Hiring tools interrogate candidates.
None cross-examine the job.
MatchCard is AI recruitment built for mutual fit hiring: an AI candidate matching platform that reads both sides of a hire, the candidate's answers for authenticity, and the role itself for whether it's actually good enough for them. Get on the list before we open the doors.
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3 specialist minds
This isn't a hunch. It's already in the data.
Two things are true about hiring right now, and most platforms are only built for one of them.
First: candidates don't trust the systems screening them, and neither do the people running those systems. That's a trust deficit at both ends of the hiring funnel, not a rounding error on one side of it.
Second: the honesty problem is getting worse, not better. Some of that's already happening: 6% of candidates surveyed admit to posing as someone else, or having someone else pose as them, during an interview.
MatchCard exists because of both halves of that problem, not just one. Authenticity detection so a fabricated answer doesn't sail through unnoticed, and a Mutual Fit Engine so the trust gap gets addressed in both directions, not just candidate-to-employer.
Half a hiring decision has been standard for a while.
Most hiring platforms score only whether the candidate fits the role, not whether the role fits the candidate. Every major platform in this category interrogates one direction of the question: is this candidate good enough for us? None of them cross-examine the other half: whether the job is actually good enough for the candidate. That's not a rounding error. It's most of the system, and it's why every hiring tool before this one has only ever told half the story.
- Skills match against the role
- Culture fit, decided on a gut feeling
- Interview performance, scored once
- A resume, tuned to survive a keyword scanner
- Does the role actually pay what they need?
- Does day-to-day match what they were told?
- Is the thing that burned out the last person about to do it again?
- Where is this hire likely to be in six months, and why?
Three minds, obsessively engineered. Not off the shelf.
MatchCard doesn't take an answer at face value. Every response is read, tested, and verified with the same rigour as a serious background check, not left to a single generic model producing one score you're asked to trust blindly. A verdict only ships once it holds up under all three.
What it reveals
Reads for what an answer says about the person behind it, not just the words on the page
What it holds up to
Tests whether an answer holds together the way a genuine one actually does
What it proves
Weighs what's carefully avoided as closely as what's actually said
Every read has been refined against real, messy, evasive answers, not tuned once and shipped. The goal was never a plausible-sounding score. It was a verdict you could defend out loud if a candidate asked you to explain it.
Self-challenged, on every report: before a verdict ships, it's tested against its own strongest counter-argument. If the case against it holds up, the verdict changes.
A bad hire isn't a bad day. It's a five-figure line item.
The US Department of Labor's conservative floor for the cost of a bad hire is 30% of that person's first-year salary, and that's direct replacement cost only. SHRM's fuller accounting runs far higher for mid-level and technical hires, once you count lost productivity, the manager hours spent absorbing the miss, and the rehire itself.
On a £60k role, that's £18k as the optimistic floor, and the realistic range runs well past it. That reframes what a screening stage is for: it's not paperwork before the interview, it's the cheapest point in the entire process to catch a mismatch. Every question MatchCard asks (is the salary expectation actually inside budget, does the day-to-day match what they think they're signing up for, is the six-month outlook a retention story or a repeat of the last exit) is aimed at the mismatch before it becomes the line item.
The half of the scorecard nobody else built.
The Mutual Fit Engine scores every hire in both directions, every time. Not just whether the candidate can do the job, but whether the job will actually keep them.
Likely strong performer, moderate flight risk tied directly to the salary gap above. Worth addressing before the offer, not after.
Candidate needs £68k–£74k. Role budgets £58k–£66k. Gap is real and worth a direct conversation now, while it's cheap to have.
Three moves. No fourth step.
MatchCard works in three steps: paste in the job description, send candidates a link to a role-specific assessment they complete in about fifteen minutes, then read the report. Each report scores authenticity, Mutual Fit, and six-month retention outlook the moment the candidate submits, no manual review pass required.
Paste in the job
The AI builds a set of role-specific Match Cards, not a generic template pulled off a shelf.
Send candidates the link
About fifteen minutes, answered on their own time. No scheduling back-and-forth for a first pass. That matters when 42% of candidates walk away from processes just because scheduling dragged.
Read the report
Verdict, authenticity read, Mutual Fit score, six-month outlook, salary reality: all waiting the moment they submit.
The reaction we're building toward.
We're pre-launch. There's no customer base yet to quote, and we're not going to invent one. These are illustrative: the kind of reaction a Match Card report is designed to earn once real recruiters start using it.
"This told me something about the role, not just the candidate."
