# Technical Architecture

The mid-stage system adopts a modular multi-agent architecture coordinated by a central Orchestrator Agent.

### Orchestrator Module

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

## **Data Ingestion & Processing Module**

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

### Preprocessing Module

Responsible for:

* Aggregating multi-source data
* Cleaning and normalizing features
* Temporally aligning inputs
* Producing a unified, model-ready representation

### Prediction Model Module

* 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

### Strategy & Interpretation Module

Includes:

* Quantitative Strategy Agent
* Market Sentiment Agent
* Output Synthesis Agent

This module converts model outputs into interpretable, strategy-ready insights.

### Safety & Governance Module

Safety & Governance Agent:

* Enforces system rules
* Applies safety constraints
* Ensures compliant behavior across agents and decision flows

### Monitoring & Deployment Module

* Tracks system performance
* Manages periodic retraining
* Exposes system outputs via APIs for integration and automation