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Our approach

A resume is a pitch.
A conversation is evidence.

Most hiring software decides whether to keep reading based on how well someone wrote a document about themselves. We think that throws away the wrong people, quietly, at scale. So we ask them instead — and hand your team what they said.

Try it on one roleBook a walkthroughor book a walkthrough →

Two weeks, your own applicants, no card.

Fifteen minutes of someone explaining their own work.

What we are arguing with

The first cut is the one nobody watches.

By the time a human opens your pipeline, most of the people who applied are already gone — removed by a keyword threshold, before anyone formed an opinion about them. Both of these are screening. Only one of them leaves something behind.

The keyword pass

  1. 01

    The resume is flattened into a bag of words.

  2. 02

    The words are counted against a list somebody wrote once.

  3. 03

    Under the threshold, the application is closed automatically.

  4. 04

    Nobody reads it. Nobody hears about it. There is nothing to appeal.

The conversation

  1. 01

    The applicant explains their work, out loud, in their own words.

  2. 02

    The AI follows up on what they actually said — not on a script.

  3. 03

    Answers are read against the requirements you wrote, in sentences.

  4. 04

    You get the transcript, the reasoning, and the call.

Line by line

What actually changes.

Keyword screening compared with an AI conversation, across six aspects of hiring.
AspectKeyword screeningA conversation
What is being judged

How well someone writes a document about themselves

How someone explains work they have actually done

Who gets through

People who know the format, and people who game it

People who can do the job and can say how

What you have to decide from

A match percentage with nothing behind it

The quoted line, the recording, and the reasoning

What the candidate gets

Silence, usually forever

Feedback, a transcript, and skill proofs they keep

Where bias creeps in

A keyword list built from who you hired before

The same questions and the same rubric for everyone

Who ends the application

The software, silently

A person on your team, on the record

None of this makes the machine the judge. It makes the machine the part that reads everything, so the person doing the judging gets to spend their attention on the six people it is actually about.

Everyone deserves the chance
to explain themselves out loud.

A resume cannot show how somebody thinks through a problem, what they do when they are wrong, or what they learned from the job they left off it. Fifteen minutes of them talking can.

Which is also why a Tukadi interview gives something back whether or not it ends in an offer: answer-by-answer feedback, the transcript, and skill proofs the candidate keeps. Fifteen minutes of someone’s life should not be worth nothing to them.

Where the line sits

The machine reads and listens. The person decides.

There is exactly one place in this where a decision gets made, and it is not inside the model. Everything before it is preparation for a human being who has the whole file open.

Two rooms, and only one of them has a person in it who can end an application.

  1. 01the machine

    It reads every application against your words

    You describe what the role needs in sentences, not boolean strings. Every resume that arrives is read against them, and each requirement comes back either met — with the line that proves it — or not, with how certain the AI is either way.

    • Plain-English criteria
    • Quoted, not paraphrased
  2. 02the machine

    It has the conversation you do not have time for

    A voice interview that follows what the candidate actually says. Every score points back at the moment in the transcript it came from, so nothing is a number you have to take on trust.

    • Same questions for everyone
    • Recording and transcript
  3. 03you

    You decide, and it is written down

    Nobody is ever rejected by the machine. Ineligible is not a decision and uncertain is not a decision — the application stops, is marked for review, and waits for someone on your team. Who decided, and when, is on the record permanently.

    • Needs review, not rejected
    • Audited, with a name on it

Being straight about it

What we do not claim.

We think a conversation beats a keyword count. We do not think the conversation is infallible, and a vendor who tells you their AI has no failure modes has told you something about the vendor.

The AI mishears people.

Accents, crosstalk, a bad connection, an answer that needed context it did not have. It happens, and it is why nothing it produces is a decision on its own.

It does not judge the things people care most about.

Whether someone will be good for a team, whether they will grow into a role, whether you want to work with them. A conversation with the machine cannot settle any of that.

We are early, and small.

Our first customers are shaping what this becomes. That means you get a say; it also means you are not buying a decade-old product.

The full version of this — what we log, what we keep, what candidates can ask for and how — is on the trust and compliance page, and what the AI does and does not do is set out in the AI disclosure.

See it on your own people

Arguments are cheap. Run it on a real role.

Take the opening that has been open too long, put it through Tukadi for two weeks, and read what comes back. If the transcripts do not tell you something the resumes did not, you will know quickly.

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Tukadi

The machine does the reading and the listening. People still decide.

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