Map
Understand the workflow, systems, people, decisions, exceptions, and current pain.
Method
The Verdify Method for Verified AI
A practical way to move from "Can AI automate this?" to "Can we verify how this workflow works?"
Define Controls
Decide what the AI agent may do, what it must not do, who approves outputs, what systems remain authoritative, and how rollback works.
Build
Implement a narrow workflow with clear acceptance criteria and controlled integrations.
Verify
Test quality, exceptions, telemetry, reviewer signal, and operational impact.
Operate
Monitor, score, tune, and expand only when evidence supports it.
Operating model
Verified AI makes action limits inspectable.
The same operating model applies across software, quality, field service, procurement, telemetry, and proof-lab workflows: define the role, preserve authority, measure outcomes, and expand only when the evidence supports it.
Evidence from the lab
The AI agent plans. Control layers constrain writes. Firmware controls. Telemetry verifies.
The greenhouse is the public proof environment behind the method: The AI agent plans. Control layers constrain writes. Firmware controls. Telemetry verifies. Scorecards and lessons close the loop.
See the Live LabHow the method transfers
Map: identify the workflow, systems, people, decisions, exceptions, and current baseline.
Define Controls and Build: give the AI agent a narrow role while approval paths, firmware, policy, or systems of record retain authority.
Verify and Operate: use telemetry, scorecards, incident review, known limits, and expansion gates to decide what changes next.
Vocabulary
Verified AI depends on outcome evidence.
Verify means observable evidence; control layers are runtime constraints. The distinction matters when teams move from concept to operations.
Verify
Outcome evidence: telemetry, scorecards, test cases, reviewer signal, source traces, exceptions, and operational impact.
Control layers
Write constraints, schemas, policy checks, approval paths, tool permissions, and runtime checks before an output can affect the workflow.
Control Matrix
Define what AI may read, draft, recommend, execute, and never touch.
A useful AI workflow is not defined by model capability alone. It is defined by allowed and prohibited actions, human approval, system authority, telemetry, and the scorecard that determines what can expand.
AI Workflow Control Matrix
Turn vague automation language into explicit permissions, approvals, evidence logs, owners, and exclusions.
AI Control Loop Blueprint
Use the greenhouse pattern when the workflow has a measured feedback loop: planner or agent, control layer, authority layer, telemetry, scorecard, and known limits.