Your application lands in a system, not an inbox
At larger companies the CV goes into an applicant tracking system. Before anyone opens it, the document is taken apart into data: job titles, employment periods, education, skills.
Method
What this analysis actually does
No magic and no “artificial intelligence” standing in for an explanation. Below is how the mechanism works, so you can judge how much to trust the result.
What happens after you click “Apply”
Software reads your CV first.
And it decides whether a person ever will.
The parser reads text, not design
Two columns, a table, an icon instead of the word “phone”, dates without months — each of these leaves a database field empty or fills it with the wrong thing. A striking template is often the biggest enemy here.
Candidates get ranked
The system compares what it read with the requirements from the posting and sorts the list. The recruiter starts at the top and rarely reaches the bottom. A good CV further down loses to a weaker one that answers the posting better.
This is not about tricking the algorithm. It is about making sure it sees what you can actually do.
How it works
Three steps, no sales call
The whole process happens on one page. There is no contact form, no callback and no “introductory consultation package”.
- 01
You add your CV and the posting
≈ 30 secondsYour CV — as a PDF or DOCX file, or pasted as text — and the job posting. No account, no email address.
- 02
The analysis compares them word by word
≈ 15 secondsThe engine pulls the required skills out of the posting, weights them by the section they appeared in, then looks for them in your CV — telling a claim apart from evidence.
- 03
You get a list of concrete moves
instantlyNot “add keywords”, but: this word, in this place, in this sentence. Plus rewritten experience bullets and a list of formatting problems.
Four decisions that make the difference
Why the result holds up
Weights instead of plain counting
A skill from the “Requirements” section weighs three times as much as the same skill mentioned in the company description. The “What we offer” and “Recruitment process” sections weigh zero — otherwise the tool would tell you to add a gym card to your CV.
Word forms, not literal matching
“Team management”, “managed a team” and “managing teams” are one skill. The engine reduces words to stems using the inflection rules of each of the seven supported languages — including consonant changes.
A claim is not evidence
A skill listed only in the skills section is marked “unsupported” and counts half as much as one that appears in an experience bullet. The filter lets both through — the recruiter only one.
Fixes that do not need fixing
Rewritten sentences are checked for grammar. Where changing the verb would require a different case on the object and the number cannot be determined, you get a bracketed fragment instead of a guess. Grammatical gender is read from your CV.
Report excerpt
This is the answer you get
Below is a real excerpt from the analysis of a marketing specialist's CV set against an e-commerce job posting.
What is missing
4 of 20 skills- Google Analyticsrequired
From the posting: „Strong command of Google Ads and Google Analytics (GA4)”
- SEOrequired
From the posting: „Hands-on knowledge of SEO and visibility analysis tools”
- Pivot tablesrequired
From the posting: „Data analysis skills (Excel, pivot tables)”
- Google Tag Managernice to have
From the posting: „Experience with Google Tag Manager”
The format as the parser sees it
- Document length — 163 words — too short to cover the requirements
- Readable employment periods — 1 date range without a month
- Standard section headings — all three found
- Contact details in the text — email, phone, profile
One bullet, before and after
Your version
Worked on preparing social media content and the newsletter
Suggestion
Prepared [social media content] and the newsletter, which delivered [measurable result]
“Worked on” is the most common phrase in CVs and the weakest — it says nothing about the outcome. You fill the bracketed parts in with your own numbers.
What you get
Specifics you can paste straight into your CV
Requirement coverage in percent
One number that tells you how close you are. Weighted: a skill from the “Requirements” section counts three times as much as a mention in the company blurb. Perks do not count at all.
Gaps split by weight
Explicit requirements on one side, nice-to-haves on the other. Every gap comes with the sentence from the posting it came from.
Rewritten experience bullets
“Responsible for running campaigns” → “Ran campaigns in Google Ads, which delivered…”. Actual sentences from your CV, not generic advice.
ATS format checks
Twelve checks that decide whether a parser can read the document at all: column layout, icons, date format, section names, contact details.
Cover letter for the posting
A draft built from your real achievements and the requirements in the posting. Everything we do not know is marked — we never invent your motivation.
Your CV stays yours
The text is processed in memory for the length of one request. We do not store it in a database, we do not log its content and we do not send it anywhere.
Limits
What this tool will not do
- We do not know which system a given company uses — we analyse what all parsers have in common.
- With pasted text we cannot see problems caused by the file itself — a scan instead of text, or text converted to outlines, only shows up when you upload the CV as a PDF.
- We cannot judge whether what you wrote is true. The report shows the match, not your skills.
- We cannot guarantee an interview. We remove one obstacle out of several.
We say this plainly, because a tool that promises a job is easier to sell and useless in practice.
Check one job posting.
It takes less than a coffee break.
The first analysis costs nothing and needs no account. If the score surprises you, you will already have the list of what to fix.