500 people apply. Your shortlist of 20 is ready before you open a single resume. Not from keyword matching. From real intent that no resume has ever captured.
more applications per job since 2022
“Could get a thousand applications in two hours.”
— Head of Global TA, Morningstar
AI-polished CVs flood your inbox faster than any team can process. Every qualified candidate looks identical to every unqualified one.
per headhunter placement
“Manual review gives you no confidence. Headhunters don’t scale.”
— Exec Recruiter, 15 years
A bad senior hire costs $150-250K. That’s 3-5 months recruiting, 6 months onboarding, then starting over. Every workaround is a regression.
of recruiter time spent filtering noise
“We have to get through 2.6 times more applicants to make the same hires.”
— Global Recruiting Director, Accenture
74% of recruiters manage 11+ roles simultaneously. TA teams have shrunk from 1.8% to 1.2% of workforce while volume exploded.
The application form has not changed since 2006. Candidates drop the same CV. The form produces no signal. Nobody has restructured the intake.
Applications are up 9x. Every CV looks the same. Nobody has restructured the intake to filter the pile down.
68% of you are reviewing resumes yourselves. The pipeline sends identical CVs. You pattern-match for 1.5 seconds each.
74% manage 11+ roles. You spend 34% of your week filtering noise. AI made every application look the same.
You validate five signals before presenting anyone. That works, but it doesn't scale. A bad hire costs $150K-$250K.
Candidates complete a personalized challenge based on their CV. A smaller, stronger pile reaches you, and every candidate on it has documented evidence for why they are there.
The application captures real intent. Non-serious candidates self-select out. When your hiring manager asks why someone made the list, you have the documented evidence.
Present candidates with structured challenge responses and documented evidence. Walk into client meetings with proof, not promises.
Every step feeds the next. Before you pick up the phone, you already know who is worth calling and what to ask.
The hiring manager defines what great looks like for this specific role. What does success look like in 6 months? What separates a good hire from a bad one? These inputs structure every question the candidate will face and every criteria the screener will evaluate against. The screen starts with the person who knows the role best.
Not a generic assessment. Not a video interview. A text-based conversation personalized from the candidate's own background. Each question references their previous answer, creating a thread only they can navigate. For someone with real experience, talking about their own work is natural. Candidates who do the work of engaging stand out from candidates who just submitted a resume.
Screening runs on CV and conversation data combined. Not keyword matching on polished resumes. The result is a shorter list of candidates who engaged with the role and showed specifics about their experience. No candidate gets auto-rejected. Your team makes every decision.
The recruiter has the candidate's conversation data, AI-generated questions that probe gaps, real-time consistency checking, and a criteria coverage checklist. The human reads the room. The AI provides structure. Nothing gets missed.
After the call, the system produces a structured summary. What was confirmed across the conversation and the call. What gaps remain. What to probe in the next round. Your decision, with the full picture. Exports directly to your ATS.
Candidates answer real questions before you ever pick up the phone. When you do call, you already know what to ask.
Not a generic assessment. Not a video interview. A text-based conversation personalized from the candidate's own background. Each question references their previous answer, creating a thread only they can navigate. Candidates who do the work of engaging stand out from candidates who just submitted a resume.
Screening runs on CV and conversation data combined. Not keyword matching on polished resumes. The result is a shorter list of candidates who engaged with the role, showed specifics about their experience, and completed every question. No candidate gets auto-rejected. Your team makes every decision.
Questions are personalized from the candidate's actual experience. Each follow-up references the previous answer. Candidates cannot template their way through. But for someone with real experience, talking about their own work is natural. The format favors depth, not rehearsal.
Real-time AI support during the call. Questions generated from this candidate's conversation data, not a generic template. Live consistency checking between what they wrote and what they say. A qualifying criteria checklist that ensures full coverage. The recruiter runs the call. AI provides the context.
Works with Greenhouse, Ashby, Lever, or no ATS at all. Response analysis, batch processing, conversational AI. No new dashboard to learn. No data written back to your ATS. Read-only, always.
Analysis runs, then source data is discarded. No candidate profiles stored. No PII liability. When the recruiter reviews the analysis, it lives in their ATS, not ours.
Every screening call produces a structured summary: what was verified, what gaps remain, and what to probe in the next interview. Notes feed directly into your ATS. No more post-call write-ups from memory.