Juicebox (PeopleGPT)
Juicebox (PeopleGPT) is an AI talent-sourcing search engine that lets recruiters find, rank, and reach candidates across 800M+ public profiles using natural-language queries instead of Boolean search, with an "Autopilot" agent that scores and ranks profiles against job criteria.
§ 01 — Score breakdown
§ Score breakdown
Category scoring
Weighted contribution shown to the right of each bar.
- 01
Article 11 Technical Documentation
Weight 20%52
+10.4
- 02
Bias Audit Transparency
Weight 18%84
+15.1
- 03
FRIA Support
Weight 15%35
+5.3
- 04
Data Governance Disclosure
Weight 15%56
+8.4
- 05
Human Oversight Design
Weight 12%50
+6.0
- 06
Post-Market Monitoring
Weight 12%55
+6.6
- 07
Customer Documentation
Weight 8%60
+4.8
§ 02 — Strongest · weakest
Strongest category
Bias Audit Transparency
Raw score 84 · contributes 15.1 to total.
Weakest category
Customer Documentation
Raw score 60 · contributes 4.8 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
Juicebox, operating the PeopleGPT product, is a San Francisco-based AI recruiting startup founded in 2022 by David Paffenholz and Ishan Gupta (Y Combinator S22). Its core product is a natural-language candidate search engine that indexes 800M+ public professional profiles aggregated from 30+ sources, plus an 'Autopilot' agent that automatically finds, ranks, and emails candidates against job-specific criteria. The company raised a $30M Series A led by Sequoia (≈$36M total), reports $10M+ ARR and 2,500–4,000+ customers, and serves both startups and enterprises. Pricing is roughly $139–$199 per seat/month, placing it in the mid tier.
Regulatory exposure
As an AI tool that sources and scores/ranks candidates, Autopilot is squarely an automated employment decision tool under NYC Local Law 144 and a high-risk employment AI system under the EU AI Act, Colorado SB 205, and California FEHA. Juicebox is unusually proactive here: it engages independent UK auditor Warden AI for continuous (monthly) bias auditing of Autopilot and publishes a live AI Assurance Dashboard plus a downloadable NYC LL 144 disparate-impact audit report. The main residual exposure is that no EU AI Act Article 27 FRIA materials or explicit deployer-obligation guidance are published, in-product human-oversight/explainability controls are not documented, and Article 11-style technical model documentation (model cards, ISO 42001) is absent.
Path to a higher score
Juicebox already leads its category on bias-audit transparency; to raise its overall score it should publish Article 11-style technical documentation (a model/system card and explainability statement beyond the Warden methodology), pursue ISO/IEC 42001 to anchor an AI management system, and add EU AI Act deployer guidance and a Fundamental Rights Impact Assessment template for customers. Documenting concrete human-oversight and override controls, surfacing per-candidate score explanations in-product, and making the SOC 2 / ISO 27001 artifacts referenced in its Wolfia trust center publicly verifiable would close most remaining gaps.
Conflicts of interest
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