How do their growth rates compare?

Fama has a month-over-month growth rate of -5.6%; Labelbox has -22.8%.

How does pricing compare?

Fama: Contact for Pricing. Contact for pricing. Fama sells to employers, background screening providers and HR technology partners on a program basis rather than publishing self-serve tiers, so pricing is quoted after a demo and depends on screening volume and configuration. Labelbox: Contact for Pricing. Contact for pricing. Labelbox does not publish self-serve plans or public rate cards; its pricing route instead directs interested teams to talk to sales, and cost is shaped by data production scope, agent deployment and enterprise requirements. There is no published free tier. Prospective customers should request a quote based on their volumes and use cases.

What are alternatives to Fama and Labelbox?

Other tools in related categories include Workable, Roboflow, Appen, Scale, HireAI: AI Recruiter by Arc.

Fama vs Labelbox — Traffic (12.25K vs 762.8K), Pricing & Verdict

Open AI Tools

Fama vs Labelbox — Traffic (12.25K vs 762.8K), Pricing & Verdict | Open AI Tools

Side-by-Side Traffic & Specification Matrix

Dimension / Metric	Fama	Labelbox
Official Domain	fama.io	labelbox.com
Pricing Model	Contact for Pricing	Contact for Pricing
Monthly Visits	12.25K (12,251)	762.8K (762,803)
MoM Traffic Delta	-726 (-5.6%)	-225.17K (-22.8%)
Primary Market & Share	🇺🇸 United States (66.6%)	🇺🇸 United States (21.9%)
Direct Visits / mo	4.86K	370.02K
User Rating	3.9	4.4
Supported Platforms	Website	Website

Fama

AI social media screening that flags workplace-relevant behavior before you hire

Behavior-first AI detection

Identifies eight categories of workplace-relevant misconduct across 30+ languages from public online activity, rather than relying on keyword searches.

Compliance-built workflow

Removes protected class information and is designed around EEOC, FCRA, GDPR, PIPEDA and other global screening standards.

Fama Lens policy screening

Skips generic categories and screens against your organization's own policy, showing which specific policy rule each result matched for faster adjudication.

Pre-employment and ongoing screening

Supports both risk checks before hiring and continuing visibility into emerging behavioral risk during employment.

Strengths & Pros

+Addresses a real gap that criminal and credit checks do not cover
+Protected class data is removed by design, which supports defensible, consistent adjudication
+A large customer base and report volume give it operational scale and benchmarks competitors may lack
+Policy-based Lens screening lets organizations align results with their own rules instead of generic categories