Most AI hiring tools just filter resumes. Lehire applies AI to the part that matters: scoring candidates 0 to 100 on evidence, running consistent AI interviews, and ranking finalists you can defend.
AI has flooded into hiring, mostly at the top of the funnel: resume parsers, keyword filters, and sourcing bots that surface more candidates faster. That helps with volume, but volume was rarely the real problem. The hard part of hiring is deciding well between the candidates you have, and that is where most AI hiring platforms go quiet.
Lehire is an AI hiring platform aimed at the decision. It uses AI to convert interviews and evidence into 0 to 100 fit scores, to run a consistent turn-based AI Interviewer that screens candidates fairly, and to rank finalists so the strongest fit rises to the top. The AI is in service of a better decision, not a faster reject pile.
Just as importantly, Lehire is honest about what it is not. It is not an ATS, a candidate database, or a sourcing tool, and it does not pretend an algorithm should make the hire. It structures evidence and surfaces signal; your team decides.
What is What is an AI hiring platform??
An AI hiring platform applies artificial intelligence to hiring tasks such as screening, evaluation, interviewing, and decision support. Lower-value applications focus on resume parsing and keyword filtering at the top of the funnel. Higher-value applications, like Lehire, apply AI to the decision itself: scoring candidate fit on evidence, conducting consistent AI interviews, and ranking finalists, while keeping the final judgment with human hiring teams.
Most AI hiring tools solve the wrong problem
The crowded part of the AI hiring market is sourcing and resume screening: tools that match keywords and rank by surface signals like job titles and school names. These are easy to build and easy to oversell, and they tend to amplify exactly the biases hiring teams are trying to reduce, because keyword matching rewards pedigree over fit.
The expensive, high-stakes part of hiring is the decision: comparing real candidates and choosing between them. That is underserved because it is harder. It requires structured evidence, consistent scoring, and a model that explains itself. Lehire is built for that harder, more valuable problem.
AI scoring you can actually explain
Lehire's AI produces a 0 to 100 fit score per candidate, but the design principle is that the score must be explainable. Every score traces back to rubric criteria, scorecard ratings, AI Interviewer results, and resume evidence. There is no black box telling you whom to hire; there is a transparent aggregation of evidence you defined the rules for.
This matters for trust and for fairness. A score you cannot explain is a liability, both because the team will not believe it and because you cannot defend it. Explainable AI scoring is the only kind that belongs in a hiring decision.
The AI Interviewer: consistent, fair screening
Lehire includes a turn-based AI Interviewer that runs a screening conversation using text-to-speech and the candidate's microphone. It asks role-relevant questions, captures and scores the answers, and saves the result against the candidate. Because every candidate gets the same structured interview, the screen is consistent in a way human phone screens rarely are.
The AI Interviewer is a first pass, not a verdict. It clears the noise so your team's live interview time goes to candidates worth meeting, and its scores feed the same unified fit model as human scorecards rather than living in a separate silo.
AI that ranks, plus a human who decides
Lehire's Decision Engine uses the scored evidence to rank candidates against the role and flag the close calls. That is the appropriate division of labor: the AI handles the consistency and the heavy comparison, surfacing a ranked shortlist with reasons attached, and the human makes the actual call with full context.
We are deliberate about this line. AI is excellent at applying a consistent standard at scale and terrible at owning a high-stakes judgment about a person's career. Lehire keeps it on the right side of that line, which is what makes it a platform hiring teams can actually trust.
Explainable AI fit scoring
A 0 to 100 score per candidate where every point traces to inspectable evidence.
AI Interviewer
Turn-based screening interviews that ask, listen, score, and save results per candidate.
AI-assisted ranking
The Decision Engine ranks finalists on evidence and flags the close calls for the panel.
Evidence aggregation
AI unifies resume, scorecard, and interview signal into one comparable evaluation.
Human-in-the-loop by design
AI surfaces signal and ranks; your team makes the final hiring decision.
Hiring memory
Re-rank past candidates against new roles using the evidence already captured.
Most AI hiring tools work at the top of the funnel. Here is how a decision-focused platform differs.
Use cases
Consistent screening at volume
Use the AI Interviewer to give every applicant a fair, structured first-round screen.
Explainable shortlisting
Hand a hiring manager an AI-ranked shortlist where every position comes with its evidence.
Reducing screening bias
Score on role criteria and evidence instead of letting keyword matching reward pedigree.
Faster, better debriefs
Walk into the decision with AI-aggregated evidence and close calls already surfaced.
Point AI at the decision, not just the resume.
See an AI hiring platform that scores, interviews, and ranks on evidence you can defend.