HiPeople
HireAIScore rates HiPeople 61 out of 100 (grade D, Concerning) under rubric v1.0, last reviewed August 2, 2026. HiPeople ranks 2 of 82 vendors rated in Assessment AI, against a category average of 46. That score is drawn from 31 evidence items across 7 rubric criteria for HiPeople — 27 with a cited source, 8 recording that nothing was located.
Score breakdown
HiPeople, criterion by criterion
Each rubric criterion is scored out of 100 on the cited evidence, then weighted into the total.
Weighted contribution shown to the right of each bar.
Article 11 Technical Documentation
Weight 20% · category avg 50
62
+12.4
Bias Audit Transparency
Weight 18% · category avg 41
84
+15.1
FRIA Support
Weight 15% · category avg 31
35
+5.3
Data Governance Disclosure
Weight 15% · category avg 53
58
+8.7
Human Oversight Design
Weight 12% · category avg 55
62
+7.4
Post-Market Monitoring
Weight 12% · category avg 38
60
+7.2
Customer Documentation
Weight 8% · category avg 58
66
+5.3
Total weighted score
61.4(rounded to 61 for display)
Category avg is the mean raw score on that criterion across the 82 Assessment AI vendors in scope of this rubric, this one included.
Strongest criterion
Bias Audit Transparency
84raw / 100
Contributes 15.1 to the total. 84 against a 41 category average.
Weakest criterion
FRIA Support
35raw / 100
Contributes 5.3 to the total. 35 against a 31 category average.
Cited evidence
The evidence behind the score
Every score is backed by at least one cited piece of evidence. Open a criterion to see what was found, when, and where.
Download diligence recordEvidence ledger
- Items
- 31
- Documentation
- 16
- Audit report
- 5
- Public statement
- 2
- Absence
- 8
- With a source URL
- 27 of 31
- Source hostnames
- 7
- Fewest items
- 3
- FRIA Support
These figures measure how thoroughly HiPeople was reviewed, not how HiPeople performed — an absence row, recording that nothing was located, is counted like any other item.
Article 11 Technical Documentation
4 items62
- DocumentationCaptured Aug 2, 2026
HiPeople runs a dedicated SafeBase-hosted AI Trust Center whose published sections include an AI Systems Overview ('How HiPeople Uses AI', 'How to Recognize AI in the Product', 'AI Training Data'), an EU AI Act group ('Compliance with the EU AI Act', 'Alignment with EU AI Act Principles', 'Decision-Making and Human Oversight'), US Employment Law items, and GDPR Article 22 material.
- Public statementCaptured Aug 2, 2026
HiPeople publishes an explainability and legal-basis statement for AI Resume Screening, describing a 'match breakdown with clear, factual evidence behind each score' and asserting the product is 'GDPR Article 22, EU AI Act Article 14 compliant'.
- AbsenceCaptured Aug 2, 2026
No model card, system card, instructions-for-use document, or ISO 42001 certification was found on hipeople.io, trust.hipeople.io, the /science page, or the /artificial-intelligence page; the trust center's 'How to Recognize AI in the Product' document is listed as gated rather than public.
- AbsenceCaptured Aug 2, 2026
The /science page asserts that HiPeople's methods are 'scientific and rigorously evidence-based' but publishes no test-construction detail, reliability or validity statistics, peer-reviewed citations, or downloadable technical whitepaper.
