Ceipal
AI-powered applicant tracking and workforce-management platform for staffing firms that sources, matches, and ranks candidates on a 1-to-100 scale against job requirements.
§ 01 — Score breakdown
§ Score breakdown
Category scoring
Weighted contribution shown to the right of each bar.
- 01
Article 11 Technical Documentation
Weight 20%30
+6.0
- 02
Bias Audit Transparency
Weight 18%20
+3.6
- 03
FRIA Support
Weight 15%25
+3.8
- 04
Data Governance Disclosure
Weight 15%46
+6.9
- 05
Human Oversight Design
Weight 12%46
+5.5
- 06
Post-Market Monitoring
Weight 12%38
+4.6
- 07
Customer Documentation
Weight 8%53
+4.2
§ 02 — Strongest · weakest
Strongest category
Customer Documentation
Raw score 53 · contributes 4.2 to total.
Weakest category
Bias Audit Transparency
Raw score 20 · contributes 3.6 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
Ceipal (Ceipal Corp.), founded in 2015 and headquartered in Rochester, New York, is an AI-powered staffing and recruiting platform serving over 100,000 recruiters worldwide, with R&D in Hyderabad, India. It combines an applicant tracking system with vendor management and workforce management, and its AI candidate matching and ranking engine contextualizes each candidate's location, experience, and skills to score and shortlist them on a scale of one to one hundred, delivering ranked results to the recruiter's dashboard across 200+ job boards. Its primary category is ATS with a strong sourcing secondary.
Regulatory exposure
Ceipal's AI scoring and ranking of applicants functions as an Automated Employment Decision Tool under NYC Local Law 144 and would likely qualify as a high-risk employment system under EU AI Act Annex III, creating audit, notice, transparency, and (for EU deployers) fundamental-rights-assessment obligations. Yet Ceipal publishes no bias audit, no AEDT or Local Law 144 guidance, no EU AI Act deployer or FRIA support, and no AI-specific technical documentation or explainability statement; its public assurance posture (SOC 2 Type II, GDPR processor commitments, ISO 27001-audited hosting) addresses information security rather than algorithmic accountability, leaving the substance of AI-hiring compliance to its customers.
Path to a higher score
Ceipal could raise its score meaningfully by commissioning and publicly posting an independent NYC Local Law 144 bias audit (with auditor and date), publishing an AI model/system card and an in-product explainability statement describing how the 1-100 rank is produced, and adding a data-governance disclosure covering training data and excluded protected attributes. Adding EU AI Act deployer guidance and a FRIA template, documenting human-oversight and override controls with audit logs, standing up a public status/security-disclosure channel and model-update changelog, and pursuing ISO 42001 would move it from a security-only posture toward genuine AI-Act and Local-Law-144 readiness.
Conflicts of interest
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