Design AI-assisted workflows around the way work is actually governed.
Onfria brings process steps, company knowledge, human decisions and evidence into one operating model. Each implementation starts with an AI Process Audit and validates one workflow in a Knowledge Flow Pilot before Managed Operation.
Designed for operations, engineering, quality and R&D teams
A governed workflow from intake to monitoring.
The operating model defines how a case enters, which knowledge and rules are used, where a person decides, what output is produced and how the result is reviewed.
Intake
Define the event, request or document that starts the workflow, together with its owner and required context.
Retrieval
Select the documentation, rules, history and system data needed for this specific case.
Execution
Describe the governed steps AI may support, the checks it must perform and the boundaries it must respect.
Approval or escalation
Assign named human decisions for sensitive steps, low-confidence cases and process exceptions.
Output
Specify the document, action, handoff or record the workflow must produce for the next responsible team.
Monitoring
Agree which quality, time, exception and business-impact signals determine whether the workflow should continue or change.
Move from workflow design to Managed Operation.
The platform direction is validated through one real process before any broader operational rollout.
Scope in the Audit
Map the workflow, owners, inputs, rules, risks, system boundaries and evidence needed for a pilot decision.
Validate in the Pilot
Test one workflow with representative cases, agreed control points and metrics defined before the pilot starts.
Operate after validation
Move to Managed Operation only when the pilot evidence supports it, with ownership and review requirements documented.
Define enterprise requirements before a pilot begins.
Controls and deployment choices depend on the workflow, data and customer environment. They are documented and validated in the agreed audit and pilot scope.
Access and ownership
Identify users, roles, permissions, process owners and administrators required for the selected workflow.
Human decisions
Define approval, rejection and escalation points together with the people accountable for them.
Evidence and traceability
Specify which sources, proposed outputs, decisions and exceptions the workflow must record.
Data boundaries
Document data classes, permitted locations, retention constraints and any deployment requirements before solution design.
Integration review
Validate the required source and output interfaces against the customer's actual systems and access constraints.
Review package
Prepare the questions and evidence needed by IT, security, legal and procurement before a pilot decision.
Specific controls, deployment choices and DPA terms are confirmed in the written scope; this page does not replace a security review.
Start with the process, not the tool.
Tell us about the process you want to evaluate. We will identify whether an AI Process Audit makes sense, which area to scope first and what evidence is needed before a pilot.