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AI Candidate Screening: Fit Score, Red Flags, Interview Questions

A pile of matching profiles isn't a decision. leadl.ai's AI candidate screening turns every sourced candidate into a 0–100 fit score with an explanation — skills match, experience relevance, red flags — plus ready interview questions, so you know who to call first and what to ask them.

A score with a reason, not just a number

Most candidate screening software either dumps raw data on you or gives a match percentage with no explanation you can act on. leadl.ai's fit score is built from a candidate's actual public professional work — code, technical answers, project history — not a self-written resume, and it comes with the reasoning behind it: what matches, what's missing, and why the score landed where it did.

What the fit score is built from

Red flags, surfaced automatically

Screening isn't only about who looks good — it's about catching what a resume alone won't show. leadl.ai flags risk signals directly on each candidate's profile (career gaps, tenure patterns, skill claims without public evidence) so you can raise the right question in the interview instead of finding out after the hire.

Interview questions, generated per candidate

Every scored candidate comes with a set of interview questions built from their specific profile and the vacancy — not a generic bank of questions, but ones aimed at the gaps and red flags the screening actually found. Try the standalone version: interview questions to ask candidates.

What "AI screening" doesn't mean here

leadl.ai doesn't run AI video interviews or automate the interview itself — tools like HireVue and Paradox do that, for people who already applied. leadl.ai screens and ranks candidates before that stage, from public data, so your team spends interview time only on people worth interviewing.

Automated candidate screening — automate the pass, not the verdict

leadl.ai automates the first pass of candidate screening end to end: every sourced candidate is scored, ranked and checked for red flags automatically, with the reasoning attached to each result. What stays manual — on purpose — is the verdict. You see why a candidate scored 82 and which requirements are unconfirmed, and you decide who advances. That split is what makes automated candidate screening defensible to a hiring manager: the machine does the sorting hours, the human owns the decision.

See a real fit score on your vacancy

Paste a job description, get scored candidates with reasoning in minutes.

Try AI screening free →

See where the candidates come from first: AI Candidate Sourcing. Or read the deeper guide: how to evaluate candidates.