Automate resume screening, calculate spatial semantic matches, and reveal candidate potentials with dynamic explainable scoring engines.
Seven core layers engineered to streamline recruitment and eliminate bias.
Deep textual structure analysis mapping entities, achievements, and chronologies.
Translates extracted skills into a multi-dimensional semantic space comparing aliases and abbreviations.
Allows recruiters to customize weights dynamically based on role profiles like Backend, DevOps, or Fresh Graduates.
Detailed scoring explanations telling recruiters exactly why a candidate matching score was awarded.
Dashboard metrics summarizing matched talents, common missing skills, and overall matching efficiency.
Tracks career progress across resume versions with built-in Comparison Reliability and score timeline indicators.
Sequential orchestration pipeline carrying request contexts across semantic, xai, and mapping layers.
Follow the automated pipeline from the initial document upload up to explainable recruiter insights.
Candidates or recruiters upload PDF or Word documents directly into the screening zone.
Our parsing algorithms resolve abbreviations, synonyms, and context matches against job descriptions.
Dynamic match score timelines, xai breakdowns, and prioritized improvements appear instantly on the dashboard.
drag_and_drop_resume.pdf
Ready to parse
Scale your candidate evaluations dynamically with high-precision semantic filters and zero human bias.
