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Evalgist Shortlist · AI resume screening

AI resume screening you can defend

Upload the vacancy and the applications. Compare everyone against the same criteria. Shortlist with the evidence open — and keep a record of the decision.

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15 free resume analyses No payment details required No subscription

How Evalgist Shortlist shows the evidence behind each shortlist

3 candidates
AI match:Suggested matchReviewer decision: Shortlisted1 / 3

Dr. S. Chen

Gist

All three required criteria are met with direct quotes. Strongest research record in the batch: 12 peer-reviewed papers, 4 years of teaching.

Criteria

3 met

Required criteria

PhD in Computer ScienceEvidence found
PhD in Computer Science, 2017. Thesis on distributed model inference.
Source:From resume
Teaching experienceEvidence found
Since 2019 I have taught the undergraduate algorithms course, covering lectures and exam design.
Source:From resume
Published researchEvidence found
12 peer-reviewed publications, including two journal articles as first author.
Source:From resume

J. Smith

Gist

PhD met with a direct quote. Teaching is limited to one semester as an assistant, and no publications were found in the resume.

Criteria

1 met, 1 partial, 1 not met

Required criteria

PhD in Computer ScienceEvidence found
Completed my PhD in Computer Science in 2021.
Source:From resume
Teaching experiencePartial evidence
Alongside my research I worked as a teaching assistant for Introduction to Programming (one semester).
Source:From resume
Published researchNo quote found

No matching line found in the resume.

M. Johnson

Gist

PhD is in an adjacent field. No teaching record and no publications were found, so two of three required criteria are unsupported.

Criteria

1 partial, 2 not met

Required criteria

PhD in Computer SciencePartial evidence
PhD in Computational Biology, 2019.
Source:From resume
Teaching experienceNo quote found

No matching line found in the resume.

Published researchNo quote found

No matching line found in the resume.

AI-assisted evaluation. The hiring decision is yours.

The job

Two hundred applications. One call to defend.

A role goes out and hundreds of applications come back. Nobody has time to read them all with equal attention, so the triage happens fast — and later, someone asks why a candidate did not make the list.

Shortlist does the reading at one standard. Every application is held against the same criteria, every match carries its quote, and the reasoning is on paper before the meeting starts. You still make the call. You just no longer have to reconstruct it.

How it works

From stack to shortlist in five steps

  1. 01

    Upload the vacancy and the applications

    One vacancy, the whole stack of resumes. PDFs and scans both work.

  2. 02

    Confirm the criteria

    Shortlist extracts the qualifications from your vacancy text. Edit them, add your own, and lock the set before anything is scored.

  3. 03

    Every resume, the same standard

    Each application is compared against the same criteria. For every match, the supporting line from the resume is captured.

  4. 04

    Shortlist with the evidence open

    Candidates are ranked by matched criteria. Open any judgment and the resume quote behind it is right there.

  5. 05

    Export the report

    A per-candidate breakdown with quotes, as a PDF you can bring to the committee or attach to the file.

The alternative

Why not ChatGPT and a spreadsheet?

A chat can score one resume. It will not hold one standard across two hundred, or hand you a packet for the meeting.

One standard, not two hundred

A chat re-interprets the criteria with every prompt. Shortlist locks the set once and applies it to every application in the batch.

Quotes, not summaries

A spreadsheet holds your verdicts; it does not hold the evidence. Every Shortlist match cites the resume line it rests on — or says that no quote was found.

A packet, not a scrollback

When the decision is questioned, a chat history is not an answer. The exportable report shows the criteria, the evidence, and the human call.

What you walk away with

A record that outlives the meeting

  • A ranked shortlist with each candidate's matched, partial, and missing criteria.
  • The literal resume quote behind every match — including where no evidence was found.
  • A per-candidate PDF report you can share with the committee, file with the decision, or send upward when the question comes.
Download the sample report

Exported by the product itself, from fictional candidates.

Pricing

Start free, then pay per resume

15 free resume analyses to begin. After that, buy evaluation credits as you need them. One credit analyses one resume; scanned or image-based resumes cost two. No subscription.

Starter

€5

25 credits · €0.20 per resume

~25 resumes

Recommended

Standard

€15

100 credits · €0.15 per resume

~100 resumes

Bulk

€60

500 credits · €0.12 per resume

~500 resumes

Prices in EUR, billed by Evalgist BV (Belgium). VAT added where applicable.

Get started free

15 free resume analyses No payment details required No subscription

Questions, answered.

What is Evalgist Shortlist?
Evalgist Shortlist is an AI resume screening tool. It extracts qualifications from your vacancy text, lets you add extra criteria, and compares each candidate against the same set. For every match, it shows the supporting quote from the candidate's own resume. Candidates are ranked by the number of matched criteria, and you decide who to shortlist.
Who is Evalgist Shortlist for?
Hiring managers, selection committees, and panels evaluating a batch of applications against the same criteria — anywhere they need to explain the outcome afterwards. Many start from an ad-hoc chat-assistant workflow; Shortlist replaces it with one criteria set, quoted evidence, and an exportable record.
How is this different from using ChatGPT?
A chat can score one resume at a time, but it re-interprets the standard with every prompt and leaves no record. Shortlist holds one criteria set across the whole batch, cites the resume line behind every match, and produces a report you can share with the committee.
What happens to uploaded documents?
Documents are stored in EU-controlled projects, and AI requests are routed through OpenRouter with zero-data-retention routing enabled. Extracted resume text is deleted immediately after analysis; the original upload is kept for up to 14 days for recovery and support, then deleted automatically. The evaluation result and its evidence quotes remain until you delete the job or your account. Full details are in the privacy notice and subprocessor register.
How much does Evalgist Shortlist cost?
You start with 15 free resume analyses without entering payment details. After that, you buy evaluation credit bundles as needed, priced in EUR. There is no subscription or paid licence commitment.
Get started free

15 free resume analyses No payment details required No subscription