Key Components of INFINIT
1. INFINIT Agent Swarm
The INFINIT Agent Swarm is the foundational infrastructure consisting of 28+ specialized DeFi agents where each agent is specialized in a specific DeFi protocol or task and handles all interactions related to that protocol.
The infrastructure intelligently selects the optimal agent(s) for each task, sequences them into coordinated workflows, and enables multiple specialized agents to collaborate in real-time to handle real-time user queries and execute complex multi-step strategies that would be impossible for any single agent alone.
These agents collaborate through advanced agentic design patterns. The specialized nature ensures deep protocol expertise; For example, when a user interacts with Aave lending strategies, the dedicated Aave agent manages those operations with complete protocol knowledge.
Agent Collaboration Structure:
Protocol-specific agents for individual DeFi protocols
Each DeFi protocol-specific agent is specialized in certain tasks
Coordinated agent swarm for sophisticated DeFi strategies
Real-time communication and data feed between agents
This distributed approach enables automated sequential processing of sophisticated strategies. After one agent analyzes optimal yield opportunities on Aave, another then deposits and purchases PT tokens on Pendle, then a third deposits and opens a short position on Hyperliquid.
Cross-Chain Execution Capabilities
INFINIT's specialized agent swarm coordinates operations across multiple blockchain networks through intelligent agent selection and automated bridging mechanisms. When executing cross-chain strategies, agents coordinate to route transactions seamlessly between networks. Each agent handles protocol interactions on their respective networks with a bridge agent that manages cross-chain strategies.
This distributed coordination eliminates manual chain switching and complex bridging procedures, creating a unified execution flow across all networks.
Supported Networks:
Ethereum
BNB Smart Chain
Solana
Arbitrum
Base
Optimism
Mantle
Sonic
Berachain
Monad
Plasma
2. Agentic Design Patterns
INFINIT agents collaborate using four key thinking frameworks that enable sophisticated coordination and continuous improvement across the entire ecosystem:
Multi-Agent Collaboration
Multi-Agent Collaboration enables specialized agents to share data and coordinate actions seamlessly through structured communication protocols. When executing complex cross-protocol strategies, agents establish execution dependencies and resource sharing agreements.
The collaboration architecture works through:
Each agent maintains domain expertise (lending, trading, bridging, etc.)
Dynamic agent selection based on strategy requirements
Real-time contextual data sharing between agents
Coordinated timing for multi-step transaction sequences
This ensures that a leveraged yield farming strategy requiring Aave lending/borrowing, Pendle swapping PT Tokens, and Hyperliquid depositing and opening a short/long position executes as a single coordinated operation rather than three independent transactions.
These patterns form the operational intelligence that transforms individual specialized agents into a cohesive execution network.
Self-Reflection
Self-Reflection allows agents to continuously review their performance and utilize feedback loops to improve accuracy over time. Each agent maintains execution history, outcome tracking, and performance metrics that feed back into decision-making algorithms.
The self-reflection cycle includes:
External data validation against current market conditions
User feedback integration for accuracy improvements
Predictive guidance based on interaction history
Saved prompts for recurring user workflows
Adaptive intelligence that evolves with user behavior
Agentic RAG
Agentic RAG enables agents to pull clean on-chain and off-chain data from INFINIT Data Stream for precise, context-aware decisions to complete complex tasks with the latest and relevant information.
The agentic RAG capabilities include:
Real-time protocol state retrieval
Social sources and expert opinion integration
Opportunity prioritization through multi-source validation
Cross-chain liquidity and opportunity assessment
User-specific portfolio analysis
This approach allows agents to include current market states as contextual factors in recommendations in addition to user context, ensuring strategy suggestions reflect real-time protocol conditions, liquidity availability, and yield opportunities.
ReAct Agent
ReAct Reasoning provides step-by-step reasoning and action coordination for personalized DeFi execution through automated sequential processing. Agents decompose any strategy, whether requiring 10 steps for simple yield farming or 50 steps for complex multi-protocol leverage operations, into granular execution sequences that they reason through systematically.
The framework operates through iterative reasoning cycles where agents evaluate each step's prerequisites, execute the action, then reason about the next step based on actual outcomes.
Despite the automated reasoning, users are rest assured that they make decisions at critical strategy points while agents handle all technical execution steps.
3. Dynamic Multi-Large Language Model Integration (LLM)
INFINIT's Multi-LLM integration serves as the intelligent bridge between users and the AI Agent infrastructure. The system dynamically leverages multiple LLMs, automatically routing queries to the best model based on task complexity, query type, and contextual requirements for maximum accuracy and efficiency.
The integration translates natural language prompts into three core capabilities that power the entire platform.
Intent Recognition analyzes user financial goals, risk tolerance, and portfolio composition from conversational context to suggest appropriate strategies and risk parameters. This enables personalized recommendations that match individual investment objectives.
Context Preservation maintains conversation history for adaptive responses, enabling users to refine strategies iteratively without starting from scratch. Build complex strategies through progressive conversation rather than single interactions.
Deterministic Code Generation assists in translating user intent into selecting and configuring DeFi strategy components, with transparent step-by-step breakdowns showing exactly what will execute. This ensures reliable outcomes while maintaining natural language accessibility.
This Multi-LLM architecture eliminates traditional barriers between DeFi expertise and execution. Simply describe investment goals in plain English, and the system translates users’ intent into precise, executable actions while maintaining complete transparency about fund interactions.
4. INFINIT Data Stream
The INFINIT Data Stream retrieves comprehensive on-chain and off-chain data from 100+ sources, and refines it before feeding it to DeFi agents for real-time, accurate insights and strategy optimization across multiple chains and protocols.
Comprehensive Data Sources:
On-Chain Data: Protocol states, yield rates, wallet data, and liquidity metrics across supported networks
Off-Chain Data: Protocol documentation, social signals from community discussions, market analytics, and expert insights
Advanced Data Processing: Real-time aggregation across multiple chains and protocols
The data is processed through sophisticated filtering and validation algorithms to eliminate noise, verify accuracy, and standardize information before delivering it to AI agents. This ensures agents access the latest, accurate, and reliable information for precise strategy recommendations.
This data infrastructure powers both INFINIT Intelligence's personalized discovery and INFINIT Strategies' optimized execution, ensuring users get current, relevant opportunities while agents coordinate based on the most accurate available information.
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