AI Agents Workflow

In order to ensure the efficient operation of the AI Agents network, the AI Agents in the AIX ecosystem adopt an intelligent task scheduling + adaptive optimization working mechanism to achieve intelligent decision-making in a series of Web3 scenarios such as automatic task execution, market data analysis, user demand matching, and cross-chain data interaction .

Data collection

· AI Agents obtain dynamic information about the Web3 ecosystem through on-chain data, market conditions, social media analysis, and user behavior patterns .

· Combined with oracle technology (Oracle) , AI performs data analysis, market forecasting, and asset monitoring to form a high-precision analysis model.

Intelligent Decision Making

· AI combines machine learning algorithms to analyze market conditions, adjust strategies, and execute optimal decisions, such as automatic trading, intelligent risk control, liquidity management, and user identity authentication .

· AI performs real-time trend forecasting , such as predicting NFT price changes, optimizing DePIN computing resources, and adjusting DAO governance proposals .

Automatic execution

· AI automatically completes tasks through smart contracts, such as data storage, identity authentication, on-chain asset scheduling, and cross-chain transaction matching .

· AI is combined with cross-chain bridges to execute multi-chain asset transfers, optimize transaction paths, and improve the asset circulation efficiency of the Web3 ecosystem.

Adaptive Optimization

· AI Agents use deep learning to analyze historical data and execution results, continuously optimize algorithms, and improve execution accuracy.

· AI combines blockchain storage to intelligently allocate computing power , ensuring optimal allocation of computing resources in the AIX ecosystem and improving overall computing efficiency.