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Our Story

High-volume hiring needs clearer evidence.

Applicant volume keeps rising, but most teams still make early review decisions by opening resumes one at a time. We built OpenSeat to make qualified candidates, rationale, and review history easier to see.

Review bottlenecks should not hide qualified candidates.

Large applicant pools create a practical problem: teams need to move quickly, but the evidence that matters is scattered across resumes, ATS fields, notes, scorecards, and reviewer opinions.

We believe that evidence should outweigh opinion. Hiring teams deserve tools that explain recommendations, show the source material, and make review decisions easier to discuss.

What that belief produced.

OpenSeat is a hiring workflow layer that groups, ranks, and documents candidate evaluations with plain-English rationales linked to role requirements and resume evidence.

It sits alongside Lever, handles the first-pass review work your team does not have time to do manually, and produces output hiring managers can review, challenge, and trust.

Transparency First

If AI makes a recommendation, it should explain why in plain English. Every ranking should point back to the evidence behind it.

Respect the Candidate

Every application deserves a role-aware review, not just a keyword scan. OpenSeat evaluates the full applicant pool against the job requirements.

Speed is Respect

Recruiters and candidates both benefit when qualified people are visible sooner. OpenSeat helps teams process thousands of applicants in a day.

Where we are today.

OpenSeat is an early-stage product built by a small team with deep conviction about how hiring should work. We are focused on Lever teams with high applicant volume, building the workflow layer that makes high-volume screening manageable, explainable, and auditable.

See how we built it.

Explore the workflow, review our security practices, or book a demo.