AI Result Evaluation
Crowd panels rate how clear, well-evidenced, and actionable an AI-generated verification result is.
A confidence score doesn't tell you whether an AI-generated explanation actually makes sense to a human. AI Result Evaluation asks a crowd panel to rate exactly that — for any completed Multimedia Verification or Language Technology run, or for the output of your own AI system — and logs every rating as a durable feedback signal.
Request an evaluation against a completed run and Crowdee automatically generates the crowd task, showing the run's pipeline, verdict, and explanation — no task template required. Reviewers rate clarity, evidence sufficiency, actionability, and bias risk, and can flag a result for retraining. Individual ratings roll up into a single transparency score.
Have your own AI's output and no Crowdee run to point at? A dedicated endpoint accepts the verdict and explanation directly — see Evaluating Your Own AI's Output.
What You Get
- A transparency score (0–100) per evaluated run, aggregated from at least three independent crowd ratings.
- Per-response feedback, including free-text notes and retraining flags.
- An append-only feedback log, keyed by the specific AI component evaluated — the durable record behind improving it over time.
Cost
45 credits by default (15 credits per crowd response × 3 responses), blocked upfront when you request the evaluation. Requesting more responses for a higher-confidence score costs proportionally more.
Where to Go Next
See AI Output Evaluation for the full technical reference: the request API, rating dimensions, batch statuses, and the feedback log.
For an always-on version of this same evaluation, see Continuous Monitoring.
How is this guide?
Source Research
Trace a piece of content back to where it came from, who's behind it, and how credible that source is.
Continuous Monitoring
A scheduled, always-on version of AI Result Evaluation that flags quality drift automatically.