LeverTRM combines an applicant tracking system with a CRM: a pipeline for active candidates plus relationship-nurture tooling for people not currently in process. Lever’s own product page describes AI generating interview transcripts, "smart summaries," and AI-generated scorecards with automated evaluations across four named dimensions: Technical, Leadership, Culture Fit, and Communication, paired with an explicit recommendation such as "Recommendation: Advance to Final."
Candidates move through visible pipeline stages: Sourced, Applied, Screen, Interview, Offer. Dashboards flag where candidates are, in Lever’s words, "sitting too long," surfacing bottlenecks in the process rather than scoring the resume itself. Lever’s product page contains no claim of automatic resume scoring or auto-rejection: the named dimensions and stage tracking are tools an evaluator uses, not a mechanism that filters a resume before a person sees it.
Everything above comes from Lever's own product page, which describes what the software can do. It says nothing about which dimensions a specific employer emphasizes, how they weight Technical against Culture Fit, or what triggers a recommendation on a given req. That is the employer's own configuration, and it is not visible to anyone outside their Lever account, including us.
Structure resume bullets and interview prep around the same four named dimensions Lever's scorecards use: Technical, Leadership, Culture Fit, Communication. Map at least one concrete accomplishment to each, rather than writing one long undifferentiated list of duties that never resolves cleanly against any one of them.
Because the pipeline itself flags candidates "sitting too long," a slow-moving application is more likely a process bottleneck than a rejection. Following up, through the posting’s own channel rather than by guessing at contacts, is a reasonable move at a company that hires through Lever; a stalled stage is not the same signal as a stalled score.
Lever's own product page makes no claim of automatic resume scoring or auto-rejection. What it does describe is AI-generated scorecards that evaluate candidates across four named dimensions (Technical, Leadership, Culture Fit, Communication) for a human evaluator to use, plus pipeline-stage tracking that flags where candidates are sitting too long. Both are organizing tools for a person reviewing the pipeline, not a filter that silently discards a resume.
Four, per Lever’s own product page: Technical, Leadership, Culture Fit, and Communication. Each is paired with an advancement recommendation an evaluator can act on, such as "Advance to Final." How much weight a specific employer gives each dimension, or whether they use all four, is set inside that employer’s own Lever account and is not visible from outside it.
Lever moves a candidate through five visible stages: Sourced, Applied, Screen, Interview, Offer. Lever’s own dashboards flag candidates who are, in the product’s language, "sitting too long" in a stage, which surfaces a process bottleneck for the recruiting team rather than describing anything about the resume’s content or score.
Related: every platform in this hub, how Greenhouse screens a resume, how Ashby screens a resume.
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