An AI integration handover should let your team understand what the system does and who owns each part. A login and a short demonstration are not enough when the workflow depends on company data, third-party accounts, and decisions with business consequences.
Ask for the workflow contract
The handover should describe triggers, input sources, permitted actions, output destinations, and human escalation. Include the exceptions. A documented boundary such as “prepares a cancellation request but does not cancel an order” prevents users from assuming more authority than the system has.
Keep examples of acceptable and unacceptable results. They make future changes easier to assess and help new employees understand why the process was designed that way.
Make ownership explicit
List the accounts, connections, and configuration the workflow needs, without putting passwords into a shared document. Identify who can renew access, revoke it, and receive failure notifications. Company-owned access should not depend on one supplier employee's personal account.
Clarify source and configuration ownership in the agreement. Different delivery models provide different rights; do not assume that paying for implementation automatically transfers every hosted component or third-party license.
Include an operating path
An employee should know how to recognize a failed job, find its reference, and complete the work manually. The maintainer needs recovery instructions that avoid repeating external actions. A rollback should restore a known working configuration without discarding unresolved work.
For an illustrative quotation assistant, handover should explain where approved prices come from, how an expired quote is detected, and who can authorize an exception. Those details matter more than a long list of model settings.
Agree on the next change
Ask which maintenance work is included, what happens when an API changes, and how new workflows are priced. Separate defect correction from a new capability so neither side has to infer the agreement later.
Golub Superintelligence can scope a custom integration around these responsibilities. If your need is individual research or preparation, Bot may be a better starting direction than commissioning a multi-system service. Describe the job first, then choose the appropriate delivery model.