AI integration services
For product leaders, CTOs, and operations owners adding AI to an existing application. Define the workflow, permitted data, intended action, acceptance criteria, and responsibilities before release.
Connect AI to a workflow you can own and verify
Map the data and action
Identify authoritative records, API permissions, data freshness, and the exact output the user needs. Decide whether the system may draft, recommend, or act, and which actions require approval.
Define acceptance before release
Agree on representative examples, failure cases, acceptance thresholds, and a named reviewer. Check retrieval, structured output, permissions, and downstream behavior against that test set.
Plan for exceptions
Specify retries, escalation, audit records, rollback, and what happens when a source or model is unavailable. Monitoring and support responsibilities belong in the agreed scope.
Make the next decision
Bring the existing product, data sources, intended users, and workflow owner. The first discussion determines whether discovery or a bounded integration is the appropriate next step.
Evaluation and monitoring can be scoped as part of an integration. This page does not promise an established managed-operation service, a response-time guarantee, or a measured client outcome.
Related project: Attuned Health — custom application engineering inside Shopify.