AI screening and automation for staffing and recruiting firms
Staffing agencies, recruiters, PEOs, training providers and employment services.
Every open role means a human skimming a stack of CVs, and the good candidate is the one nobody got to in time.
What I build for staffing & workforce
Structured screening against the actual requirement
CVs parsed and matched to the role, ranked with the reasoning shown, so a recruiter starts from a shortlist and a rationale rather than an inbox.
Intake that captures the requirement properly
Most bad placements start with a vague brief. Structured intake makes the requirement explicit before anyone starts searching.
Placement and margin reporting
Time-to-fill, fill rate and margin per placement, without anybody maintaining the spreadsheet that currently answers those questions.
Where this usually starts
LLM Integration Sprint — from $7,500
Published pricing, fixed scope, and a free Operations Audit first so we both know whether the build is worth doing before either of us commits to it.
Questions I get asked
Does AI screening introduce bias or legal risk?
It can, and that is exactly why the design matters. Screening should rank against stated job requirements with the reasoning visible and a human making every decision — never an automatic reject. I build it that way and will not build it the other way.
Will it work with our ATS?
Generally yes — most of these builds read from and write back to the ATS you already have rather than replacing it. If your ATS has no usable API I will find that out in the scoping call, before you have spent anything.