Beyond keyword matching. How well do you actually fit?
See how your experience level, skills depth, qualifications, and career trajectory align with what the job actually requires. Detailed fit analysis, not just a percentage.
On signup. No card required.
Per full optimization.
Your resume is encrypted at rest, processed only for your active request, never used as model training data, deletable on demand.
Four dimensions of fit, evaluated independently.
The match analysis evaluates four dimensions of fit. Each dimension contributes to the overall score, but they are also reported separately so you can see where you are strong and where gaps exist.
The result is more diagnostic than verdict-style. A 75% match doesn't mean a 75% chance of getting the job — it means your resume currently demonstrates 75% of what the posting asks for in terms of skills, experience, and qualifications. The remaining 25% is either a genuine gap or experience you have but haven't expressed in resume terms.
Four signals.
Reported independently so you can see exactly where the gap is.
Which required and preferred skills from the posting appear in your resume, and in what context. A skill mentioned in a work experience bullet ("Deployed Kubernetes clusters for production workloads") scores higher than the same skill in a bare list ("Kubernetes"). The analysis also considers skill adjacency: if you list Docker and container orchestration but not Kubernetes specifically, that partial match is noted.
Whether your years of experience and the seniority implied by your job titles match what the posting asks for. A "Senior" title on your resume paired with a "Junior" role posting flags a potential mismatch. Years of experience are estimated from employment dates and compared against the posting's stated requirements.
Education requirements, certifications, and credential matches. If the posting requires a specific degree or certification, the analysis checks for it. It also distinguishes "required" from "preferred" qualifications based on the posting's language. A missing preferred qualification is flagged differently from a missing required one.
Whether your career progression suggests a natural path toward the target role. A product manager role is a logical next step for someone with a background in product analysis and UX research. Less obvious for someone whose last three roles were in accounting. The analysis looks at role titles, industry consistency, and progression patterns.
Three things no automated analysis can read.
Use the score as a diagnostic, not a verdict. These signals matter to hiring managers but are invisible to any algorithm.
Context and impact are hard to quantify
"Led a team of 50 engineers" and "Managed engineering team" contain similar keywords but represent very different levels of experience. The match score can detect that "team leadership" is mentioned. It cannot reliably assess the scale or impact from resume text alone.
Company and industry reputation matter
A hiring manager reads "Software Engineer at Google" and "Software Engineer at a 5-person startup" very differently, even if the resume content is similar. Automated matching cannot fully account for this kind of contextual signal.
Cultural fit is entirely invisible
Whether you would thrive in the company's environment is not something a resume analysis can determine. Some companies value startup experience; others prefer candidates from structured corporate environments. The match score addresses qualifications and skills, not cultural alignment.
Pick the lens that matches your question.
Ajusta offers four analyses. Each is useful at a different point in the application workflow.
ATS Resume Scanner
OpenUse when you need to know if your resume will pass automated filters. Best before submitting to large companies that use ATS screening.
Resume Keyword Checker
OpenUse when you want a focused look at keyword coverage. Best for tailoring your resume's language to a specific posting.
Resume Format Checker
OpenUse when you suspect formatting issues are causing problems. Best for resumes with complex layouts, columns, or non-standard designs.
Job Match Score▸ This tool
Use when you want to understand overall fit for a role. Best for deciding whether to invest time in a full application or for identifying which aspects of your background to emphasize.
Frequently asked questions.
Common questions about this tool. Email hi@ajusta.ai if yours isn't here.
An ATS score measures whether your resume will pass automated filters: keywords present, format parseable, sections detectable. A job match score evaluates how well your background aligns with the role: experience level, skills depth, career trajectory, qualification fit. You can have a high ATS score (resume passes filters) but a low match score (you're not a strong fit for the role).
It can inform that decision, but it should not be the sole factor. A 40% match might mean you lack specific technical skills the role requires, or it might mean your resume does not express relevant experience using the posting's terminology. The score identifies gaps; whether those gaps are real or just presentation issues is something you assess.
Career changers typically score lower because their experience uses different terminology than the target role. This does not necessarily mean you're unqualified. The suggestions will show which transferable skills to highlight and which role-specific terms to incorporate.
To a limited degree. If the posting specifies "3-5 years" and your resume shows 15, the analysis flags a potential mismatch. Some employers filter for overqualified candidates just as they filter for underqualified ones. The score reflects the possibility, though overqualification is ultimately a subjective judgment that varies by employer.
See how you match.
Upload your resume and paste a job description. The analysis takes about 30 seconds and breaks down your fit across four dimensions. Free first run for new accounts.