AmazingHiring
A technical-talent sourcing platform that aggregates public developer profiles from 50+ networks (GitHub, Stack Overflow, Kaggle, LinkedIn) and uses AI to rank and surface candidates for recruiters, with verified-contact retrieval and outreach automation.
§ 01 — Score breakdown
§ Score breakdown
Category scoring
Weighted contribution shown to the right of each bar.
- 01
Article 11 Technical Documentation
Weight 20%35
+7.0
- 02
Bias Audit Transparency
Weight 18%22
+4.0
- 03
FRIA Support
Weight 15%30
+4.5
- 04
Data Governance Disclosure
Weight 15%50
+7.5
- 05
Human Oversight Design
Weight 12%48
+5.8
- 06
Post-Market Monitoring
Weight 12%33
+4.0
- 07
Customer Documentation
Weight 8%52
+4.2
§ 02 — Strongest · weakest
Strongest category
Customer Documentation
Raw score 52 · contributes 4.2 to total.
Weakest category
Bias Audit Transparency
Raw score 22 · 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
AmazingHiring (founded 2011, headquartered in Redwood City, California) is a technical-talent sourcing engine that aggregates 600M+ candidate profiles from 50+ public sources — GitHub, Stack Overflow, Kaggle, and other developer communities alongside LinkedIn and job boards — and layers AI ranking, verified-contact retrieval, outreach campaigns, and a Chrome extension on top for technical recruiters. The AI sorts and ranks candidates by fit across attributes such as job title, experience, skills, and professional-community activity; recruiters set the search parameters and make all contact and hiring decisions.
Regulatory exposure
Because AmazingHiring scores and ranks candidates by 'fit,' it is potentially in scope for NYC Local Law 144 (as a tool used in sourcing prioritization) and for the EU AI Act's high-risk employment category, yet it publishes no bias audit, AI model/system card, explainability statement, or Fundamental Rights Impact Assessment material. Its documented compliance posture is entirely GDPR/data-protection-oriented — Data Controller/Processor delineation, an appointed DPO, sub-processor Article 28(3) DPAs, EU Model Clauses, data minimization and retention, and ISO 27001-referenced information security — which addresses data governance reasonably well but leaves the algorithmic-accountability obligations of AEDT-specific laws essentially undocumented.
Path to a higher score
Commission and publish an independent NYC LL 144 bias audit plus an AI system/model card that explains the ranking attributes and how scores are derived; add explicit deployer guidance for NYC LL 144 and an EU AI Act Article 27 FRIA template; obtain a first-party ISO 27001/SOC 2 certificate (and consider ISO 42001) rather than relying solely on the cloud provider's certification; and stand up a public status/security page, incident channel, and sub-processor list to evidence post-market monitoring.
Conflicts of interest
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Casework has no commercial relationship with this vendor.