Bias Audit Transparency
6 items84
- Audit reportCaptured Aug 2, 2026
A publicly accessible Warden AI assurance dashboard for HiPeople's AI Application Screening shows monthly continuous bias auditing with a latest audit date of 9 July 2026 across 19,092 candidate samples, returning a 'Clear' grade on sex, race/ethnicity, intersectional sex-by-race/ethnicity, age, disability, religion and sexual orientation.
https://trust.warden-ai.com/hipeople/ai-application-screening
- Audit reportCaptured Aug 2, 2026
A public NYC Local Law 144 bias audit report dated 9 July 2026 by Warden AI publishes selection rates and impact ratios by sex (Female 48.93%/1.00, Male 48.58%/0.99), by race/ethnicity (0.98–1.00), and across eight intersectional categories (0.94–1.00), with sample sizes of 1,688 per sex category and 422 per intersectional cell, noting Warden's independent dataset was used due to lack of access to historical data.
https://trust.warden-ai.com/hipeople/ai-application-screening/nyc
- Audit reportCaptured Aug 2, 2026
A separate public EU AI Act (Regulation 2024/1689) bias report dated 9 July 2026 assesses risk management, pre-market testing, post-market monitoring, transparency and human oversight for protected classes per Recital 57, while expressly stating it 'should not be interpreted as evidence of full compliance with the EU AI Act'.
https://trust.warden-ai.com/hipeople/ai-application-screening/eu-ai-act
- Audit reportCaptured Aug 2, 2026
A detailed bias and fairness page publishes both disparate-impact results and counterfactual individual-bias consistency scores (Female 100.00%, Male 99.90%) over the 19,092-sample dataset.
https://trust.warden-ai.com/hipeople/ai-application-screening/bias
- DocumentationCaptured Aug 2, 2026
Warden AI's published methodology documents the four-fifths rule threshold, counterfactual matched-pair testing that varies only identifying details, and testing across 15+ protected categories, establishing the basis for HiPeople's audit grades.
- AbsenceCaptured Aug 2, 2026
No bias audit, adverse-impact study, or fairness evidence was found for HiPeople's assessment library, reference checking, or AI screening calls - only the AI Application Screening system appears in the Warden Assured directory and dashboards.
FRIA Support
3 items35
- DocumentationCaptured Aug 2, 2026
The AI Trust Center provides partial deployer-facing regulatory material, publishing items titled 'Compliance with the EU AI Act', 'Alignment with EU AI Act Principles', 'Decision-Making and Human Oversight', 'NYC Local Law 144 (AEDT)' and 'Article 22 GDPR', which gives deployers a starting reference set.
- AbsenceCaptured Aug 2, 2026
No Fundamental Rights Impact Assessment template, Article 27 guidance, or deployer-obligation checklist was found anywhere on hipeople.io, trust.hipeople.io, the Warden AI reports, docs.hipeople.io, or in targeted web searches pairing HiPeople with FRIA/Article 27.
- AbsenceCaptured Aug 2, 2026
HiPeople's own 'AI Compliance' blog post is generic educational content covering GDPR, CCPA, EEOC and the Illinois AI Video Interview Act, and does not address FRIA, Article 27, or deployer obligations under the EU AI Act.
Data Governance Disclosure
4 items58
- DocumentationCaptured Aug 2, 2026
A public subprocessor page names vendors grouped by function with data regions, explicitly disclosing OpenAI, Microsoft Azure and Google Cloud for AI Resume Screening, AI Interviews and AI Assistant, ElevenLabs for AI interviews, and AWS, Kombo, Checkr, Intercom, Mailgun, Mixpanel, Sentry, Dash0 and LaunchDarkly for platform functions.
- DocumentationCaptured Aug 2, 2026
A Data Processing Agreement is published as Schedule 1 of the public terms, incorporating GDPR Article 28 obligations, a two-week client objection window on new subprocessors, data-subject request handling, deletion-on-termination duties, and an Annex 1 of technical and organizational measures covering access control, encryption, input logging, backup and recovery testing.
- DocumentationCaptured Aug 2, 2026
The Privacy & Security page documents SOC 2 Type II certification with annual audits, GDPR and CCPA alignment, customer-configurable data retention and deletion rules, PIN-protected candidate profiles with revocable access, and consent-based processing.
- AbsenceCaptured Aug 2, 2026
HiPeople holds no ISO 27001 or ISO 42001 certification of its own (ISO certifications cited in its terms belong to AWS as infrastructure provider), its SOC 2 report is gated behind an access request on the trust center, and the 'AI Training Data' trust center item's substance is not readable without an interactive session, so no training-data exclusion list could be verified.
