Ava the portfolio manager

🤖 Ava the Portfolio Manager AI Agents

Multiple specialized autonomous AI agents with powerful tools work together to analyze, recommend, and execute optimal DeFi strategies while maintaining user-defined risk parameters and portfolio goals currently live on Avalanche , Mode , Base, powered by Brian AI and LangChain

Portfolio Validation Service with Neo4j and AI

A knowledge graph-based portfolio validation service that combines Neo4j with AI models through the Modus framework. This service enables intelligent portfolio analysis by storing portfolio data in a graph structure and using AI for validation.

🎯 Problem Statement Managing DeFi portfolios across multiple protocols on Avalanche can be complex and time-consuming.

Users need to:

• Monitor multiple positions across different protocols
• Execute complex multi-step transactions
• Stay updated with the latest crosschain yield opportunities
• Maintain desired portfolio allocations
• React quickly to market changes

💡 Solution An autonomous AI agent that manages your Avalanche DeFi portfolio by:

• Understanding high-level goals in natural language
• Breaking down complex operations into executable steps
• Automatically executing transactions when needed
• Providing real-time updates and progress tracking
• Maintaining portfolio balance according to user preferences

Features

• Graph-Based Portfolio Storage: Store portfolios and tokens as interconnected nodes in Neo4j
• AI-Powered Validation: Use GPT-4 to analyze portfolios and generate validations
• Historical Validation Tracking: Store all validations in the graph with timestamps
• GraphQL API: Easy-to-use GraphQL interface for all operations

🌟 Key Features of the AI Agents

1. Natural Language Interface

• Express portfolio goals in plain English
• No need to understand complex DeFi terminology
• AI translates intentions into actions

2. Autonomous Execution

• Breaks down complex goals into steps
• Executes transactions automatically
• Handles error recovery
• Provides progress updates

3. Portfolio Management

• Multi-protocol position monitoring
• Yield optimization
• Risk management
• Rebalancing capabilities

4. Real-time Updates

• Live execution status
• Progress tracking
• Transaction confirmations
• Performance metrics

Architecture

graph TB
    subgraph Frontend
        UI[Web Interface]
    end

    subgraph ModusAPI[Modus API Layer]
        GQL[GraphQL Endpoint]
        PF[Portfolio Functions]
    end

    subgraph AI[AI Services]
        GPT[GPT-4 Model]
    end

    subgraph KnowledgeGraph[Neo4j Knowledge Graph]
        P[Portfolio Nodes]
        T[Token Nodes]
        V[Validation Nodes]
        R1[CONTAINS Relations]
        R2[HAS_VALIDATION Relations]
    end

    UI --> GQL
    GQL --> PF
    PF --> KnowledgeGraph
    PF --> AI
    P --> R1
    R1 --> T
    P --> R2
    R2 --> V

Built With

• ai-model
• dgraph
• hypermode
• modus
• neo4j