Gem
Gem is an AI-first recruiting platform combining a talent CRM, AI sourcing and outreach automation, candidate engagement, and a newer applicant tracking system with AI-powered application review and ranking.
§ 01 — Score breakdown
§ Score breakdown
Category scoring
Weighted contribution shown to the right of each bar.
- 01
Article 11 Technical Documentation
Weight 20%58
+11.6
- 02
Bias Audit Transparency
Weight 18%66
+11.9
- 03
FRIA Support
Weight 15%35
+5.3
- 04
Data Governance Disclosure
Weight 15%57
+8.5
- 05
Human Oversight Design
Weight 12%61
+7.3
- 06
Post-Market Monitoring
Weight 12%47
+5.6
- 07
Customer Documentation
Weight 8%62
+5.0
§ 02 — Strongest · weakest
Strongest category
Bias Audit Transparency
Raw score 66 · contributes 11.9 to total.
Weakest category
Customer Documentation
Raw score 62 · contributes 5.0 to total.
§ 03 — Cited evidence
§ Evidence
Cited per category
Every score is backed by at least one cited piece of evidence.
§ 04 — Editorial notes
Company overview
Gem (Gem Software, Inc.), founded in 2017 by ex-Dropbox/Facebook engineers Steve Bartel and Nick Bushak and headquartered in San Francisco, is an AI-first recruiting platform serving over 1,200 customers including Stripe, Robinhood, and Databricks. Its product spans a talent CRM, AI outbound sourcing and outreach, talent rediscovery, candidate engagement, and a next-generation ATS, layered with agentic AI features including AI-powered Application Review that scores and ranks candidates 0-100% against recruiter-defined criteria. Pricing is reported around $4,000 per seat annually with an enterprise-leaning customer base.
Regulatory exposure
Gem's AI Application Review ranks job applicants, placing it squarely in scope of AI-hiring scrutiny under NYC Local Law 144, the EU AI Act (Annex III high-risk), and US state laws. Gem positions its tools as decision-support that accelerate rather than make hiring decisions, and on that basis does not classify them as Automated Employment Decision Tools, while nonetheless proactively commissioning a NYC LL 144-style bias audit. It publicly monitors the EU AI Act and Colorado AI Act and commits to support customer compliance, but publishes no EU deployer guidance, FRIA templates, or formal model/technical documentation, leaving most non-NYC obligations to its customers.
Path to a higher score
Gem already clears several bars most peers miss: a publicly downloadable independent BABL AI bias audit, a detailed AI compliance FAQ, in-product explainability (per-criterion percentage matches), PII redaction, a named AI Governance Group, and a public status page. To score higher it should publish a second consecutive year's bias audit to demonstrate continuity, release a formal model/system card or technical pack and an explainability statement (and pursue ISO 42001), and add explicit EU AI Act deployer guidance plus FRIA support to convert its 'we monitor these laws' stance into concrete deployer-facing documentation.
Conflicts of interest
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