In a regulated workflow, "the agent made a reasonable decision" does not count as an audit trail. Someone still has to show who authorized the action, which controls applied, and where a human could have stepped in.
So Camunda and Diagrid Catalyst are not two versions of the same workflow product, and comparing them that way leads to the wrong choice. Camunda starts from end-to-end process orchestration and BPMN. Catalyst starts from durable, governed execution for applications, workflows, agents, and MCP servers. Both address AI now, but they enter the problem at different control boundaries.
Different approaches
Take an insurance claim. Deterministic steps validate coverage and fetch policy data. An AI agent summarizes the evidence and flags anomalies. A human approves or rejects the recommendation. Then a payment service does something that changes state.
Camunda is strong at making that whole process explicit. Its agentic orchestration documentation describes AI agents inside BPMN workflows, next to human tasks, deterministic rules, and AI-driven decisions. That is worth a lot when business and technology teams need one process model they both work from.
Catalyst treats agents as durable workflows and puts the weight on recovery, identity, policy, and observability in the execution layer. That fits better when the AI part is not one boxed task but an agent that may call tools, delegate to other agents, or run in a different environment.
Four questions that decide the fit
Who owns the process model? If business analysts and process owners have to see and change an end-to-end BPMN model, Camunda has the natural advantage. If developers own the agent code in frameworks they already use, a runtime that preserves those frameworks probably fits better.
Where does the non-determinism live? A bounded AI task inside a stable process is a different design problem from an agent that chooses its next step at runtime. Settle that question before you pick the orchestration layer.
What do you have to prove? An audit may want more than a diagram and some logs. It may want execution history, identity, the authorization decisions that were made, lineage, and evidence that the records were not altered afterwards. Diagrid's verifiable execution positioning is worth checking against the specific compliance requirement in front of you rather than accepting it as a generic checkbox.
Where does it have to run? Camunda and Catalyst both offer deployment choices, but the real constraint is which topology your organization has already approved: SaaS, your own infrastructure, private connectivity, or a fully isolated environment. Confirm the exact edition and who is responsible for what.
You may not have to pick one
An enterprise does not always need a single product to own every layer. Camunda can coordinate the formal business process while a durable agent runtime executes a complicated AI task behind a service boundary. It works the other way too. Catalyst workflows can model human approval without bringing BPMN into it, when the process is mostly owned by developers.
Choose Camunda when BPMN, human work, and process transparency are the center of the design. Evaluate Catalyst when agent durability, framework choice, workload identity, tool policy, and governance across environments are what you spend your time on.
Whichever you pick, the useful test is whether the control boundary is obvious afterwards: an auditor can find the evidence, an operator knows what can be resumed, a developer knows where side effects belong, and everyone knows the point at which the machine is allowed to act on its own.
Top comments (0)