Talyn runs an adaptive AI interview — a real conversation and a live work-sample — on every inbound candidate, and hands you a ranked shortlist with plain-language verdicts and the verbatim evidence behind each one. Not a résumé filter. An interview.
One control, three named settings you can name in a kickoff call. It changes what the interview actually does — and shows you the trade before a single candidate starts. Move it, and watch the funnel.
Balanced: Standard screen. Solid shortlist, standard bar.
Strong answers make the interview harder. Thin answers earn a second chance. Every move is logged — verbatim, with the reason it happened. The candidate never sees the mechanism; you see all of it.
When a candidate is cruising, the work-sample gets harder — a deeper version of the same problem, tighter constraints. Depth beyond the question’s scope raises the bar, and the log records why.
When an answer is thin, the interview offers another angle — same warmth, same phrasing as an escalation, so no one can tell which way they just moved. A recovery counts. A third thin answer doesn’t.
Ranked rows, a one-line verdict that names the bar the candidate cleared, and a click-to-open log of every escalation and lifeline. The evidence is right there, so the verdict doesn’t have to pre-argue every call — and a rejection holds up on its own.
Cleared Screen Hard. Escalated twice; held up through both with senior-level depth.
A gap. A non-traditional path. A thin-looking résumé. The kinds of candidates naive filters reject to ration a recruiter’s time. Talyn interviews them anyway — and when it finds real signal, it surfaces the save, front and center.
Cut for a two-year gap by every résumé filter. The interview found senior-level signal instead.
Machines take the floor.
Humans take the ceiling.
Talyn does the screening no one has time to do by hand, and hands the judgment back to a person — with the full picture, not a score.
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