All-in-One Sports Trading AI ModelMonthly returns over 30%
AI-powered intelligent sports analysis and trading system, covering major global betting platforms
Partnership & Funding
Largest AI Agent infra on SUI/BSC/BTC
DeAgentAI empowers AI Agents to think, agree, and remember—just like humans, but better.
Decentralized AI Governance
DeAgent Framework
DeAgentAI introduces DeAgent, a distributed decision-making framework that ensures AI Agents operate with consensus, identity, and continuity, fostering trust in autonomous AI governance.
Verifiable & Transparent Execution
Executor & Committer
The Executor & Committer mechanism guarantees that AI-driven decisions are executed transparently and verified on-chain, preventing manipulation and ensuring accountability.
Persistent AI Memory
Memory Modules
With Memory Modules, DeAgentAI empowers AI Agents with long-term recall and contextual awareness, ensuring decisions are informed by historical interactions.
AI-Powered DAOs & Collaboration
Decentralized Organizations
DeAgentAI enables AI Agents to participate in Decentralized Autonomous Organizations (DAOs), allowing AI and humans to co-govern and make collective decisions in a decentralized environment.
Interoperable & Modular Design
Web3 Integration
DeAgentAI supports seamless integration with smart contracts, DeFi protocols, and other Web3 infrastructures, making it highly adaptable to diverse decentralized applications.
Scalable & Autonomous AI Economy
AI-Driven Automation
By leveraging decentralized execution and AI-driven automation, DeAgentAI fosters a scalable AI economy, where intelligent agents perform autonomous tasks with minimal human intervention.
Why Decentralized AI Fails Today
Consensus:
The "Multiple Personality" Dilemma
AI Agents, unlike traditional nodes, can produce different results on different devices due to small computational variances. This creates challenges in reaching consensus when decisions are not deterministic.
Identity:
Split Decision-Maker
AI Agents may give contradictory answers to the same question, disrupting consistency. Ensuring decision traceability and output consistency is key to maintaining agent reliability.
Continuity:
Agent Without Memory
AI Agents face limitations in state persistence and context management, which prevent knowledge accumulation across sessions. A lack of memory can disrupt decision continuity and consistency.
How to Deploy Trustworthy AI Agents
AI Agents That Work for Humans, Not Against Them.
DeAgent
Distributed System
DeAgent Modular Layer 2 Network
The DeAgent Core
DeAgent's foundation combines Lobe, Memory, and Tools. A Developer configures these modules to deliver flexible, adaptive intelligence capable of handling a wide range of tasks.
Interaction & Distribution
Users connect through the Agent Interface, with a Selector routing requests to the right models or tools. Meanwhile, a Distributed System underpins the entire process, ensuring robust, scalable performance across multiple nodes and environments.
Consensus & Tokenization
Execution requests pass through a Screening Mechanism, Executor Nodes, and Validators, all secured by a Hybrid POS/POW model. A Memory NFT logs final results, and a Token Incentive Economic Model rewards participants.
