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Component Abstraction Diagram

Abstract representation of how AI-tizate is architected conceptually within a cluster. This diagram avoids naming specific technologies and focuses on the logical components and responsibilities that form the foundation of the system.

Description of Components​

  • Users & Service Accounts: Human or automated actors requesting access to language models or AI services.
  • Access Control: Centralized gatekeeper that validates identity and applies role-based permissions.
  • Model Proxies: Unified interface layer to interact with multiple AI models while applying control rules.
  • Language Models (A, B, etc.): Abstract representation of local or remote AI models (LLMs).
  • Budget & Quota Controller: Component that applies usage limits, tracks consumption, and ensures budget adherence.
  • Security Layer: Handles encryption, audit logs, and policy validation to enforce privacy and compliance.
  • Observability & Reporting: Aggregates logs, metrics, and usage data for transparent monitoring.
  • Model Configuration Planner (MCP): Intelligent agent that reads system/data/API context and proposes or automates deployment logic.

This architecture is designed to enable fast, secure, and manageable scaling of AI-powered capabilities inside any organization, while maintaining transparency, control, and operational trust.