For hiring teams

Hire on evidence, not resumes.

Every candidate has already interviewed. You see clear, approved proof of how they actually work. Never a resume pile, never their raw transcript.

See the dashboard

Bias-audited & contestable · LL144 and EU AI Act aligned.

Matched to your roles · sample

  • AS

    Aisha S. · ML Engineer

    matched on: structured debugging

    94%
  • RV

    Rahul V. · Backend

    matched on: systems ownership

    91%
  • MK

    Meera K. · Platform

    matched on: reliability under load

    88%
Defensible hiring NYC Local Law 144 EU AI Act aligned Bias-audited & contestable
The triage problem

You're hiring from a guess.

A resume only tells you what someone claims, in a format a filter can reject before anyone reads it. So the person you hire is often the one who wrote the best document, not the one who does the best work.

  • 300+ resumes per role

  • 20s each gets, at best

  • 1 hire — mostly on a guess

Your resume pile

312 · unread
  • 312 applications

    one open role

    Buried
  • ~20 seconds

    average resume scan

    Skimmed
  • Keyword-first

    filters before humans

    Filtered
  • Great people

    screened out on format

    Filtered
  • The one you want

    somewhere in the pile

    Buried
  • + 307 more you'll never open
What you see

Approved signal. Never the raw interview.

You get evidence a hiring manager can defend: every trait backed by the candidate's own words. The full transcript stays sealed, so your process stays fair and easy to defend.

Candidate evidence, visible to you

94%Structured debugging

I bisect the failure — reproduce it, then halve the surface until the cause is isolated.

89%Handling ambiguity

When the spec was unclear I wrote down my assumptions and confirmed them before building.

91%Ownership

I shipped the fix, then added the alert so it couldn't fail silently again.

What you never see

Raw transcript · sealed

Candidates approve what they share. You never handle unfiltered, off-the-record answers, which keeps you clear of bias and privacy risk.

How it works for teams

From open role to warm intro.

Read how each candidate actually thinks. Traits backed by their own words, ranked by fit. Never a raw transcript.

  • Every score is sourced
  • Defensible to hiring managers
  • Bias-audited & contestable
Your shortlist, pre-interviewed

Ranked on proof, with the reason.

Each candidate comes with why they fit — the exact evidence, not a keyword overlap. Sample profiles shown.

AS

Aisha S.

ML Engineer · 4 yrs · remote

94%

match

Verified via interviewStructured debuggingAmbiguity

Why they fit: reasoned cleanly through an under-specified failure, stated assumptions first

Built to be trusted

Fast to hire. Safe to defend.

Speed means nothing if you can't defend the hire later. On Placedon, every decision is backed by evidence you can point to, and a candidate can challenge.

Voices from hiring teams

Signal people can stand behind.

  • We stopped shortlisting on keywords and started reading how people actually reason. Our first two Placedon hires were people we'd have filtered out on paper.

    Dana Okafor

    Head of Talent · Meridian

  • The trait scores link straight to the moment in the interview. When a hiring manager pushes back, I show them the exact answer. No more black box.

    Ravi Menon

    Talent Partner · Cortex

  • No timer, no trick questions, and I could see every trait it pulled — and contest one. First interview in years that felt like it was actually listening.

    Sofia Lindqvist

    Candidate · placed at Lumen

Questions

What hiring teams ask.

Every candidate completes an interview before they ever reach you. We turn that conversation into traits, each backed by their own words. So what you see is proven, not just claimed.

No setup fee · cancel anytime

Stop guessing from resumes.

Give one team one week. Watch how fast “who should we talk to?” gets an honest answer.

Every score is bias-audited and contestable.