process 01Smarter ScreeningRead and score every application, not just the top of the pile. 02Better ShortlistingRank on twenty signals, with the evidence behind each one. 03Faster SchedulingNo calendars, no slots. One link, good for fourteen hours. 04Fairer InterviewsQuestions built from the role, answers scored against a written rubric.
Pricing
use cases 01Resume VerificationEvery claim read in context, not lifted out as a keyword. 02AI Cheating PreventionBuilt for the copilot era: divided attention, novel questions. 03Volume ScreeningThe same rubric for applicant one and applicant a thousand. 04Pre-BGV FilterA consistency check before formal verification spend.
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our views

Writing on hiring, and the machines doing it.

What we are learning building a system that reads every application, and what it means for the people on both sides of the process.

  1. TrustHe Worked Four Full-Time Jobs. Every Reference Check Came Back Clean.
  2. AIYour Agent Applied. Their Agent Rejected It. No Person Was in the Room Either Time.
  3. ScreeningOne Job Posting Got 1,000 Applications in Three Days. Four People Got an Interview.
  4. AI88% of HR Leaders Saw No Value From Their AI. The Vendor Says 340%.
  5. MarketThe EU Just Delayed Its AI Hiring Law by 16 Months. Don't Celebrate.
  6. CandidatesThe Salary Has Always Been There. You Just Weren't Allowed to See It Until the End.
  7. InterviewsA Dropout Raised $15M to Cheat Your Interview. He Is Half Right.
  8. MarketThe Career Ladder Lost Its Bottom Rung. The Screen Can't See the Next One.
  9. TrustThe Candidate Cleared Every Screen. The Candidate Wasn't Real.