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Novistu

Use case : automation

AI candidate screening

AI candidate screening scores every application against a structured, role-specific rubric with evidence highlights for each judgment, monitors for adverse impact continuously, and leaves every advance decision with a human recruiter who sees the evidence, not just the score.

The problem

High-volume roles drown recruiters in applications: screening quality depends on remaining energy at 6pm, consistency between reviewers varies, and strong candidates are lost in queues while weak fits get interviews on gut feel.

Systems it touches

ATS platformsApplication sourcesInterview schedulingVoice screening (optional)

How it works

The automated version, step by step.

  1. 01

    Define

    The rubric is written with your hiring managers: criteria, weights, what good evidence looks like.

  2. 02

    Screen

    Every application scored against the rubric with evidence quotes attached per criterion.

  3. 03

    Monitor

    Adverse-impact metrics tracked continuously across cohorts; anomalies flagged.

  4. 04

    Review

    Recruiters see ranked lists with evidence, verify the top of the pile, and make every advance decision.

  5. 05

    Calibrate

    Hiring outcomes feed back; rubrics and scoring recalibrated on real results.

What changes

Every candidate gets a fair, consistent read; recruiters work from defensible shortlists instead of resume piles; and the process survives both legal scrutiny and candidate experience standards.

Variations by industry

Pairs with voice first-round interviews for volume hiring, and with knockout-question automation for roles with hard requirements (licences, certifications, right to work).

Common questions.

When built correctly: rubric transparency, adverse-impact monitoring, candidate notices and human decision authority. Several markets mandate exactly these; we build to that standard everywhere.

Keyword filters match strings; rubric screening evaluates evidence against criteria and shows its reasoning. Recruiters audit the why, not just the what.

The system produces rubric-based summaries your team can share where policy allows, which is fairer to candidates and protects you in disputes.

Tell us what is eating your team's hours.

A short brief, answered within one working day. The first call is free, and if AI is not the right answer, we will say so on that call.

First call free : honest about fit : no obligation