Technical Architecture
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The mid-stage system adopts a modular multi-agent architecture coordinated by a central Orchestrator Agent.
Orchestrator Agent:
Coordinates all AI agents
Routes tasks and merges signals
Ensures coherent end-to-end processing
Supports plug-and-play integration of new agent modules
Includes the following agents:
Social-Media Processing Agent
News Processing Agent
Historical Market Data Agent
Smart-Money Analysis Agent
These agents collect raw data from:
Twitter/X
News sources (e.g., Bloomberg)
Market APIs
Smart-money flows
Responsible for:
Aggregating multi-source data
Cleaning and normalizing features
Temporally aligning inputs
Producing a unified, model-ready representation
Uses time-series and probabilistic models (e.g., LSTM-style or Transformer-based architectures) selected based on data availability and task requirements.
Generates probability forecasts and risk-neutral fair-value estimates
Operates on the unified feature space
Includes:
Quantitative Strategy Agent
Market Sentiment Agent
Output Synthesis Agent
This module converts model outputs into interpretable, strategy-ready insights.
Safety & Governance Agent:
Enforces system rules
Applies safety constraints
Ensures compliant behavior across agents and decision flows
Tracks system performance
Manages periodic retraining
Exposes system outputs via APIs for integration and automation
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