01
Map the workflow
Define triggers, records, owners, exceptions, and the consequence of a mistake.
Custom integration scope
Designed around your workflow and permissions
Connect Open AI to the workflows around it
Build multimodal agents and bounded workflows with models, tools, and structured outputs.
Typical objects
The records a scoped build may use
- Model responses
- Tools and function calls
- Files and vector stores
- Evaluations and usage data
Workflow examples
Practical patterns to evaluate
These are design examples, not claimed customer deployments or results.
- 01
Extract structured fields from approved documents.
- 02
Draft a grounded answer or summary from permitted context.
- 03
Select among a narrow set of validated tools with approval gates.
Delivery sequence
Integration work starts with the operating process
02
Confirm access
Check the platform edition, APIs, authentication, scopes, limits, and data policy.
03
Build and test
Implement narrow actions and verify normal, failure, retry, and approval paths.
04
Operate deliberately
Document ownership, logs, escalation, stop controls, and the change process.
Platform consideration
Model choice, data policy, prompt and tool design, evaluation, latency, cost, regional needs, and failure behavior require testing.
Scope before promise
Platform editions, API access, permissions, rate limits, vendor policies, security requirements, and data residency can change what is feasible. CombineApps confirms scope before implementation.
Related departments
See the workflow in team context
Related integrations
Connect the surrounding stack
Bring one real workflow
Define what Open AI should read, change, and leave for a person
We can map the systems, authority, exception paths, and test cases before deciding how the integration should be built.