Data contract and integration
Specify input formats, required fields, timestamps and output schema. Define responses to missing or invalid data. Check compatibility so a service-version change does not unexpectedly break callers. Keep business rules in an explicit, testable layer rather than scattering them through model code.
Repeatable tests and versions
Record model files, data definitions and application versions together. Test empty inputs, timeouts and device faults as well as successful examples. Compare new versions with the same control samples. Maintenance depends on identifying which change affected a result and being able to return to a previous version.
Security and operation
A service should access only necessary data and resources. Keep credentials out of source code and limit personal or confidential data in logs. Handle lost external connections and missing model responses predictably. Monitoring reports health and error types; an AI output should not automatically become an operational decision in every situation.