Measure against your standard.
Define what good looks like.
Bring the work you want evaluated.
PoQ returns the result and the record behind it.
How PoQ works
01
Set the standard
Define the criteria.
Set weights and thresholds.
02
Route the work
Let agents handle volume.
Surface uncertainty for review.
03
Apply judgment
Apply qualified expert judgment.
Score context and consequence.
04
Reach consensus
Combine independent scores.
Measure quality and agreement.
Evaluate the whole system
Inputs
Evaluate the data and context AI systems rely on.
Reasoning and process
Evaluate how AI systems arrive at a result.
Outputs
Evaluate what AI systems generate or return.
Decisions and actions
Evaluate what AI systems decide and do.
See the result. Keep the detail.
Quality Score
Consensus Score
Proof Report
PoQ Record
Bring your own
Source a panel
Start with a managed pilot.
Request a pilot
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About VERIQ
VERIQ explores Proof of Quality for AI work: explicit criteria, independent expert review and a record of the evidence behind a result.
What does Proof of Quality evaluate?
It compares AI work with an explicit rubric. Quality scores describe performance against that standard; agreement scores describe consistency between independent reviewers.
What stays in the record?
The intended record connects the criteria, individual judgments and resulting scores. A record makes a conclusion inspectable; it does not turn subjective judgment into an absolute truth.
Do I need a wallet to explore?
No. You can explore the method without connecting. Choose SKIP to continue, or connect a browser wallet when you choose.