Workflow inventory
Ranked list of candidate workflows with owner, volume, source systems, current pain, risk level, and measurement path.
Verified AI Operations Audit
Know where AI belongs before you build.
A fixed-scope audit that identifies high-value Verified AI workflow opportunities, defines action limits and approval points, surfaces risks, and produces a practical roadmap for one controlled implementation.
Evidence from the lab
The audit starts with what AI may write and what must stay authoritative.
In Verdify Lab, the first design question was not whether the AI agent could control the greenhouse. It was which tactics the agent could propose, which control layer would accept them, and which controller would enforce physical state.
Inspect the Greenhouse Case StudyWhat transfers to an audit
Map the workflow before choosing tools, prompts, models, or automations.
Define allowed, conditional, and prohibited AI actions before implementation.
Name the authority layer, telemetry events, scorecard metrics, known limits, and decision gate before any MVP.
Deliverables
The audit ends with decisions, not a vague recommendation deck.
Each artifact is meant to help the team decide which workflow to build first, what AI may do, and what evidence must exist before implementation expands.
AI opportunity map
Where AI can read, classify, draft, recommend, route, or execute, with value and risk separated by workflow step.
Control Matrix
Allowed, conditional, and prohibited AI actions, including customer-facing, regulated, irreversible, and system-of-record writes.
Risk register
Failure modes, owners, mitigations, escalation triggers, required evidence, and unresolved procurement or data issues.
Telemetry plan
Event list for inputs, recommendations, approvals, overrides, exceptions, handoffs, scorecard metrics, and review cadence.
Executive readout
Recommended first workflow, scope, investment logic, non-goals, and the decision needed to start or defer an MVP.
Scope
What the audit requires from your team.
The audit is fixed-scope, but it is not passive. Verdify needs enough context to map authority, evidence, and workflow reality.
Typical timeline
Two to four weeks, depending on stakeholder count, system complexity, and how quickly workflow samples can be reviewed.
Client inputs
Workflow walkthroughs, sample tickets or documents, current SOPs or policies, system screenshots, reporting exports, risk concerns, and decision-owner interviews.
Decision produced
Build, defer, or reject the first AI workflow, with the controls, scorecard, owner, and implementation path explicit.
Sample artifact
Example audit output: medtech design-change evidence pack.
This is the level of specificity the audit is designed to produce before anyone builds. The same structure can be applied outside medtech when authority, evidence, and approval paths are explicit.
| Workflow step | AI may | AI may not | Evidence |
|---|---|---|---|
| Change intake | Classify change type and affected records. | Approve the change or close CAPA. | Change request ID, source docs, reviewer decision. |
| Traceability review | Map requirements to tests and flag missing links. | Invent source evidence or alter controlled documents. | QMS record IDs, document revisions, trace completeness. |
| QA/RA review prep | Draft a review packet and unresolved-gap memo. | Release the device or submit regulatory changes. | Approver IDs, exception log, approval-ready evidence packet. |
Support escalation remains a valid simpler audit pattern. This example shows how the same audit structure handles document-heavy workflows where reviewer-approved evidence matters.
The audit is the right first step when the controls are unclear.
Good fit when
You have AI ideas but no clear priority.
A workflow has enough volume or consequence to justify controls.
Leadership wants ROI evidence before expanding AI use.
You need a practical first implementation path.
Not a fit when
You want generic AI training without a specific workflow.
You want unchecked automation of customer-facing or irreversible actions.
You cannot provide stakeholder access for workflow discovery.
You need a large platform rebuild before workflow controls can be discussed.
FAQ
Common buyer questions.
Is this a strategy workshop or an implementation plan?
The audit produces an implementation-ready roadmap. It includes workflow inventory, action limits, systems-of-record review, risk register, telemetry plan, and a recommended first Verified AI build path.
Do we need a model or prototype already?
No. The audit is useful before a prototype exists, especially when the team has multiple AI ideas but no shared definition of what AI should be allowed to do.
What makes this different from AI readiness consulting?
The audit is workflow-specific. It focuses on allowed and prohibited actions, approval paths, logging, scorecards, and the first implementation decision.