Human Oversight Design
5 items62
- DocumentationCaptured Aug 2, 2026
HiPeople describes 'Recruiter-in-the-loop' design claimed to be 'GDPR Article 22, EU AI Act Article 14 compliant', with the system explaining its judgment and quoting the specific resume sections behind each score, alongside resume anonymization and pre-processing to reduce bias.
- DocumentationCaptured Aug 2, 2026
The AI Trust Center publishes a dedicated item titled 'Decision-Making and Human Oversight' under its EU AI Act section, plus an 'Article 22 GDPR' item addressing automated decision-making.
- DocumentationCaptured Aug 2, 2026
Assessment results are surfaced to recruiters as in-depth comparative reports with an AI insights layer allowing preset or free-form questions against candidate results, and results can be shared back to candidates with learning resources.
- AbsenceCaptured Aug 2, 2026
The Resume Screening help-center collection covers job setup, prompt writing, supported languages, candidate review and fraud signals, but documents no score-override control, no audit log, and no per-jurisdiction compliance toggle.
https://docs.hipeople.io/en/collections/12478526-resume-screening
- Public statementCaptured Aug 2, 2026
HiPeople states that recruiters can 'define auto-rejection and auto-advance rules', meaning customers can configure the product to act on AI scores without an individual human review step, which tempers the recruiter-in-the-loop framing.
Post-Market Monitoring
4 items60
- Audit reportCaptured Aug 2, 2026
A publicly viewable continuous monitoring dashboard runs monthly re-audits of HiPeople's screening model and explicitly advertises 'Post-market monitoring', 'Continuous bias auditing' and 'Transparent reporting', giving outsiders ongoing visibility into fairness drift.
https://trust.warden-ai.com/hipeople/ai-application-screening
- DocumentationCaptured Aug 2, 2026
A public Pingdom uptime dashboard linked from the HiPeople site footer resolves and displays a rolling service-monitoring table, though the page does not itself carry HiPeople branding or a written incident history.
- DocumentationCaptured Aug 2, 2026
The trust center publishes a dedicated responsible-disclosure contact at security@hipeople.io alongside a support channel, and the Privacy & Security page documents a formal vulnerability disclosure process.
- AbsenceCaptured Aug 2, 2026
The help-center 'Updates' collection is a thin index of two articles and publishes no dated changelog of AI model changes, scoring-logic revisions, or assessment updates.
Customer Documentation
5 items66
- DocumentationCaptured Aug 2, 2026
HiPeople maintains full public product pages for each module - AI resume/application screening, assessments, AI screening calls and reference checks - with compliance badges for GDPR, SOC 2, CCPA and the Warden AI audit, and footer links to the trust center, documentation, status page and AI audit reports.
- DocumentationCaptured Aug 2, 2026
A public help center at docs.hipeople.io organizes customer guidance into collections covering resume screening setup, prompt writing, candidate review, fraud signals, hiring teams and product updates.
https://docs.hipeople.io/en/collections/12478526-resume-screening
- DocumentationCaptured Aug 2, 2026
The AI Trust Center provides jurisdiction-specific customer-facing items including 'NYC Local Law 144 (AEDT)', 'Federal Law and EEOC Guidance', 'US Employment Law Compliance', 'GDPR Compliance and AI' and 'Data Roles', giving deployers a per-regime reference surface.
- DocumentationCaptured Aug 2, 2026
A complete Data Processing Agreement is published openly as Schedule 1 of the terms rather than being held back for sales negotiation, and is cross-referenced to the public subprocessor list.
- DocumentationCaptured Aug 2, 2026
A dedicated 'Leading the Way for AI in Screening' page sets out HiPeople's 'AI where it makes sense' positioning, describes proprietary fraud-detection AI verifying candidate–reference relationships, and links out to both the AI Trust Center and the external Warden AI audit reports.
