Every applicant arrives
already interviewed.
Kanvis interviews everyone who applies — against the criteria you set — and hands you verdicts with the evidence attached. You spend your day deciding, not screening.
Post a role in one conversation · No ATS migration · Live today
Senior Backend Engineer
28 applicants · 28 interviewed · 0 unread
- MCShortlist
Mei C.
Staff Engineer · 9 yrs
Ran the Postgres shard migration she describes — evidence linked
- MRShortlist
Marcus R.
Senior Engineer · 7 yrs
Owned on-call for a 40M-req/day service; depth confirmed in interview
- NHBackup
Noor H.
Lead Developer · 6 yrs
Strong systems answers, no production Kubernetes — your must-have
- PSBackup
Priya S.
Platform Engineer · 5 yrs
Interview surfaced infra work the résumé never mentioned
Ask the shortlist
“Which of these have actually run Postgres at scale?”
Mei and Marcus both have — Mei led a shard migration on a 4TB cluster, Marcus ran the read-replica failover work. Noor’s Postgres experience is single-instance only.
What one open role costs you
≈250
résumés arrive for a single corporate opening
Glassdoor
55%
of applicants never hear back — usually because nobody had time
Resume Genius, 2026
11,000/min
applications hit LinkedIn every minute
LinkedIn, 2026
You can't hire your way out of volume — the screening cost scales with it. Kanvis changes the unit instead: every applicant arrives as an interview, not a document.
How it works
Four steps between an open role and a defensible shortlist.
Describe the role the way you'd describe it to a colleague
No form. The Job Builder asks what someone actually has to have done, turns it into a structured JD, and keeps a separate set of private criteria that candidates never see and no agent ever quotes back.
Job Builder
What does someone need to have actually done to succeed here?
Owned a service in production. Postgres at real scale. I don’t care about the degree.
Noted. I’ll treat production ownership and Postgres depth as must-haves and drop education from scoring.
Private criteria · never shown to candidates
Prefer someone who’s survived an on-call rotation. Avoid pure agency backgrounds.
Every applicant gets the same real interview
Not a knockout quiz. A short conversation that starts from what their profile already proves, goes after the gaps your criteria care about, and asks follow-ups when an answer is thin.
Application interview · candidate side
Your profile shows you led the migration off the monolith. What broke that you didn’t expect?
Connection pooling. We hit the Postgres ceiling at ~400 concurrent and had to put PgBouncer in front before we could cut over.
Understood — how did you verify the cutover was safe?
One question at a time, about 10 minutes. What gets covered comes from your criteria, decided in advance. The AI chooses the wording, never the ground.
Every score opens up
The conversation and the profile they applied with are graded into a score with a full breakdown behind it. The AI points at the evidence; the number is calculated from it, so the same candidate always scores the same way.
Score breakdown
Every number is calculated from the interview record. The AI points at the evidence; it never picks the score.
- Production ownershipEvidenced
- Postgres at scaleEvidenced
- Kubernetes in prodNot shown
- On-call experienceEvidenced
Decide from a board, not an inbox
Verdicts arrive ranked with reasons attached. Question the shortlist in plain language, keep private notes, and move people through your own stages — all of it invisible to the candidate.
Decision board
One call per applicant — Shortlist, Backup or Reject — taken across the whole pool at once, with each recommendation shown next to the evidence that produced it.
9
Shortlist
12
Backup
7
Reject
The recommendation is advice. The decision — and the record of it — is yours.
Every applicant
Six things you get on every single person who applies.
Not just the ones who make the cut. The applicant you would have skimmed past in four seconds gets the same file as your favourite.
The profile exactly as they applied with it
You review what they actually sent. Edits they make afterwards cannot rewrite the application you scored, so everyone in the pool is judged on the same footing.
The full interview transcript
Every question asked and every answer given, in order. No summary standing in for the conversation.
Evidence links on every claim
Each entry on the profile traces back to the conversation that produced it. A claim without a source is visibly a claim without a source.
A Twin you can interrogate
Ask this specific application anything — “where exactly did they own the deploy pipeline?” — and get an answer grounded in their record, not invented.
Private notes and stages
Your notes, your pipeline stage, your read on the person. There is nowhere in the product a candidate could ever see any of it.
What we learned last time
When someone applies to a second role, answers they already gave carry forward. Your team stops asking the same three questions a good candidate has answered twice.
Built to be defensible
If you have to justify a rejection, you should have the receipts.
AI writes the words. It never picks the number.
Questions are chosen by rules, not improvised. Scores are calculated, not judged. The AI decides how something is worded and points at the evidence behind it — it gets no vote on a number, a verdict, or what happens next.
Everyone is judged on the same record.
An application is fixed at the moment it is submitted — the profile, the role, and your criteria as they stood. A candidate polishing their page next week cannot move a score you have already seen, in either direction.
Your private criteria stay private.
The criteria you would rather not publish never reach a candidate, and are never quoted back to one. They shape the questions asked without ever being visible in them.
Candidate text is evidence, never instructions.
Nothing a candidate writes can change how your side of Kanvis behaves. Their words are read as evidence about them, and only ever as that.
You always know what you are looking at.
Every application on the board says whether its read is complete. You are never shown a confident number without the work behind it.
Kanvis does not replace your interviews. It replaces the first screen — the part where good people are lost to volume.
Pricing
Candidates never pay.
Founding teams don’t either.
Kanvis is built to be paid for by the companies that hire, which is the only way the candidate side can stay free and honest. The teams who come in now run on it at no cost, with everything turned on.
They are also the teams we build the pricing around, and the ones we ask first when we set it.
Founding teams
Freefor founding teams
- Unlimited roles, for as long as you're a founding team
- Every applicant interviewed and scored — no per-candidate metering
- Decision board, Shortlist QA, and per-application Twin
- Your criteria, notes and pipeline stay private to your organisation
- The people building Kanvis on the other end of it
Tell us the role you’re hiring for and we’ll set it up with you.
Does this replace our interviews?
No. It replaces the first screen — the résumé pile and the 20-minute phone call that mostly confirms someone can talk. Your team still runs the real interviews, on a shortlist that arrives with evidence instead of guesses.
Can a candidate game the AI interview?
Answers are graded against the candidate's own verified record, so an impressive claim that nothing in their profile supports doesn't score like a proven one. Nothing a candidate writes can change how your side of Kanvis behaves — their words are read as evidence about them, and only ever as that. And the transcript is right there, so if an answer looks coached, you can see it.
Do candidates know they're being interviewed by AI?
Yes, plainly, before they start. They're told what it's for, it's a conversation rather than a test, and it runs on their time. Hiding it would poison the answers we're asking you to trust.
Do we have to move our ATS?
No. Kanvis runs a role end to end on its own — post it, interview, score, decide — so you can put one requisition through it without touching your existing stack.
Who owns the candidate's data?
The candidate owns their profile and their page. What you see is their application exactly as it stood when they sent it to your role, visible to your organisation only. Your criteria, notes and pipeline stages stay on your side, and a candidate has no way to see any of them.
Who makes the final call?
You do. The score is advice with its reasoning attached, and you can overturn any recommendation on the board. Every number traces back to a specific answer in a specific transcript, so if you disagree with one, you can go and look at why rather than argue with it.
How many roles can we run?
As many as you want. We're deliberately not metering per candidate — the whole point is that the applicant you'd have skimmed past gets interviewed too.
Put one role through it.
See what you’ve been missing.
We’ll set the first one up with you — and you’ll have every applicant interviewed before your next pipeline review.