocation on token transfer🤖 AI Agent EcosystemDiscovery: AI agents help users find relevant datasetsNegotiation: Automated price negotiation between buyers and sellersValidation: Quality assessment and schema verificationAttestation: On-chain recording of validation results📊 Provenance TrackingComplete transaction history on BlockscoutValidator signatures and attestationsQuality scores and metadataTransparent ownership transfers💰 Economic ModelRoyalties: 2.5% to original data creatorsPlatform Fees: 1% to marketplace operatorsAtomic Swaps: Secure peer-to-peer transactionsBulk Discounts: Negotiated pricing for large purchasesWorkflow ExamplesDataset Upload & MonetizationUpload: Data provider uploads dataset to LighthouseEncrypt: File is encrypted with access controlMint: DataCoin NFT is created via 1MB.ioList: Token is listed on marketplace with pricingStore: Metadata is stored in MeTTa knowledge graphDataset Discovery & PurchaseQuery: User asks AI agent to find specific datasetsSearch: Agent queries MeTTa knowledge graphRecommend: Agent provides ranked recommendationsVerify: User can verify provenance via BlockscoutPurchase: Atomic swap transfers token and paymentAccess: Token holder can decrypt and download dataQuality ValidationDownload: Validator agent retrieves datasetIntegrity: Hash verification and corruption checksSchema: Data format and structure validationQuality: ML-based quality assessmentAttestation: Results recorded on-chain with signatureTechnology StackBlockchain & Web3Ethereum/Polygon Mumbai: Smart contract deploymentERC-721: NFT standard for data tokensEthers.js: Blockchain interactionWagmi: React hooks for Web3Storage & IPFSLighthouse: Encrypted file storageIPFS: Decentralized file systemAccess Control Lists: Token-gated permissionsAI & AgentsFetch.ai: Agent frameworkASI:One: Chat interface integrationMeTTa: Knowledge graph for metadataPython/Node.js: Agent implementationsFrontend & BackendNext.js: React frameworkTypeScript: Type-safe developmentTailwind CSS: Styling frameworkExpress.js: Backend API serverInnovation & Uniqueness🔬 Technical InnovationToken-Gated Encryption: First implementation of NFT-based data access controlAI Agent Integration: Automated discovery, negotiation, and validationProvenance Transparency: Complete audit trail on blockchainQuality Attestation: On-chain validation records🎯 Market ImpactData Democratization: Makes valuable datasets accessibleCreator Economy: Enables data monetization for researchersQuality Assurance: Automated validation and verificationTrust & Transparency: Blockchain-based provenance tracking🚀 ScalabilityModular Architecture: Easy to extend with new featuresAgent Ecosystem: Pluggable AI agents for different use casesCross-Chain Ready: Designed for multi-chain deploymentAPI-First: Comprehensive API for third-party integrationsUse CasesFor Data ProvidersMonetize valuable datasetsMaintain control over data accessTrack usage and attributionReceive royalties on resalesFor Data ConsumersAccess high-quality training dataVerify data provenance and qualityNegotiate fair pricingEnsure data authenticityFor ValidatorsEarn rewards for quality assessmentBuild reputation in the ecosystemContribute to data standardsParticipate in governanceFuture RoadmapPhase 1: Core MarketplaceBasic buy/sell functionalityToken-gated access controlAI agent integrationProvenance trackingPhase 2: Advanced FeaturesAutomated quality validationPrice discovery mechanismsBulk trading capabilitiesCross-chain supportPhase 3: Ecosystem GrowthThird-party agent developmentAPI marketplaceGovernance tokenDecentralized autonomous organization (DAO)This project represents a significant step forward in creating a truly decentralized, AI-powered data marketplace that addresses the fundamental challenges of data access, quality, and monetization in the AI industry.

