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Running without AI

You can run the platform with AI switched off. No model or embedding provider is contacted, no AI work is scheduled, and nothing leaves the deployment for an AI service. Everything that does not need a model keeps working.

This suits a platform installed before the AI capability is bought, a deployment where policy forbids sending data to a model, and an air-gapped install with no provider to reach.

No licence is required

A platform running without AI needs no licence. You can install it, hand it to your users, and buy the AI capability later.

What keeps working

  • Deterministic flows, their triggers and their schedules
  • Integration syncs, importing and exporting as usual
  • Sign-in and single sign-on, users, groups, roles and invitations
  • Platform settings, branding, audit logs, health and metrics
  • Every existing agent, knowledge base, flow, run and trace, readable as before

What is unavailable

  • Chat, and every agent or assistant that answers with a model
  • Creating agents, knowledge bases, prompts, skills and templates
  • Knowledge-base indexing, and searching a workset
  • Evaluations, and the MCP endpoints

AI areas stay listed and reachable in the navigation, marked unavailable rather than removed, so you can still see what is configured. AI actions are visibly disabled and explain why instead of failing when used.

Turning AI off or on

An administrator changes this from Settings → Parameters, under Artificial Intelligence. No restart is needed.

The setting has three values:

  • Enabled — AI runs, whatever the deployment default is
  • Disabled — AI does not run, whatever the deployment default is
  • Deployment default — follow the PLATFORM_MODE the platform was started with

Deployment default is a distinct choice, not the same as Disabled: it hands the decision back to the deployment, so a later change to PLATFORM_MODE takes effect.

Turning AI on

Saving provisions the built-in content that a normal startup would create, so the first save after enabling takes a moment. Wait for it to finish rather than reloading — an interrupted save leaves the platform enabled with some content still missing, and saving again completes it.

You also need at least one model provider configured before agents can run. Add one from Settings → AI Models.

Turning AI off

New AI work stops within one scheduler interval and AI actions begin refusing immediately.

Runs already in progress finish

Work already running is left to complete under its own time limit rather than being cancelled, so you may see AI activity for a few more minutes after saving. Cancelling mid-run would leave half-written runs and traces.

Nothing is deleted. Agents, knowledge bases, flows, runs and traces are all kept and stay readable, and turning AI back on needs no repair.

Setting the deployment default

PLATFORM_MODE=ai_disabled starts the platform with AI off, and is the right setting for an install that should never contact a provider unless someone deliberately changes it. See Configuration.

A platform started this way seeds no AI content at all: no built-in agents, assignments, templates, skills or knowledge bases are created, and the startup log states what was skipped. They are created the first time AI is enabled.

Flows

A flow runs as long as none of its steps needs AI. Flows built from schedules, webhooks, HTTP requests, notifications, conditions and scripts are unaffected.

A flow containing at least one AI step does not start. It is recorded as skipped, with the reason on the run, so you can see in Operations that it was held back rather than silently missed. No part of it executes.

In the flow editor, AI steps appear locked rather than absent, and a flow that already contains one tells you it will not run. Removing the AI step lets the flow run again on its next trigger — the decision is made from the flow as it is at that moment, not from a stored verdict.

A flow that hands off to another flow

If a flow calls another flow, the AI steps of the called flow count too. A deterministic flow that hands off to an AI-bearing one is held back.

Next step

To configure model providers once AI is enabled, see Settings. For what the platform shares with an AI provider and how to control it, see AI governance.