AI integrations.
Model capabilities connected to approved data and tools, with firm limits on the actions they can take.
Treat the connection as part of the product.
A model response is only one step in a business workflow. We define the input, the expected output, the checks and the next action so the integration has a defined role and an owner when something goes wrong.
What we can build together.
The final deliverables, review rounds and schedule are agreed around your brief.
- Task and system design
- Define the job, data sources and systems involved.
- Model and API integration
- Connect the selected capability with structured inputs and outputs where appropriate.
- Access and review
- Set boundaries around data access, actions and human approval.
- Evaluation and monitoring
- Test representative cases and agree how quality, failures and usage will be reviewed.
Define the action boundary.
Separate a draft from a committed change
Generating a suggested reply and sending it are different actions. Likewise, extracting a field and updating a customer record should not be treated as one invisible step. Agree validation and approval around the action that changes the business system.
Evaluate the whole workflow
Test what happens when input is missing, a response is unsuitable or a connected tool is unavailable. The model can be functioning while the overall task still fails. Keep enough operational visibility to identify which step needs attention and who can resolve it.
From brief to handover.
Define the contract
Agree what the integration receives, produces and is permitted to change.
Build a limited workflow
Connect the required systems and validate outputs before downstream actions.
Test and operate
Review failure cases, add monitoring and document the owner’s controls.
The answers to
your questions.
Get in touch
Can AI update our CRM?
It can be scoped to do so where APIs and permissions allow, with validation and approval requirements agreed in advance.
Can we use an existing model provider?
Yes. We review its capabilities, commercial terms and suitability for the task before implementation.
What if the model returns an unsuitable answer?
The workflow should handle invalid or uncertain outputs and provide a fallback or human review path.