For AI agents: a documentation index is available at the root level at /llms.txt and /llms-full.txt. Append /llms.txt to any URL for a page-level index, or .md for the markdown version of any page.
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HomeAdministration & GovernanceDevelopment and IntegrationAgent ForgeAPI ReferenceSDK Docs
HomeAdministration & GovernanceDevelopment and IntegrationAgent ForgeAPI ReferenceSDK Docs
  • Getting Started
    • Quick Start
  • Installation
  • Administration
    • Admin Console
    • Create an AI System
    • AI System Management
    • Model Management
    • API Keys
    • Monitoring
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On this page
  • Creating a System
  • Managing a System
  • Deploying a System
Administration

System Management

Create and manage sovereign AI systems in the Admin Console
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Model Management

Deploy and manage private, managed, and external models in your Prediction Guard system
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The Systems page is your central view of all AI systems in your Prediction Guard deployment. From here you can create new systems, monitor their health, and manage their configuration.

Systems Page

Each system card displays:

  • Status: Health state (Healthy, Never Connected, Degraded)
  • API Keys: Number of active API keys
  • Models: Number of deployed models
  • MCP Servers: Number of connected MCP servers
  • Location: Deployment environment (e.g. kubernetes, staging)
  • Last Update / Created: Timestamps for the system

Creating a System

Click Create System in the top-right corner. You’ll be prompted to choose a configuration mode:

Create System - Choose Mode

ModeBest For
Quick StartStandard deployments — simplified setup with sensible defaults
CustomFull infrastructure control, air-gapped environments, or advanced configuration

For Quick Start, provide a System Name and optionally configure a Public API Endpoint for external access. See the Quick Start guide for the full walkthrough.

For Custom configuration, see the Create an AI System guide.

Managing a System

Click Manage on any system card to open its management dashboard.

System Management Dashboard

From the dashboard you can:

  • API Keys: Create and manage API keys for secure access to your system’s endpoints
  • Models: Deploy private, managed, or external models — see Model Management
  • MCP Servers: Configure Model Context Protocol servers and connections
  • Advanced Settings: Update system settings, resource limits, networking, and cluster-specific options

To update a system’s configuration, click Edit from the system management page. To get the deployment command for a system, click Deploy.

Deploying a System

Once created, a system needs to be deployed to your infrastructure. Click the Deploy button on the system management page to get the installation command, then follow the guide for your environment:

  • GCP
  • Azure
  • AWS
  • Air Gapped
  • Kubernetes
  • Zero Dependency Binary