Editorial notes
Company overview
HiPeople GmbH was founded in Berlin in 2019 by Jakob Gillmann and Sebastian Schüller and is registered at Zionskirchstraße 73a, 10119 Berlin (HRB 211492 B). The company raised roughly $6.8M from Moonfire, Capnamic Ventures, Cherry Ventures and Mediahuis. Its platform spans four modules: a talent assessment library of 400+ skills and personality tests, automated reference checking with fraud/relationship verification, AI resume and application screening that produces a match score against customer-defined criteria, and AI screening calls across 113 languages. Customers named on its trust center include Fujifilm, Douglas, OLX Group, DAZN, Celonis, Zapier and Grammarly. Entry pricing starts around $70/month with a credit-based model layered on top.
Regulatory exposure
As a Berlin-headquartered provider whose tools screen and rank candidates, HiPeople sits squarely in Annex III employment high-risk territory under the EU AI Act and carries provider-side obligations, with GDPR Article 22 exposure on automated decision-making. Its US customer base pulls in NYC Local Law 144 AEDT duties, plus EEOC/Title VII and the Illinois and Colorado regimes. HiPeople is unusually strong on the bias-audit dimension: Warden AI runs continuous monthly third-party auditing of its AI Application Screening system, with a publicly viewable dashboard (latest audit 9 July 2026, 19,092 samples) covering sex, race/ethnicity, intersectional sex-by-race, age, disability, religion and sexual orientation, plus dedicated NYC LL 144 and EU AI Act bias reports carrying published selection rates and impact ratios. The important caveat is scope: that assurance covers the application-screening product only, not the assessment library, reference checks, or AI screening calls. Elsewhere the picture thins - the SafeBase AI trust center structures topics against the AI Act but gates or client-renders the substance, there is no ISO 42001, no model or system card, no published validity evidence behind the assessments, and nothing on Article 27 FRIA support for deployers.
Path to a higher score
The highest-leverage move is extending Warden's continuous auditing beyond AI Application Screening to the assessment library, reference checks and AI screening calls, since those are the products the primary category rests on and they currently carry no published fairness evidence. Publishing an Article 11-style technical pack or system card per AI system - intended purpose, model and data provenance, known limitations, performance metrics - and ungating the 'How to Recognize AI in the Product' and 'AI Training Data' items would lift technical documentation materially. Adding an explicit deployer-obligations page with an Article 27 FRIA template and DPIA mapping would move FRIA support off the floor. Pursuing ISO 42001 alongside the existing SOC 2 Type II, publishing the psychometric validity and adverse-impact evidence gestured at on the /science page, and adding a real AI model-update changelog plus documented override and audit-log controls in the help center would round out the remaining gaps.
Regulatory frame
What applies to assessment AI.
Assessment is the most-regulated surface in AI hiring. NYC LL 144, EEOC and OFCCP frameworks, Illinois HB 3773, and EU AI Act Annex III §4 all apply, with overlap on bias-audit obligations.
Compare
HiPeople against its nearest-scoring peers.
The closest scores in Assessment AI, side by side.
- Side-by-sideHiPeople vs Alva Labs61D
- Side-by-sideHiPeople vs HireVue58F
- Side-by-sideHiPeople vs Fuel5058F
- Side-by-sideHiPeople vs Bryq57F
Ranking
Others rated in Assessment AI
Ranked 2 of 82 by weighted total under rubric v1.0. The ordering is arithmetic on the rubric and carries no view on which tool suits a given hiring process.
- #1Maki People67D
- #2HiPeopleThis profile61D
- #3Alva Labs61D
- #4HireVue58F
Conflicts of interest
No vendor pays for placement, scoring, or removal. Casework - the consulting firm that operates this directory - provides paid services to some vendors. Any active or recent (within 24 months) commercial relationship is disclosed on the affected vendor profile and the review is reassigned to an independent reviewer. See the full policy on About.
Casework has no commercial relationship with this vendor.