Support triage workflow
AI summarizes, classifies, and drafts. Humans approve external responses and escalations.
Proof
Proof should be operational, not performative.
Verdify uses artifacts, scorecards, workflow examples, and the public Live Lab to show how bounded AI operations work before asking buyers to take the claim on trust.
Public AI greenhouse
A physical proof layer with telemetry, bounded control, public scorecards, and honest limits.
Sample boundary matrix
Define what AI may read, classify, draft, recommend, execute, and never touch.
Sample scorecard
Measure whether the workflow is faster, safer, more accurate, easier to supervise, and worth expanding.
Workflow teardown examples
Support triage, quality documentation, and CPG exception workflows decomposed into claims, boundaries, evidence, and caveats.
Quality documentation workflow
AI assembles source evidence and drafts summaries. Required review and traceability remain authoritative.
Proof standard
Every proof artifact should name the claim, boundary, evidence, and caveat.
The point is not to make AI look impressive. The point is to make the workflow inspectable enough that a buyer can decide whether the evidence supports the next step.
Claim
What the AI workflow is supposed to improve: speed, quality, traceability, exception handling, or supervision.
Boundary
What AI may read, draft, recommend, execute, and what it must never touch.
Evidence
Telemetry, logs, source traces, reviewer decisions, scorecard metrics, and before/after comparisons.
Caveat
What the proof does not show yet, including confounders, known limits, and unresolved risks.
Proof pages are useful when buyers need evidence before a call.
Good fit when
You need to understand Verdify's operating posture before involving a team.
Your workflow has actions that need explicit boundaries.
You want examples of artifacts before starting an audit.
You value caveats and known limits as part of the proof.
Not a fit when
You want broad AI transformation claims without operating details.
You expect public client data before a client has approved publication.
You want a greenhouse automation product.
You do not want to define prohibited actions or scorecard metrics.
FAQ
Common buyer questions.
What counts as proof before there are public client case studies?
Verdify uses artifact proof: boundary matrices, scorecards, workflow teardowns, explicit excluded actions, and the public greenhouse lab. Client case studies will use the same structure when they are publishable.
Why include what was not automated?
For high-trust AI workflows, restraint is evidence. Naming what AI was not allowed to do shows the action boundary, approval model, and operating discipline.
Is the greenhouse proof causal proof?
No. The greenhouse comparison is operational evidence with caveats, not a controlled A/B test. Its strongest proof is auditability: planner availability, telemetry, stress, cost, and score are visible enough to inspect.