How we measure
If we publish a number, here's exactly where it comes from.
Public claims should be auditable. This page lists every metric we put on the site, our methodology, and our last verification date.
Live claims
| Claim | How measured | Last verified |
|---|---|---|
| 180+ data sources | Count of unique data-source categories integrated into the investigation pipeline, including registries, sanctions feeds, hiring sources, and pattern libraries. Sub-sources within a category count separately. | 2026-05-15 |
| 50,000+ job seekers (eyebrow badge) | Cumulative unique user signups, all-time. Includes free-tier accounts. Excludes deleted accounts. | 2026-05-01 |
| Scams detected (50K+, landing stat) | Count of reports flagged with at least one HIGH-confidence scam-risk indicator, all-time. Same dossier flagged twice counts once. | 2026-05-01 |
| 99.2% accuracy rate | Internal benchmark over a 500-case labeled set drawn from known scams and known-legitimate companies. We report accuracy as 1 − (false positives + false negatives) / total. The benchmark set is rotated quarterly. | 2026-04-22 |
| 2.3s average report time | Median end-to-end response time across all completed investigations over the last 30 days, sampled at minute granularity. | 2026-05-20 |
| 4.8 average rating | Mean of opt-in in-product ratings collected post-report over the last 90 days. Sample size disclosed in JSON-LD as ratingCount. | 2026-05-15 |
Where the asterisks live
— Accuracy is benchmarked, not measured live. A benchmark set can never fully reflect production traffic.
— User-count metrics include free-tier accounts. We don't pretend they're all paying customers.
— Speed is median, not p99. A heavy investigation can take longer than the headline number.
— Ratings are voluntary. People who hate the product rarely fill out the form.
Find a claim we publish that isn't on this page? Email us — we'll add it.
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