OfficialJev Guides & Articles
How Jack & Jill Cut Candidate Screening Costs By 88% With Jev
A TypeSafe case study of a talent marketplace that swapped Gemini 3.1 Flash Lite for Jev in candidate matching: 88% lower cost, about twice as fast, and a projected $500K a year saved.
- Format
- Article
- Published by
- TypeSafe AI
- Last verified
- Oct 2026
Highlights
- Cost per 1,000 candidates screened fell from $0.755 with Gemini 3.1 Flash Lite to $0.092 with Jev.
- Median time to screen a role's candidates dropped from 20.3s to 10.3s.
- Winners kept in the shortlist rose from 93.9% to 94.6%; ranking AUC rose from 0.924 to 0.933.
- The team tested 150 live roles, then moved Jev into production within 10 days.
- A profile check after onboarding fell from about 3.6s on Gemini to about 0.2s.
Watch out
A vendor case study with a methodology appendix: the offline quality test was run by Jack & Jill, and the $500K figure is a projection that includes expected growth.
Questions about this entry
Short answers drawn from the linked project or page.
Cost per 1,000 candidates scored fell from $0.755 with Gemini 3.1 Flash Lite to $0.092 with Jev, an 88% reduction. The post attributes it to Jev's lower input price and free output tokens.
Median time to screen all candidates for a role fell from 20.3 seconds with Gemini to 10.3 seconds with Jev, roughly half. A post-onboarding profile check dropped from about 3.6 seconds to about 0.2 seconds.
Jack & Jill report the share of hiring-manager winners kept in the shortlist rose from 93.9% to 94.6% and ranking AUC from 0.924 to 0.933; the post calls the quality difference not statistically significant.
On 150 live roles using the same candidates for each, including every past winner plus a sample weighted to represent the original 6,000 candidates retrieved per role, run as an offline test before switching.
About $265K a year at current volume, projected to $500K over twelve months once expected growth in search volume is included. The article labels the larger figure a projection, not a measured result.
The initial scoring stage of a three-step screen: 6,000 candidates per open role, a low-cost model cutting them to a 2,000 shortlist, then a stronger model narrowing to a few hundred. Jev replaced Gemini 3.1 Flash Lite there.
The post says Jev spread into more than 15 workflows, including matching roles at sign-up for under $0.10 per candidate, the CV editor, company classification, and marketplace filtering.
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