👷How it works?

Features and actions of the Maiga AI agent

Maiga.ai redefines what it means to trade, earn, stake, and profit, in the era of Web3.0 and #DeFAI.

How Maiga AI works?

Maiga AI agent creation:

• Process: AI agents are created using Maiga’s native token, $MAIGA. This token acts as the foundation for activating and owning these agents.

  • Example: A user might spend $MAIGA to create an agent specialized in monitoring and trading DeFi assets. Once created, the AI agent is ready to receive tasks and training for personalized use cases.

  • Technical Insight: The creation process initializes a connection between the AI agent and Maiga’s shared knowledge base, equipping with default libraries and capabilities.

AI Agent Paths:

• Description: These are pre-built guides or roadmaps that help Maiga AI agents navigate blockchain networks efficiently.

  • Example: If an AI agent needs to perform a cross-chain token swap, it will use a specific path that outlines the necessary steps, including locating a bridge, ensuring liquidity, and completing the transaction.

  • Technical Insight: These memories are maintained as part of a graph database, where nodes represent specific blockchain operations (e.g., smart contracts, DEXs). AI agents query the graph to identify optimal routes for task execution, reducing computational costs and errors.

Reinforced Learnings:

• Description: AI agents can learn from past interactions, improving their decision-making and task efficiency over time.

  • Example: An AI agent trading agent might recognize patterns in market behavior and adjust its strategies to maximize returns based on previous successes and failures.

  • Technical Insight: Memory systems categorize experiences into short-term (active tasks), long-term (cumulative knowledge), and pinned memories (key learnings). This architecture ensures agents adapt and refine their actions based on evolving conditions.

  • Advanced Training: Users can further enhance agents by providing domain-specific data, such as financial reports or specialized tutorials. This tailored training enables agents to specialize in tasks like market analysis, sentiment analysis or more.

MPC Wallet Management:

• Description: AI agents come equipped with digital wallets, enabling them to securely store, trade, and manage blockchain assets.

  • Example: An AI agent might manage an EVM wallet, autonomously transferring funds to a staking protocol while ensuring compliance with user-defined conditions.

  • Technical Insight: Maiga’s platform leverages Multi-Party Computation (MPC) wallet architecture. This ensures private keys are never fully exposed, adding an abstraction layer for enhanced security.

    • Custom Wallets: Users can import dedicated wallets to their agents for specific purposes. For instance, a wallet can be assigned to an AI agent managing DeFi strategies while isolating other funds.

    • Abstraction Benefits: By abstracting wallet management, agents can interact seamlessly across blockchains without compromising security. This abstraction also allows for smoother cross-chain operations, aligning with Maiga’s interoperability goals.