AI becomes operational only when data can flow securely
A model cannot compensate for unclear system ownership, poor data quality or overly broad permissions. Integration is therefore treated as part of the solution design.
From read-only access to controlled action
Step 1
Read
Retrieve approved fields or documents without changing the source.
Step 2
Propose
Show a proposed action to an employee in the app.
Step 3
Approve
An authorised user approves the specific change.
Step 4
Execute
An integration component performs only the validated, permitted action.
Typical integration sources
- Document repositories and knowledge bases
- ERP, CRM and project management systems
- Email, calendar and case queues
- Databases, APIs and controlled file extracts
- PLC/SCADA and machine data where physical and digital automation meet
Technical controls
Every integration should have a clear purpose, a data contract and an owner. Errors, duplicates, rate limits and missing access should trigger visible fallback behaviour rather than silent failure.
- Least-privilege service accounts
- Secrets kept out of the browser, code and prompts
- Input and output validation
- Idempotency and duplicate protection
- Audit trail for sources, actions and approvals
Data contracts before code is written
An integration begins not with code, but with an agreement on the data: which fields are exchanged, what they mean, who owns them, which format and frequency apply, and what should happen when data is missing or invalid. We call that agreement a data contract.
Without a data contract, errors are discovered in production, where they are most costly. With a data contract, validation, error paths and responsibilities can be tested before the first real record is transferred.
Why an integration is more than an API connection
The API call itself is the smallest part. A responsible integration clarifies identity and access (who acts and with which permissions), input and output validation, error handling and retries, idempotency where repeated calls could otherwise create duplicates, traceable logging, and human approval before consequential write operations.
We therefore normally start with read-only access. Read access can create value early while revealing data-quality issues and edge cases before any write operation is allowed to touch the source system.
Common questions
Does every system need an API?+
No. A pilot can begin with controlled file extracts or read-only lookups. The long-term integration route is assessed separately.
Can an agent be given write access?+
Yes, but only for bounded objects and actions, with validation, logging and the relevant approvals.
How do you prevent data from different customers or cases being mixed?+
Access, indexes, environments and logs must be separated and tested for the specific architecture.