Solution

Real-World Data Marketplace for AI Agents🏗️ Architecture OverviewThis project is a complex full-stack application that integrates multiple cutting-edge technologies to create a seamless data marketplace experience. Here's how we built it:🛠️ Technology Stack & IntegrationFrontend: Next.js + Web3 Integration// Wagmi configuration for Web3 connectivity const config = createConfig({ chains: [polygonMumbai], ssr: true, transports: { [polygonMumbai.id]: http(rpcUrl), }, });Key Implementation Details:Next.js 13.5.4with TypeScript for type safetyWagmi v1.4.7+RainbowKitfor wallet connectivityTailwind CSS v4.1.15for modern, responsive designCustom React hooksfor blockchain state managementSmart Contracts: Solidity + OpenZeppelin// DataCoin.sol - ERC-721 with custom functionality contract DataCoin is ERC721, Ownable, ReentrancyGuard { mapping(uint256 => string) public tokenCID; mapping(uint256 => address) public tokenSeller; mapping(uint256 => uint256) public tokenPrice; function mintDataCoin(address to, string calldata cid) external onlyOwner returns(uint256) { uint256 id = ++nextId; _safeMint(to, id); tokenCID[id] = cid; tokenSeller[id] = to; emit DataCoinMinted(id, to, cid); return id; } }Notable Features:ERC-721 NFTsrepresenting data ownershipAtomic swap marketplacewith built-in royalties (2.5% to creators, 1% platform fee)Reentrancy protectionfor secure transactionsToken-gated access controlvia Lighthouse integrationBackend: Express.js + Multi-Service Integration// MCP Adapter for Blockscout integration router.post('/query', async (req, res) => { const { queryType, target, params = {} } = req.body; switch (queryType) { case 'transaction': response = await simulateTransactionQuery(target, params); break; case 'contract': response = await simulateContractQuery(target, params); break; // ... more query types } });Backend Architecture:Express.jswith TypeScript for API serverModular route structure(lighthouse, mcp-adapter, mint)Comprehensive loggingsystem for MCP callsError handlingwith detailed error responses🔗 Partner Technology Integration1. Lighthouse Storage Integration// Token-gated access control setup const acl = { conditions: [ { id: 1, chain: 80001, // Mumbai testnet method: "balanceOf", standardContractType: "ERC721", contractAddress: contractAddress, returnValueTest: { comparator: ">", value: "0" }, parameters: [":userAddress", tokenId] } ], operator: "and" };Lighthouse Benefits:Encrypted file storagewith IPFS backendToken-gated access controlusing ERC-721 ownershipAccess control liststhat verify NFT ownershipDecentralized storagewithout single points of failure2. Blockscout Integration// Blockscout SDK integration for transaction verification export async function getTx(txHash: string): Promise<TransactionData> { const response = await simulateBlockscoutCall('transaction', txHash); return { hash: txHash, blockNumber: response.blockNumber, from: response.from, to: response.to, explorerUrl: `${BLOCKSCOUT_BASE_URL}/tx/${txHash}` }; }Blockscout Benefits:Transaction verificationand provenance trackingContract interactionmonitoringReal-time transactionstatus updatesExplorer integrationfor user transparency3. Fetch.ai Agent Integration// Buyer Agent - Dataset discovery and recommendation class BuyerAgent { async processQuery(userQuery, userAddress) { const intent = await this.analyzeIntent(userQuery); const datasets = await this.searchDatasets(intent); const recommendations = await this.evaluateDatasets(datasets, intent); return this.generateResponse(recommendations, intent); } }Fetch.ai Benefits:Intelligent dataset discoveryusing natural language processingAutomated price negotiationbetween buyers and sellersQuality assessmentand validation workflowsMeTTa knowledge graphfor structured metadata storage🧠 AI Agent ArchitectureMulti-Agent System Design// Seller Agent - Handles dataset upload and minting async processDataset(datasetPath, metadata) { const uploadResult = await this.uploadToLighthouse(datasetPath, metadata); const aclResult = await this.setupAccessControl(uploadResult.cid, metadata); const mintResult = await this.mintDataCoin(uploadResult.cid, metadata); const listingResult = await this.createListing(mintResult, metadata); await this.storeInMetta(mintResult, metadata); }Agent Responsibilities:Seller Agent: Upload → Encrypt → Mint → List → Store metadataBuyer Agent: Discover → Evaluate → Recommend → Facilitate purchaseValidator Agent: Download → Validate → Attest → Record on-chainMeTTa Knowledge Graph Integration# Python integration for MeTTa knowledge graph class MettaClient: def store_dataset(self, dataset: Dict[str, Any]) -> bool: response = self.session.post(f"{self.endpoint}/store", json=dataset) return response.status_code == 200 def query_datasets(self, **filters) -> List[Dict[str, Any]]: response = self.session.post(f"{self.endpoint}/search", json=filters) return response.json().get('datasets', [])🔧 Particularly Hacky Solutions1. Token-Gated Decryption Simulation// Simulated access control for demo purposes router.post('/check-access', async (req, res) => { const { cid, userAddress } = req.body; // Hacky demo logic: allow access if address ends with even hex const lastChar = userAddress.trim().toLowerCase().slice(-1); const evenHex = ['0','2','4','6','8','a','c','e']; const hasAccess = evenHex.includes(lastChar); res.json({ hasAccess }); });Why This Works:Demo-friendlyaccess control for testingDeterministicbased on wallet addressEasy to testwithout complex token verificationProduction-readystructure for real implementation2. Mock Data Generation for Agents// Generate realistic mock datasets for agent responses getMockDatasets(intent) { const mockDatasets = [ { id: 1, name: 'Computer Vision Dataset', description: '50,000 labeled images for object detection', category: 'Computer Vision', price: '0.1', size: '2.5GB', format: 'Images', verified: true, cid: 'QmSampleImageDataset123', tokenId: 1 } // ... more datasets ]; }Benefits:Realistic demo datafor agent responsesConsistent user experienceduring developmentEasy to customizefor different scenariosFallback mechanismwhen external APIs fail3. Blockscout Simulation Layer// Simulate Blockscout API calls for demo purposes async function simulateBlockscoutCall(type: string, identifier: string): Promise<any> { await new Promise(resolve => setTimeout(resolve, 500)); // Simulate API delay if (type === 'transaction') { return { blockNumber: Math.floor(Math.random() * 1000000), from: '0x' + Math.random().toString(16).substring(2, 42), to: '0x' + Math.random().toString(16).substring(2, 42), status: 'success', confirmations: Math.floor(Math.random() * 100) }; } }Why This Approach:No external dependenciesduring developmentConsistent demo experienceregardless of network conditionsRealistic datathat matches expected API responsesEasy to replacewith real API calls in production🚀 Deployment & CI/CDGitHub Actions Pipeline# Multi-service deployment pipeline jobs: frontend: runs-on: ubuntu-latest steps: - name: Build frontend run: cd frontend && npm run build - name: Upload build artifacts uses: actions/upload-artifact@v3 with: name: frontend-build path: frontend/.next/Pipeline Features:Parallel buildsfor frontend, backend, and contractsArtifact managementfor deploymentSecurity auditsacross all servicesPerformance testingand monitoringAutomatic deploymentto VercelEnvironment Configuration# Comprehensive environment setup RPC_URL_MUMBAI=https://polygon-mumbai.g.alchemy.com/v2/YOUR_ALCHEMY_KEY LIGHTHOUSE_API_KEY=your_lighthouse_api_key BLOCKSCOUT_MCP_URL=https://your-mcp-endpoint.com NEXT_PUBLIC_BLOCKSCOUT_INSTANCE_URL=https://your-autoscout-instance.blockscout.com🔍 Notable Technical Decisions1. TypeScript EverywhereFrontend: Next.js with TypeScriptBackend: Express.js with TypeScriptContracts: Solidity with comprehensive type safetyAgents: Node.js with TypeScript2. Modular ArchitectureSeparate servicesfor different concernsAPI-first designfor easy integrationPluggable agentsfor extensibilityMicroservice-readystructure3. Comprehensive Logging// MCP call logging for debugging and monitoring const logMCPCall = (request: any, response: any) => { const logEntry = { timestamp: new Date().toISOString(), request, response, duration: Date.now() - request.startTime }; const logPath = path.join(__dirname, '../../logs/mcp.log'); fs.appendFileSync(logPath, JSON.stringify(logEntry) + '\n'); };4. Error Handling & ResilienceGraceful degradationwhen external services failComprehensive error loggingfor debuggingFallback mechanismsfor demo purposesUser-friendly error messages🎯 Production ReadinessSecurity ConsiderationsReentrancy protectionin smart contractsAccess controlfor sensitive operationsInput validationacross all APIsSecure key managementfor external servicesScalability DesignStateless backendfor horizontal scalingDatabase-agnosticarchitectureCaching strategiesfor performanceCDN integrationfor static assets