Candidate evaluation software that scores applicants 0 to 100 against one rubric per role, backed by interview and resume evidence, so comparison is fair and ranking is defensible.
Evaluating candidates well is hard because the inputs are messy: a resume here, three interview impressions there, a take-home that one person reviewed. Without a consistent framework, evaluation collapses into preference. The candidate who interviewed last, or reminded someone of themselves, gets the edge. Candidate evaluation software exists to replace that drift with structure.
Lehire evaluates every candidate against a single rubric per role and produces a 0 to 100 fit score backed by evidence. Each score traces to specific criteria, interview answers, and resume signals, so it is an argument you can inspect rather than a number you have to trust blindly.
The payoff is fair comparison. When everyone is measured the same way, the ranking reflects the candidates, not the inconsistencies of who evaluated them. That is the foundation of a hiring decision you can stand behind.
Candidate evaluation software is a tool that assesses applicants against a defined set of role criteria and produces comparable, evidence-backed scores. Rather than tracking candidates through stages like an ATS, it focuses on measuring fit: applying one rubric per role, converting interview and resume signal into a 0 to 100 fit score, and enabling fair comparison and ranking. It is the evaluation layer that informs the hiring decision.
The most common evaluation mistake is judging candidates before agreeing on what good looks like. Criteria get invented mid-process, weighted differently by each interviewer, and quietly shifted to fit whoever the team already likes. Lehire makes you define the rubric for the role up front: the criteria, what they mean, and how much they matter.
Defining "good" before you judge is what makes evaluation honest. Every candidate is then measured against the same standard, and the standard is the role's actual requirements rather than a moving target shaped by the candidates in front of you.
Lehire turns each candidate's evaluation into a single fit score from 0 to 100. That score is composed from the rubric criteria, weighted as you defined them, and fed by interview scorecards, AI Interviewer results, and resume evidence. The number is a summary, and the evidence behind it is always one click away.
This is the difference between a score you can defend and a score you have to apologize for. When a hiring manager challenges why a candidate scored what they did, you show the criteria and the evidence. The conversation moves from "do you trust the number" to "do we agree on the criteria," which is the conversation worth having.
Once candidates are scored against the same rubric, comparison is straightforward and fair. Lehire ranks candidates by fit and lets you compare them side by side on each criterion, so you see not just who scored higher but where and why. The close calls are obvious, and you can focus discussion exactly where the candidates diverge.
Ranking on consistent evidence also protects against the failure mode where the strongest interviewer-advocate wins regardless of the candidate. The candidate with the best evidence ranks highest, which is the only ranking that should drive a decision.
Lehire is not a candidate database or an ATS. You bring candidates from your ATS, from job boards, or through Lehire's public application links. Lehire's job is to evaluate them well and feed that evaluation back: export scored, ranked candidates to your ATS or to CSV.
Keeping evaluation separate from tracking is deliberate. The ATS is optimized to move people through stages; it was never designed to help you decide who deserves to move. Dedicated candidate evaluation software fills that gap without trying to replace the system of record you already rely on.
Define criteria and weights up front, so every candidate is judged against the same standard.
A 0 to 100 score per candidate, traceable to specific criteria and evidence.
Compare candidates criterion by criterion to see exactly where they differ.
Rank by fit so the strongest evidence wins, not the loudest advocate.
Combine resume evidence with interview scorecards into one consistent evaluation.
Send scored, ranked candidates back to your ATS or export to CSV in a click.
An ATS lets you tag and rate candidates loosely. Here is what dedicated evaluation adds.
Put your final candidates side by side on every criterion to make the close call clearly and quickly.
Score a large applicant pool consistently and rank it so review effort goes to the strongest fits.
Anchor every assessment to the same rubric so personal preference does not quietly drive the score.
Hand leadership a scored, evidence-backed rationale for why the chosen candidate was the strongest fit.
No. Candidate evaluation software like Lehire focuses on assessing and scoring candidates, not tracking them through stages. It sits on top of your ATS, evaluates the candidates you bring, and exports scored, ranked results back.
You define a rubric of criteria and weights for the role. Lehire scores each candidate against it using interview scorecards, AI Interviewer results, and resume evidence, producing a fit score where every point traces to specific evidence.
Yes, and you should. Each role gets its own rubric: the criteria and weights that define a strong fit for that specific position. Evaluation is only fair when the standard matches the role.
Yes. Consistent scoring is most valuable at volume, because it lets you rank a large pool and focus human review on the strongest candidates instead of reading every profile cold.
From your ATS, job boards, or Lehire's public application links. Lehire is not a sourcing tool; it evaluates the candidates you already have access to.
Premium is $79 per user per month. Enterprise adds interview intelligence depth, integrations, and security, with custom pricing. There is no free trial; onboarding is demo-led.
See how evidence-backed evaluation makes comparison fair and ranking defensible.