AI agent for HR candidate screening
An AI worker that reviews every application against your role criteria, applies the same standard to each candidate, books screening calls, and hands you a shortlist with reasons.
Volume hiring is inconsistent and slow
A popular role can draw hundreds of applications, and the first pass is brutal: someone skims CVs under time pressure, applies a standard that drifts as fatigue sets in, and inevitably reads the hundredth CV differently from the first. Strong candidates wait days for a reply and take another offer; weak ones get interview slots that should have gone elsewhere; and almost nobody can explain, afterwards, exactly why a given applicant was passed over.
That inconsistency is not just inefficient — it is a fairness and defensibility problem. Screening should apply the same criteria to every candidate and leave a record of why each decision was made. Doing that by hand, at volume, against the clock, is precisely where humans struggle and an operator, run carefully, can help.
A consistent first pass with a record
- 01Define the criteria. With your team the operator is set up against the role’s must-haves, nice-to-haves, and disqualifiers — the same explicit standard for every applicant.
- 02Parse every application. It reads CVs and forms, extracting experience, skills, qualifications, and gaps into a structured profile.
- 03Score against the role. It assesses each candidate against the defined criteria and records a plain-language rationale for the score — not an opaque number.
- 04Engage and schedule. It acknowledges every applicant, asks any clarifying screening questions you set, and books screening calls for the strong matches into recruiter calendars.
- 05Surface the shortlist. It hands recruiters a ranked shortlist with reasons attached, plus the borderline cases flagged for a human look rather than auto-rejected.
Built to be consistent and defensible
Screening people demands more care than screening invoices. The operator assesses only the job-relevant criteria you define and is configured to disregard protected and irrelevant attributes; AIMOCS reviews its scoring distribution for adverse patterns rather than assuming fairness. The reasoning core is version-pinned so the same standard applies across a hiring round, and an append-only log records every assessment and its rationale — the record you need if a decision is ever questioned.
Your ATS, calendars, and the application channels sit behind a uniform gateway with scoped credentials; the operator holds no raw secrets, runs in a contained environment, and handles candidate data under your retention and privacy rules.
The operator screens; people decide
No one is hired or finally rejected by the operator. It runs the consistent first pass and produces a shortlist with reasons; interviews, judgment, and the hiring decision stay entirely with your recruiters and managers. Borderline candidates are flagged for human review, never auto-rejected, because the cost of a wrong screen-out is a missed hire. You own the criteria, the fairness rules, and the final call — the operator makes that work fast, consistent, and recorded.
Does the AI agent decide who gets hired or rejected?
No. It runs a consistent first-pass screen and surfaces a ranked shortlist with reasons. Interviews, judgment, and the hiring decision stay with your team, and borderline candidates are flagged for human review rather than auto-rejected.
How do you stop it from being biased?
It assesses only the job-relevant criteria you define and is configured to disregard protected and irrelevant attributes. We review its scoring distribution for adverse patterns, version-pin it for consistency, and log every assessment with its rationale so decisions are auditable.
Does it integrate with our ATS?
Yes. Your ATS, calendars, and application channels sit behind the operator’s tool gateway, mapped during setup, and candidate data is handled under your retention and privacy rules.
We don't advise on AI. We run it for you.
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