"I wish I'd had this before the hire I regretted last quarter."
"The salary flag alone would have saved us a countered offer."
"Finally something that reads the answer instead of scoring the vibe."
"Closer to due diligence than an interview tool."
"The six-month outlook is the bit I didn't know I needed."
We keep building tools that interrogate the candidate. Nobody's built one that holds the job to the same standard.
One Match Card system. Built for the role in front of you.
As a pre-employment assessment, the three-mind read and Mutual Fit Engine work the same way regardless of what you're hiring for. The cards themselves are what change, written around the real responsibilities of the role.
Before you ask, here's what people usually do.
Is MatchCard AI recruitment software?
Yes. MatchCard is AI recruitment software built specifically for UK employers: AI candidate matching that scores both the candidate and the role, rather than the candidate alone. If you're looking for recruitment made easy, or a smarter way to screen than a CV and a gut feeling, this is that, with the honesty checks most AI hiring tools skip.
Does MatchCard replace the interview?
No. It replaces the resume-and-gut-feeling candidate screening stage that happens before an interview. A Match Card report tells you who's worth interviewing and what to actually ask them, instead of guessing from a CV.
How long does a Match Card assessment take a candidate?
Around fifteen minutes. Cards are role-specific scenario questions, not a generic personality quiz, so the time goes toward answers that actually reveal something rather than padding.
Can it actually tell if an answer was written by AI?
Yes. Authenticity detection is built into every answer's read, checking language patterns, specificity, and consistency across everything a candidate submits, not just a single answer in isolation.
What roles and industries does this work for?
Any role where you'd normally write a job-specific interview question: sales, engineering, customer success, finance, HR, marketing and operations are all in active use during early access. The cards are generated from your actual job description, not a fixed template.
How much does a bad hire actually cost?
The US Department of Labor's conservative estimate is 30% of first-year salary in direct replacement costs alone; SHRM puts the fuller figure at 50–150% of annual salary depending on seniority, once lost productivity and rehiring are counted. On a £60k role that's £18k as the floor. That's why catching a mismatch at the screening stage, before an offer exists, is the cheapest intervention in the whole hiring process.
Why score the role as well as the candidate?
Mismatch, not incompetence, drives most early exits. Employers most commonly report 10–25% of new hires leaving within six months, with the role not matching what was described as the leading cause. A candidate who can do the job but was sold a different one still leaves. Scoring both directions, candidate-to-role and role-to-candidate, is how you catch that before the offer, not at the exit interview.
How does MatchCard handle candidate data?
A candidate's answers are used to generate their report and nothing else. They're not sold, shared with third parties, or used to train external AI models. We're finalising formal data-processing documentation ahead of general availability; if you need specifics for your own compliance review before then, ask us directly.
How is this different from an ATS or a personality test?
An ATS tracks candidates through a pipeline; it doesn't judge them. A personality test scores traits in the abstract, disconnected from the actual job. MatchCard sits between the two: role-specific scenario questions, read by AI for authenticity and fit against the real role, not a fixed trait model or a keyword-matched CV.
Does MatchCard integrate with our existing ATS?
During early access, MatchCard runs standalone. You send candidates a link and get a report back, no pipeline migration required. ATS integration is on the roadmap and will be prioritised based on what early-access cohorts actually ask for.
What does early access cost?
We haven't opened pricing publicly yet. It's shared directly with each cohort as early access opens. Joining the waitlist costs nothing and doesn't commit you to anything.
When does early access open?
We're opening in cohorts rather than all at once. Join the list on this page and we'll email you the moment your cohort is ready. That's the only email you'll get from it.
Read the thinking behind the product.
DOL and SHRM figures applied to real UK salaries, and why mismatch (not incompetence) drives the bill.
Read →The four levels of AI-assisted applying, why detectors and proctoring fail, and what catching it actually requires.
Read →Personality tests, skills platforms and ATS screening, honestly compared, including where each one wins.
Compare →30.3% cite misaligned expectations, not skills: the leading cause, ahead of culture fit and onboarding combined.
Read →Schmidt & Hunter's landmark finding: structured interviews are nearly twice as valid as "gut feeling" hiring.
Read →65% of applicants now disappear mid-process. The data-backed reasons, and the fix that actually closes the gap.
Read →Fifteen minutes. One real report. Your actual role.
Early access opens in cohorts. Get on the list and we'll email you the moment yours does. No pitch deck, no sales call to sit through first.
No spam. Just one email when we open your cohort.