Recruitee
Collaborative applicant tracking system, part of the Tellent group, with AI-assisted features for job-description generation, screening candidates against team-defined criteria, resurfacing past applicants, and summarizing evaluation feedback.
§ 01 — Score breakdown
§ Score breakdown
Category scoring
Weighted contribution shown to the right of each bar.
- 01
Article 11 Technical Documentation
Weight 20%42
+8.4
- 02
Bias Audit Transparency
Weight 18%30
+5.4
- 03
FRIA Support
Weight 15%27
+4.0
- 04
Data Governance Disclosure
Weight 15%52
+7.8
- 05
Human Oversight Design
Weight 12%58
+7.0
- 06
Post-Market Monitoring
Weight 12%40
+4.8
- 07
Customer Documentation
Weight 8%58
+4.6
§ 02 — Strongest · weakest
Strongest category
Customer Documentation
Raw score 58 · contributes 4.6 to total.
Weakest category
FRIA Support
Raw score 27 · contributes 4.0 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
Recruitee is a collaborative applicant tracking system founded in 2015 in Amsterdam by Perry Oostdam and Pawel Smoczyk. It now operates as "Tellent Recruitee," a product unit of the Tellent group formed after Recruitee's 2021 merger with Sympa and later acquisitions of Javelo and kiwiHR. Aimed mainly at SMB and mid-market hiring teams, it provides career sites, job posting, candidate pipelines, and collaboration tools, layered with AI-assisted features: job-description generation and translation, an AI screening assistant that evaluates applications against clear team-defined criteria, a matching assistant that resurfaces existing candidates from the database, AI evaluation summaries that consolidate team feedback, and an AI writer for candidate emails.
Regulatory exposure
Recruitee's AI screening, candidate matching/rediscovery, and evaluation features fall within Annex III recruitment-and-selection use under the EU AI Act (high-risk obligations from 2 August 2026) and can constitute an AEDT under NYC Local Law 144 when used to screen or rank candidates. Recruitee publishes a plain-language AI Statement and solid security/privacy documentation (ISO 27001, SOC 2 Type II on request, EU-only data residency, a DPA and sub-processor framework, GDPR automation) and commits not to train AI models on customer data. However, it publishes no bias audit, no EU AI Act or FRIA deployer guidance, and no model cards or Article 11 technical documentation, so deployers must request compliance evidence directly.
Path to a higher score
Recruitee could raise its score by commissioning and publicly posting an independent bias audit (NYC LL 144 style, e.g., BABL AI / Warden AI / Holistic AI) and repeating it annually; publishing model/system cards and instructions-for-use for its screening and matching features; adding explicit EU AI Act deployer guidance plus a FRIA template; and pursuing ISO 42001. Documenting its AI data-exclusion and (non-)training practices in detail and surfacing a public status/monitoring page would further lift the data-governance and post-market-monitoring categories.
Conflicts of interest
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