Sapia.ai
Structured, text-based chat interview that scores candidates on personality (HEXACO) and competency traits — with no video, audio, or demographic data used.
§ 01 — Score breakdown
§ Score breakdown
Category scoring
Weighted contribution shown to the right of each bar.
- 01
Article 11 Technical Documentation
Weight 20%70
+14.0
- 02
Bias Audit Transparency
Weight 18%52
+9.4
- 03
FRIA Support
Weight 15%35
+5.3
- 04
Data Governance Disclosure
Weight 15%62
+9.3
- 05
Human Oversight Design
Weight 12%62
+7.4
- 06
Post-Market Monitoring
Weight 12%50
+6.0
- 07
Customer Documentation
Weight 8%62
+5.0
§ 02 — Strongest · weakest
Strongest category
Article 11 Technical Documentation
Raw score 70 · contributes 14.0 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
Sapia.ai (legally Sapia&Co Pty Ltd, formerly PredictiveHire) is a Melbourne-based HR-tech vendor selling an enterprise "Smart Interviewer." Candidates complete a structured, text-only chat interview of roughly five to seven open questions — there is no video or audio recording. Its models analyse written responses to produce personality (HEXACO) and competency profiles, with natural-language explanations tracing each score back to the candidate's own words. The company is unusually well-prepared on AI governance, holding ISO/IEC 42001:2023 certification (Sensiba LLP, October 2025) alongside ISO 27001 and SOC 2.
Regulatory exposure
As an automated employment decision tool used at the screening/interview stage, Sapia.ai is in scope for the EU AI Act (high-risk employment use), NYC Local Law 144, and the Illinois and Colorado regimes. Its strongest signal is the ISO 42001 AI-management-system certification. Its weakest point is bias-audit currency: the only independent disparate-impact audit it publishes (BLDS, LLC) dates to December 2022, is framed as a US/Canada study rather than an annually-refreshed NYC LL 144 audit, and the full report is not openly downloadable.
Path to a higher score
The fastest gains are in bias-audit transparency and FRIA support. Publishing a current independent NYC LL 144-format audit with openly downloadable impact-ratio tables would move it from "one old audit" to "consecutive public audits." Posting model cards and an instructions-for-use / deployer-obligations pack (leveraging the ISO 42001 documentation it already maintains) would lift the Article 11 and customer-documentation scores, and an explicit Article 27 FRIA template would be a clear differentiator.
Conflicts of interest
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