Before any human opens your CV, an Application Tracking System screens hundreds of candidates per role and silently rejects most of them. Jobyr decodes the vacancy, rebuilds your CV and motivation around the exact employer, validates that it passes ATS, and gets you in front of fresh matching roles before everyone else.
Every CV and motivation is rebuilt around the actual vacancy: required skills, keywords, template structure - the exact signals the ATS scores against.
After every generation we re-run Check Fit against the new CV and show you a measurable improvement vs the original. No guessing whether it actually got better.
When a new matching vacancy goes live - for example C++ developer in Vienna - the pipeline runs and auto-apply submits prepared documents while everyone else is still copy-pasting.
Modern hiring runs on Application Tracking Systems. Every vacancy collects hundreds or thousands of CVs and the ATS automatically scores each one against the role: template structure, formatting, required skills, keywords. CVs that miss the signals are silently filtered out and a real human never sees them. The CVs that do pass get about 7 seconds of attention from a recruiter before a yes-or-no decision. The problem is not your experience. The problem is that your CV never reaches the human who could appreciate it.
Research, fit analysis, targeted generation, and validation work together to increase the chance that the right human sees the right version of your story.
Paste a job link or pick a fresh role from our continuously refreshed vacancy database. Every pipeline starts from a real, specific employer - never from a generic template.
An AI agent runs deep research on the company and the role and assembles a clean report: business context, stack, expectations, culture - everything you need before touching the CV.
Compare role requirements against your current CV. See exactly which skills are missing, where the gaps are, and how to close them before generating anything.
Choose template, language, and optimization degree. Moderate adoption frames missing skills as 'in progress, willing to learn'. Strong adoption claims and justifies them through your existing experience. You stay in control.
Edit the result manually, or just tell the AI agent in a chat what to change. The new PDF recompiles instantly and is ready to preview and download.
Configure a pipeline once, then let it auto-apply when a fresh matching role appears - for example a new C++ developer role in Vienna - so you are the first applicant in the queue, not the hundredth.
Each stage removes guesswork, improves signal quality, and prepares you to move faster on the next matching role.
Paste a vacancy URL or pick one from our fresh job database. The pipeline locks onto a real employer instead of a generic dream.
An AI agent runs deep research on the company and the role and gives you a full report: stack, business context, culture, expectations.
Compare requirements against your CV. See missing skills, weak signals, and a concrete plan for how to improve before generating anything.
Choose template, language, and optimization degree - from light styling tweaks to strong adoption where the AI claims and justifies missing skills through your real experience.
Edit by hand or ask the AI agent in chat to make changes. The new PDF recompiles instantly and is ready to preview and download.
Re-run Check Fit on the new CV and see a measurable improvement vs the original. Proof, not promises, before the application leaves your hands.
Send manually, or let the configured pipeline auto-apply when a fresh matching vacancy appears. Example: a new C++ role in Vienna goes live at 09:14 - your application is in by 09:15.
This showcase is built from real pipeline runs: pick a role, see the company research, the Check Fit gap analysis, the generated CV and motivation, the fine-tune iteration, and the validation that the new version is measurably stronger than the original.
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No empty subscription. You spend credits when the pipeline does real work for a real vacancy. Top up when you want more capacity, stop when you have an offer.
Spend credits per pipeline stage: research, fit, generation, fine tune, validation, auto-apply.
Top up with card or crypto whenever you need more application capacity.
Free tier lets you try the full pipeline on at least one real vacancy before paying anything.
Honest model: the more real applications you push through the pipeline, the more value you extract.
The pricing story should reinforce the product story: pay for meaningful ATS and application work, keep control over output, and scale when needed.
The full per-vacancy pipeline is live today: research, Check Fit, generation, fine tune, validation, manual or assisted apply. The next layer is continuous market watch: when a fresh role matches your search, the pipeline runs and auto-apply submits while you sleep.
Add a job, get deep company research, run Check Fit, generate ATS-aware CV and motivation, fine tune in chat, validate the improvement, and apply.
Define a search like 'C++ developer in Vienna'. The system watches the market, runs the pipeline the moment a fresh matching role appears, and submits a tailored application before the queue fills up.
Saved company reports, reusable optimization profiles, and learned recruiter preferences so every next matching vacancy is even faster and more targeted.
This story must stay commercially strong and technically honest. The current platform already builds the research and document assets; the bigger future layer is reacting faster to the right fresh vacancy under user guardrails.
Join auto-apply early accessATS stands for Application Tracking System. It is the software employers use to receive and pre-screen hundreds or thousands of CVs per role. It scores each CV against the vacancy: template structure, formatting, required skills, keywords. CVs that miss the signals are auto-rejected and never reach a human. Jobyr rebuilds your CV around the exact role so it passes that gate.
On the CVs that pass the ATS, yes - studies consistently land around the 6-8 second range for the first scan. That is why every line of your CV has to push the right signal for that specific employer. Generic CVs lose this scan; tailored CVs survive it.
Moderate adoption: when a required skill is missing from your CV, the AI frames it as 'in progress, willing to learn'. Strong adoption: the AI claims the skill is present and justifies it through your existing experience and projects. You pick the level per pipeline, so the level of risk and aggressiveness stays under your control.
Yes. Fine Tune supports both manual edits and a chat with the AI agent. After every change the new PDF recompiles instantly and is immediately ready to preview and download.
Only inside pipelines you explicitly configure for it. You define the search criteria, the optimization degree, and which document package to use - generated by Jobyr or your own prepared one. Outside those rules, nothing is sent automatically.
Contact and legal trust surfaces should reduce friction and support conversion, especially for candidates who want to understand the ATS and automation angle before joining.
Donation and utility surfaces can exist, but they should not disrupt the main sales path. That means quiet placement, clean hierarchy, and no competition with the primary CTA.
Run the full pipeline on a real vacancy in minutes: deep research, Check Fit, generated CV and motivation, fine tune in chat, validation, and a clean apply.