Technical Architecture
Technical Architecture
Overview
The AIPaul platform is built on a layered modular architecture designed for scalability, security, decentralization, and extensibility. Each major component operates independently while communicating through standardized, verifiable interfaces.
System Layers
1. Data Aggregation Layer
Collects real-time and historical data across multiple sources.
Integrates sports statistics APIs, decentralized oracle feeds, and social sentiment trackers.
Standardizes data into structured formats for AI preprocessing.
Sample Code: Fetch Data from Sports API (Node.js)
const axios = require('axios');
async function fetchSportsData(matchId) {
const response = await axios.get(`https://api.sportsdata.io/v4/soccer/scores/json/Match/${matchId}`, {
headers: { 'Ocp-Apim-Subscription-Key': 'YOUR_API_KEY' }
});
return response.data;
}2. Prediction Engine Layer
Runs supervised learning models, ensemble algorithms, and time-series forecasters.
Dynamically adapts model parameters based on live updates.
Outputs prediction probabilities and confidence scores.
3. Oracle Submission Layer
Encapsulates prediction outputs into verifiable payloads.
Publishes prediction hashes and metadata onto blockchain smart contracts.
Enables public verification and dispute resolution.
4. Blockchain Smart Contract Layer
Manages prediction storage, staking, governance voting, and reward distribution.
Provides APIs for external dApps to integrate prediction data feeds.
Sample Code: Basic Oracle Contract for Submitting Predictions (Solidity)
5. User Interface Layer (Front-End)
Web application interfaces (React, Next.js) for users to interact with the platform.
Connects via Web3 wallets (e.g., MetaMask, WalletConnect).
Provides dashboards for predictions, staking, and governance voting.
Architectural Highlights
Modularity: Each layer can be independently upgraded without disrupting the entire system.
Security: Critical operations like staking and voting are handled via audited smart contracts.
Transparency: Prediction data, model hashes, and governance votes are fully auditable on-chain.
Developer-Friendly APIs: Public API endpoints allow third-party developers to build on top of AIPaul infrastructure.
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