Trendence.ai
  • Introduction
    • The AI Fragmentation Problem
    • Core Problems
    • What is Trendence?
  • Vision and Mission
    • Vision
    • Mission
  • Trendence Solution
    • Trendence Solution
  • System Architecture
    • Architecture Approach
    • Application Layer
    • Orchestration Layer
    • Data Layer
    • Execution Layer
  • Terminal
    • Agent Categories
    • Modes
    • Evaluation & Ranking
  • Developer Ecosystem
    • Integration via API/SDK
    • Contribution Mechanisms
    • Quality Control System
  • Token Utility ($TREND)
    • $TREND
  • Business Model
    • Subscription Tiers
    • API/Data Licensing Revenue
    • Agent Monetization Split
  • Governance
    • DAO Governance
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  1. System Architecture

Orchestration Layer

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Last updated 2 months ago

The core logic responsible for coordination, task decomposition, and result integration.

  • Mastermind Engine: Divides initial prompt into logical subqueries via NLP tools and LLMs. Then based on key-words, semantic search and scoring selects most suitable agents to process each subquery and routes them to selected Agents.

  • Aggregation Module: Merges outputs from multiple agents into a single coherent response, eliminating contradictions and data-noise.

  • Evaluation Module: Once each agent produces response including aggregation module, Evaluation module provides assessment of selected agents and quality of response to provided prompt and tags.

  • Learning module: Collects the complex feedback from external and internal ecosystem elements, users and modules, forming the comprehensive historical experience database for AI-modules further development. Increasing quality of agent selection based on user prompts and agents specialization.

Modules interaction system
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