Overview
Juicebox is an AI-powered people search engine designed for recruiters and hiring teams. It finds candidates by understanding job requirements in natural language, searching across public profiles and databases, and delivering ranked results with contact information.
Our take
Juicebox is AI-powered people search for recruiting, which places it in the most heavily regulated corner of this directory. Sourcing and searching candidates sits differently from screening and ranking them, and the distinction matters legally. Tools that find people are lower risk than tools that score them, and this is primarily the former.
Worth it if
Recruiters sourcing candidates from a wider pool than keyword search surfaces.
Look elsewhere if
Automated ranking or rejection, which carries bias-audit and notification obligations in several jurisdictions.
✨ Features
AI People Search
Describe your ideal candidate in plain English and get ranked results.
Contact Discovery
Finds verified email addresses and contact details for candidates.
Smart Matching
AI understands context, skills, and experience to rank candidates accurately.
ATS Integration
Export candidates and integrate with existing applicant tracking systems.
⚖️ Pros & Cons
Pros
Cons
💰 Pricing
Free
$0
- Limited AI people searches
- Basic candidate results
- Individual use
Pro
$99 /mo
- Unlimited AI searches
- Contact information credits
- Advanced filters and ranking
- ATS integration
Enterprise
Custom
- Unlimited team seats
- Custom integrations
- Dedicated account manager
- Volume contact credits
Categories
❓ Frequently Asked Questions
Does this trigger automated employment decision rules?
Search and sourcing generally sit outside the strictest rules; scoring, ranking and screening generally fall inside them. New York City requires bias audits and candidate notice for automated employment decision tools, and the EU AI Act classes employment AI as high risk. How you use the output decides which side you are on.
Can sourcing tools introduce bias?
Yes, through the search itself. A model surfacing candidates who resemble your past hires will reproduce whatever imbalance those hires contained, often through proxies like university, postcode or employment gaps rather than protected characteristics directly. Reviewing who gets surfaced, by group, is the check that catches it.