AI Workbook
Feature

Connectors. Governed links to the systems your organisation already depends on.

AI value stalls when teams have to copy data between disconnected tools. Connectors let AI Workbook work with the systems the organisation already depends on, with clearer control over access and data movement.

What connectors are for

This page is about integration boundaries. Connectors can support workflows and outputs, but their primary role is to let the platform work with real systems without losing control of access, credentials, and data movement.

Connectors relay between systems and runtime
The point is not connectivity for its own sake. It is controlled movement between systems, workflows, and outputs.

Why it matters

Why it matters
Real system use
AI-enabled work can use live business data instead of depending on pasted context.
Explicit boundaries
Integration behavior is governed through defined provider, credential, and approval models.
Reusable connection patterns
Teams can connect useful services without rebuilding the same interface logic from scratch.

What value it brings

What value it brings
Less swivel-chair work
Data and outputs move through controlled interfaces instead of manual transfer.
Safer adoption
Teams can connect important systems without normalising informal data movement.
Lower long-term regret
Integration becomes part of the platform model rather than a collection of one-off hacks.
Clearer enterprise control
Teams can define which systems are approved sources, where outputs can go, and how access is governed.
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