Criteria defined per role
Job-related requirements you specify, with weightings agreed before screening begins.
AI Product
Structured screening against job-related criteria you define, with consistent scoring, audit trails and human decision-making retained throughout.
Contact us for pricing — it depends on volume and integration scope.
Screening a large applicant pool by hand is slow and, more importantly, inconsistent — the same resume gets different treatment depending on who reads it and when.
This tool extracts structured information from applications and scores it against criteria you define for the role, producing a consistent summary per candidate with evidence for each criterion.
Be clear on the boundary: it ranks and summarizes to support a human decision. It does not reject candidates automatically, and we do not build it to. Employment screening carries real legal exposure and the design keeps a person accountable for every decision.
Job-related requirements you specify, with weightings agreed before screening begins.
Skills, experience duration, certifications and education pulled into comparable fields.
Every score cites the text it came from, so a recruiter can verify rather than trust.
Flags scoring drift across a batch and across reviewers.
What was evaluated, against which criteria, with what result, and who made the decision.
Configurable exclusion of fields unrelated to the job, and distribution reporting across a pool to surface disparate patterns.
Illustrative scenarios this product is designed for, not descriptions of specific client deployments.
Deployed against your applicant tracking system through its API, or as a standalone review workspace.
Four to seven weeks, including a calibration phase against a set of applications your team has already assessed.
Deployment in your own cloud tenancy is available where HR data policy requires it.
Categories we can build against. Feasibility for your specific systems and versions is confirmed during scoping — these are not certified partner integrations.
Applicant data is personal data, often across jurisdictions with different rules. Retention, access, candidate notification and deletion are agreed and documented before launch.
Automated employment decision tools are regulated in a growing number of jurisdictions, including bias-audit and notice requirements in some. Your counsel must confirm what applies to you. We design to keep humans accountable and to produce the audit evidence those rules tend to require, but we do not provide legal advice and we do not perform statutory bias audits.
Before launch, you get it in writing. What data the product can access, where it is processed, how long it is retained, who can read it, and what is logged. If any of that does not work for your policy, it is a design decision we change rather than a limitation you accept.
Questions
No. It ranks and summarizes; a person decides. We will not build automatic rejection, both because of the legal exposure and because the error rate is not acceptable for that kind of decision.
By excluding fields unrelated to the job, requiring evidence for every score, and reporting score distribution across a pool so disparate patterns are visible. That reduces risk; it does not eliminate it, and no honest vendor will tell you otherwise.
Contact us for pricing, based on application volume and integration scope.
Tell us the workflow you want to change and we will tell you whether this product fits, needs configuration work, or is the wrong tool.