Recruiting AI that speeds the process without deciding for you
Parsing, scheduling, screening support, and pipeline reporting on top of your ATS, with bias testing, human review at every decision, and records built for audit.
How it works
Recruiters lose their week to coordination, not judgment: reformatting resumes, chasing four calendars for one panel, and rebuilding the same pipeline report every Monday morning. That work is safe to automate and worth automating. What is not safe is handing rejection authority to a model, so the systems we build rank, structure, and summarize, while a named human makes every advance-or-reject call and the record shows exactly who made it.
Resume parsing that produces a real profile
Every inbound application becomes structured, comparable data in your ATS instead of an attachment somebody has to open.
- Extracts skills, titles, tenure, certifications, and gaps from PDFs and scans
- Normalizes titles and skills to your taxonomy so candidates compare fairly
- De-duplicates against existing ATS records and prior applications
- Optional masking of name, photo, school, and address for first-pass review
Scheduling that stops the late-stage drop-off
Panels get booked in hours rather than days, which is where most strong candidates are quietly lost.
- Multi-interviewer availability across calendars, time zones, and panels
- Self-serve booking links with automatic rescheduling and reminders
- Interview notes transcribed against your scorecard, not free-form impressions
- Debrief packets assembled and delivered before the hiring manager asks
Screening support designed to be audited
Assistance for the humans doing the screening, with the fairness testing and documentation the law increasingly expects.
- Ranks and summarizes against job-related criteria, never auto-rejects anyone
- Annual disparate-impact testing by sex and race/ethnicity in the Local Law 144 format
- Selection-rate and impact-ratio reporting you can publish, plus candidate notice templates
- Every score explained, versioned, and logged with the reviewer who acted on it
Where teams use it
Built for real revenue work.
High-volume requisitions with 900 applicants
Instead of a recruiter opening resumes until the morning runs out, the pipeline arrives structured and ranked against job-related criteria, with the reasoning shown so the recruiter can disagree and record why.
Panels that take two weeks to convene
Availability, booking, rescheduling, and reminders run across the whole panel automatically, and the interview kit, scorecard, and prior notes land inside each interviewer's calendar invite.
Talent leaders rebuilding the same board deck
Pipeline health, source quality, stage conversion, and time in stage generate from live ATS data, including the breakdowns you need for EEO-1 reporting and adverse-impact review.
“We wanted the speed without ever having to explain a model to a regulator. Screening stayed a human call, but the shortlist now arrives structured and the annual bias testing report largely writes itself.”
FAQ
Questions, answered.
What does AI recruiting software actually do?
In practice it handles the operational half of talent acquisition: parsing and structuring resumes, matching candidates to open requisitions, coordinating interviews across panels, transcribing and summarizing interviews against a scorecard, and reporting on pipeline health. It shortens the calendar, not the judgment. Recruiters and hiring managers still make the hiring decisions.
Can AI reject candidates automatically?
It can, and we do not build it that way. Automated rejection concentrates legal risk, removes the person who would have caught an obvious parsing error, and is precisely the behavior regulators are examining. Our systems rank, summarize, and flag. A named human makes each advance-or-reject decision, and the system records who, when, and on what basis.
How do you handle bias auditing and NYC Local Law 144?
If a tool substantially assists or replaces a hiring decision, New York City treats it as an automated employment decision tool, which requires an independent bias audit from within the past year, published selection rates and impact ratios by sex and race/ethnicity category, and candidate notice at least ten business days before use. We build the outcome data capture that makes that audit possible from day one, run internal disparate-impact testing against your own results, and support whichever independent auditor you appoint. Illinois, Maryland, Colorado, and the EU AI Act impose overlapping duties, so we design to the strictest regime you are exposed to.
Will this work with the ATS we already have?
Yes, and we assume it has to. We integrate with Workday, Greenhouse, Lever, iCIMS, SmartRecruiters, and Taleo through their APIs, and with anything else through a documented middleware layer. Your ATS stays the system of record while we add parsing, scheduling, screening support, and reporting on top of it. The integration code is yours at handover.
Keep exploring
More from the Leadify platform.
Custom AI Software
Purpose-built AI systems delivered on a fixed price, with the IP transferred to you.
AI Document Processing
Turn resumes, transcripts, and credentials into structured, comparable data.
AI for Training & Enablement
What happens after the offer: ramp paths that get new hires productive sooner.
Faster hiring, defensible decisions
Send us one live requisition and a batch of resumes, and we will show you the parsing quality and the audit trail on your own pipeline.