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AI & Machine Learning Overview

Overview

Add a brief overview of this document here.

Table of Contents

Introduction

Anya Core's AI/ML capabilities provide advanced features for blockchain analytics, security monitoring, and system intelligence. This document provides an overview of the AI/ML components and their integration points within the Anya Core ecosystem.

Core Components

1. ML System Architecture

The ML system follows a hexagonal architecture pattern with clearly defined inputs, outputs, and domain logic. Key components include:

  • Agent Checker System: Monitors and verifies system health and readiness
  • Data Processing Pipeline: Handles data ingestion, transformation, and feature extraction
  • Model Serving: Provides real-time inference capabilities
  • Training Framework: Supports model training and fine-tuning

2. Model Types

  • Bitcoin Analytics: Transaction pattern recognition, anomaly detection
  • Security Monitoring: Threat detection, intrusion prevention
  • System Intelligence: Performance optimization, resource management

3. Integration Points

  • Blockchain Layer: Direct integration with Bitcoin protocol
  • API Layer: REST and gRPC interfaces for model serving
  • Monitoring: Real-time metrics and alerting

Key Features

  • Real-time Processing: Low-latency inference for time-sensitive operations
  • Scalability: Horizontal and vertical scaling support
  • Security: Built-in security measures for AI/ML components
  • Compliance: Adherence to regulatory requirements
  • Extensibility: Plugin architecture for custom models and algorithms

Getting Help

For more detailed information, refer to the following documents:

Support

For support, please open an issue in the GitHub repository.

See Also