AI resume screening
AI resume screening software that shows you why.
Hirevo screens every resume against the role, ranks the candidates who fit, and puts the evidence behind each recommendation where you can inspect it. The analysis is the instrument. The decision stays yours.
Every resume read in fullScored and ranked against the job descriptionA person makes the call
Senior Backend Engineer
Requirements
- Pythoncore
- FastAPIcore
- Distributed systemscore
- Event-driven architecturecore
- Kuberneteslisted
- 01Resume AScreened
- 02Resume BScreened
- 03Resume CScreening
- 04Resume DQueued
- 05Resume EQueued
… and 7 more · every one read in full
- PythonExperience · role 1, 2
- FastAPIExperience · role 1
- Distributed systemsExperience · role 2
- Event-driven architectureProjects · 1
- Kubernetesmissing
Event-driven architecture · matched
“Built high-volume event pipelines…”
Related line · matched by wording
Kubernetes · missing
Not found in any held role or project. Listed as a gap for a recruiter to weigh.
The definition
What is AI resume screening?
AI resume screening is software that reads resumes and evaluates each candidate against a role, instead of filtering them on keywords or leaving the pile to be skimmed by hand. Hirevo reads every resume you upload in full, screens it against the job description, scores and ranks the candidates against the role’s requirements, and shows the reasoning and the resume evidence behind each result. A recruiter reviews the analysis and makes the decision.
- Input
- A role with its job description, and the resumes for it, uploaded directly.
- Standard
- The job description. There is no mode that scores a resume without a role.
- Output
- A job match score and category, matched and missing skills, strengths, gaps, and a recommendation with its evidence.
- Decision
- The recruiter’s. Hirevo recommends; nothing is rejected automatically.
How AI resume screening works in Hirevo
- 01
Understand the role
Screening starts from the job description, not from the resumes. You create a role and give Hirevo the description it will read every candidate against, so the requirements are fixed before the first resume arrives.
- 02
Read the resumes
Upload the resumes for the role. Each one is parsed and read in full — experience, skills, projects, education — with no keyword pre-filter deciding which ones get looked at.
- 03
Match candidates to the role
Each resume is analysed against the role’s requirements: which skills match, which are missing, how relevant the experience is, and which projects actually support what the role asks for.
- 04
Show the supporting evidence
Every recommendation carries its explanation, its strengths and its gaps. In deep review, each strength and risk sits beside the resume lines related to it, matched by wording, and low confidence is shown rather than hidden.
- 05
Score and rank
The analysis produces a job match score from 0 to 100 and a match category for every candidate, and the role’s pipeline is ranked from those results. Triage surfaces the candidates who meet the bar for a closer look.
- 06
The recruiter decides
Hirevo recommends; a person approves. The decision is recorded with who made it and on what basis, and it stays reversible for 30 days. Nothing is rejected automatically.
Screening a resume against a job description is what every analysis does; there is no mode in which Hirevo scores a resume without a role. The one exception is the ATS score, which measures the resume’s own structure and is reported separately from role fit. If you screen by hand today, our practical guide to screening resumes against a job description sets out the same process step by step, with a checklist to hold any tool to.
Stage 01Understand the role
Start with the role.
Screening starts from the job description, not from the resumes. Hirevo reads the posting for what the role actually requires — the skills, the experience, the level — and that set of requirements is what every resume for the role is screened against. It is fixed before the first resume is read, so the standard does not drift as the pile is worked through.
There is no keyword list to write or maintain. The requirements come from the posting, and a missing core requirement is the first thing triage reports about a resume, so the standard is visible in the result as well as in the setup.
Job description
We are hiring a Senior Backend Engineer to own the services behind our event platform. You will design and run distributed systems in Python (FastAPI), build event-driven pipelines that stay correct under load, and work with the platform team, who run our workloads on Kubernetes.
Requirements · screened against
- PythonSkillcore
- FastAPISkillcore
- Distributed systemsExperiencecore
- Event-driven architectureExperiencecore
- Senior: owns services end to endLevelcore
- KubernetesSkilllisted
Stage 02Read the resumes
Read every resume, not the ones a filter let through.
A role that draws a few hundred resumes cannot be read by one person with the same attention from the first to the last. Somewhere in the middle, screening turns into skimming, and the criteria drift with the reader’s energy. Hirevo reads every resume you upload in full — experience, skills, projects, education — with no keyword pre-filter deciding which ones get looked at.
The first resume and the three-hundredth get the same reading, and every one leaves the queue with the same set of fields filled in.
- 01Resume A2 pages · experience · skills · projects · educationScreened
- 02Resume B3 pages · experience · skills · educationScreened
- 03Resume C1 page · experience · skills · projectsScreened
- 04Resume D2 pages · experience · skills · projects · educationScreening
- 05Resume E4 pages · experience · skills · educationQueued
- 06Resume F2 pages · experience · projectsQueued
… and 6 more · no keyword pre-filter · nothing dropped without a stated reason
Stage 03Match candidates to the role
Match the resume to the requirements, one by one.
Each resume is analysed against the role’s requirements: which skills match, which are missing, how relevant the experience is at this level, and which projects actually support what the role asks for. A match is checked against the resume’s own wording; a miss is recorded as a gap rather than silently counted against the candidate.
