Teamtailor
Teamtailor is a Stockholm-based applicant tracking and employer-branding platform whose OpenAI-powered "Co-pilot" assists recruiters with candidate screening, resume and interview summaries, talent-pool matching, interview-question generation, and AI-assisted job-ad and content writing.
§ 01 — Score breakdown
§ Score breakdown
Category scoring
Weighted contribution shown to the right of each bar.
- 01
Article 11 Technical Documentation
Weight 20%50
+10.0
- 02
Bias Audit Transparency
Weight 18%30
+5.4
- 03
FRIA Support
Weight 15%42
+6.3
- 04
Data Governance Disclosure
Weight 15%58
+8.7
- 05
Human Oversight Design
Weight 12%54
+6.5
- 06
Post-Market Monitoring
Weight 12%42
+5.0
- 07
Customer Documentation
Weight 8%62
+5.0
§ 02 — Strongest · weakest
Strongest category
Customer Documentation
Raw score 62 · contributes 5.0 to total.
Weakest category
Bias Audit Transparency
Raw score 30 · contributes 5.4 to total.
§ 03 — Cited evidence
Download diligence record→§ Evidence
Cited per category
Every score is backed by at least one cited piece of evidence.
§ 04 — Editorial notes
Company overview
Teamtailor (Teamtailor AB) is an applicant tracking system and employer-branding platform founded in Stockholm in 2013 and used by over 10,000 companies, with 500+ employees. Its AI layer, 'Co-pilot,' is built on OpenAI GPT models and covers candidate screening, resume and video-interview summaries, talent-pool candidate suggestions, interview-question and skills generation, discrimination detection in interview content, and job-ad/content drafting and translation. AI features must be actively enabled by a company admin rather than being on by default, and the product is framed as decision support with the recruiter retaining final judgment.
Regulatory exposure
Teamtailor publicly acknowledges that several Co-pilot features meet the EU AI Act's definition of high-risk AI and that it acts as the 'provider,' committing to detailed technical documentation, instructions for use, risk/quality management, conformity assessment, post-market surveillance, and EU-database registration once the high-risk rules apply (from August 2026). It gives customers explicit deployer-side guidance (candidate notice, competent human oversight, and assessing how AI influences candidates' access to employment). However, it publishes no NYC Local Law 144 bias audit, no independent or academic bias/disparate-impact audit, and no Fundamental Rights Impact Assessment template, and it holds SOC 2 Type 2, ISO 27001 and ISO 27701 but not ISO 42001.
Path to a higher score
The largest gaps are audit and published technical evidence. Commissioning and publicly posting an independent bias/disparate-impact audit (e.g., Warden AI, BABL AI, or Holistic AI), plus an NYC LL 144 summary where NYC candidates are in scope, would move the bias-audit score most. Pursuing ISO 42001, publishing model/system cards and the 'instructions for use' and FRIA template it currently only references as future obligations, and ungating its 'Information Security and AI Policy' would raise the technical-documentation, data-governance, and FRIA scores. Adding an AI model-update changelog or monitoring surface would strengthen post-market monitoring.
Conflicts of interest
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