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The AI Chat lets you interact with the mogenius AI agent directly through a conversational interface. You can ask questions, investigate issues, and give instructions — the agent has access to your cluster and will use its configured tools to find answers and take action.
AI Chat requires a connected AI model. If you haven’t configured one yet, see AI Setup.

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Opening the Chat

Click the chat icon in the platform header to open the AI Chat sidebar. The chat is available at both the Cluster and Workspace level — the agent automatically scopes its responses to the context you’re working in.

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What You Can Do

The AI agent understands natural language and can use its tools to interact with your cluster on your behalf. Common use cases include:
  • Investigating issues such as misconfigured resources, unreachable applications, or networking problems.
  • Querying cluster resources like Pods, Deployments, Services, and ConfigMaps.
  • Getting guidance on resource optimization, including node allocation and resource limits.
  • Reviewing and writing Kubernetes manifests or Helm values.
  • Troubleshooting errors interactively by providing additional context the agent can use.

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Tools

The AI Chat uses the same tools configured in AI Setup. Depending on your configuration, the agent can access the following during a conversation:

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Built-in Tools

These are always available:
  • Kubernetes — The agent can query resources, read logs, describe Pods, inspect events, and retrieve manifests from your cluster. When you ask about a failing Deployment or a misconfigured Service, the agent fetches the relevant data in real time.
  • Helm — The agent can list releases, inspect chart values, and check release history. Useful for questions about what’s currently deployed or reviewing a Helm upgrade.
During a conversation, tool usage is indicated with badges (e.g., “Kubernetes”, “Helm”) so you can see which tools the agent is using to answer your question.

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GitHub

When GitHub is connected in AI Setup, the agent can access your linked repositories during chat. This enables:
  • Looking up source code, configurations, and CI/CD pipelines related to the resources you’re asking about.
  • Cross-referencing cluster state with the code that produced it.

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Memory Repository

If a Memory Repository is configured, the agent can recall context from previous interactions. It stores and retrieves long-term knowledge — such as recurring issues, environment-specific quirks, or team conventions — to provide more relevant answers over time.

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Permissions

The AI agent operates under the same permissions as the logged-in user. If your workspace role grants you View access to specific namespaces, the AI agent can only query resources in those same namespaces. The chat never exposes data beyond what you are authorized to see.

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Token Usage

Chat conversations count toward the cluster-wide daily token limit. A usage indicator near the input field shows how much of the daily budget has been consumed. Once the limit is reached, new messages are queued until the limit resets.

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Session Persistence

Chat sessions are preserved across page reloads and browser refreshes. You can close the sidebar, navigate to other pages, and return to an ongoing conversation without losing context.