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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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.

Illustration: a padlock with the shackle open and a compliance seal, ticked, stuck across the gap anyway.
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NYC's Local Law 144 requires an annual AI-hiring bias audit — but it measures fairness, not accuracy, and a 2025 state review found enforcement barely works.

Prateek Porwal · · 7 min read  →
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