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  • About Minos
  • Minos SDK
    • Core functions
      • Core functions: Trade
      • Core functions: Vaults
    • Websocket
    • CLI: Sandbox strategy testing
  • Multi-Agent Orchestration
    • Agents
      • Data Collection Agent
      • Analytical Agent
      • Strategy Development Agent
      • Trade Implementation Agent
      • Performance Monitoring Agent
    • OpenAI Swarm and Langchain
  • Terminal: On-chain tasks execution
  • Autonomous trading agents
    • Ariadne: Autonomous Trade Scanner
    • Deucalion: Advanced Copy Trading
    • Androgeus: Rule-Based Trade Executor
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  • DevOps
    • Servers and GPU Infrastructure
    • Retrieval-Augmented Generation (RAG) Operations
      • Iterative Retrieval-Generation
      • Embedding Models
    • Conversational History Management
    • Agent Monitoring & Performance Analytics
  • Telegram terminal
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Minos AI 2025

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  1. DevOps

Retrieval-Augmented Generation (RAG) Operations

Minos RAG pipeline powers scalable data retrieval for trading insights, using a distributed TimescaleDB infrastructure across multiple regions. This setup enabled us High Availability ensuring uninterrupted access to market data and historical trends and Optimized Query Performance supporting the Market Data Agent’s <50 ms ingestion speeds.

Integrated with PostgreSQL, TimescaleDB enables automated document embeddings for real-time indexing of scraped data, advanced reranking prioritizing high-value trading signals for the Portfolio Manager Agent and In-Database LLM Queries executing complex analytics, like cross-asset correlations, within the database.

Our RAG pipeline enhances data retrieval efficiency, reducing query times by 40% and boosting trade precision by 8–10%.

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Last updated 5 days ago