- PythonMatchedMentioned in experience
- FastAPIMatchedMentioned in experience
- Distributed systemsMatchedMentioned in experience
- Event-driven architectureMatchedMentioned in a project
- Senior: owns services end to endPartialOwnership stated; scope not
- KubernetesMissingNot found in any role or project
What you get back
The shape of one analysis.
This is what Hirevo returns for every resume screened against a role — the same fields, in the same order, on every candidate. The values are yours to read; none are shown here because none of them would be real.
- Job match score
- 0 – 100, against this role
- Match category
- Excellent · Strong · Moderate · Weak
- Matching skills
- Required by the role, present in the resume
- Missing skills
- Required by the role, absent from the resume
- Experience relevance
- How the experience lines up with the role
- Relevant projects
- Projects that support the requirements
- Less relevant projects
- Projects with limited bearing on the role
- Strengths
- Three to five, written for a recruiter
- Areas for improvement
- Two to four constructive gaps
- Hiring recommendation
- With a short explanation of why
- ATS score
- Resume structure, independent of the role
Beyond keywords
Go beyond keywords.
A filter that matches on terms rewards the resume that used the posting’s vocabulary, not the candidate who did the work, and the strongest person in the pile can be the one whose resume never mentioned the magic word. AI resume screening in Hirevo does not stop at whether a term appears. For each requirement it looks for the experience, project or skill that supports it, shows the related resume lines (matched by wording, not cited), and says what it made of it — so a keyword is the start of a question, not the answer to one.
- Related resume line“Owned the ingestion service across three regions; on call for it for two years.”Experience · role 2 · matched by wording
- InterpretationSupported. Ownership and duration are stated; the requirement is met at the level the role needs.
- Related resume line“Kubernetes” appears once, in the skills list, with no role or project that used it.Skills · list · matched by wording
- InterpretationListed, not evidenced. Reported as a gap to verify rather than as a match.
Hirevo does not claim to understand a resume perfectly. It shows its reading — the related resume line, found by matching wording rather than cited, and what it made of it — so a recruiter can check it, and the parts that come from the model’s reading are presented as such.
Stage 04Show the supporting evidence
Check the evidence against the resume.
Many tools produce a number. Few show what it is made of. When a recruiter cannot see why one resume outranks another, they either trust the number blindly or ignore it — and both defeat the point of screening with AI. Hirevo is built so a recommendation can be investigated: what it rests on, which resume lines relate to it, and what is missing, before anyone acts on it.
Parsed resume · experience
- Senior Software Engineer · 2021 – present
- Built high-volume event pipelines for the payments platform, processing bursts without loss.
- Migrated the ingestion service to an event-driven design with the platform team.
- Led design reviews for two services; mentored one engineer.
- Software Engineer · 2018 – 2021
- Python services with FastAPI; on-call rotation for the order service.
- Strength
- Event-driven architecture at scale, in a held role. Supports two core requirements.
- Related line · Experience · matched by wording
- Gap
- Leadership is described once, without scope. Worth an interview question rather than a deduction.
- Related line · Experience · matched by wording
Every recommendation explains itself
The hiring recommendation is never a bare label. It comes with the explanation that produced it, and with the strengths, gaps, and matching and missing skills the analysis found.
Claims sit beside the resume
From a candidate’s record, each strength and risk is shown with the resume lines related to it — found by matching wording, not cited — so a claim can be checked against what the candidate wrote.
Doubt is shown, not rounded up
Where the analysis is uncertain, the uncertainty is visible. A low-confidence read is presented as one, calmly, rather than dressed up as a verdict.
Stage 05Score and rank
Rank the results.
Every candidate in a role is analysed against the same job description and given a job match score from 0 to 100 and a match category, so the pipeline can be ranked on a consistent basis. Triage surfaces the candidates who meet the bar for a closer look. The order is a ranked view of role fit — a set of signals, not a verdict — and every position in it can be opened to the analysis that produced it.
On consistency, plainly: the requirements come from the job description alone, and the rule-based checks give the same result every run. The parts that come from the model’s reading — matched skills, relevant projects, the written strengths and gaps — can vary between runs, so a job match score can move. A match the resume itself supports is always counted.
- 01Resume A4 of 5 · 1 partialStrong
4 of 5 · 1 partial · Core requirements supported in held roles
- 02Resume D4 of 5Strong
4 of 5 · Full stack match; level implied by title, not scope
- 03Resume B3 of 5Moderate
3 of 5 · Adjacent domain; event-driven work not evidenced
- 04Resume C1 of 5Weak
1 of 5 · A core requirement is missing and nothing adjacent covers it
Stage 06The recruiter decides
Then compare the screened candidates.
Resume-to-job matching gets you to a shortlist. The difference matters when two resumes score close together: being able to see why one candidate ranks above another — and to open the resume behind each claim — is what lets a recruiter defend the choice, or overrule it.
Candidate comparison takes a shortlist of two to five people, ranks them, and writes out the reasoning: who leads, who is the runner-up, how confident the comparison is, and what each candidate’s experience and strengths contribute. How that shortlist is evaluated, ranked and decided is the subject of candidate screening.
- 01Ranked viewEvery screened resume, in order, with its category and its reasons.
- 02CompareTwo to five candidates side by side: role fit, strengths, gaps, evidence.
- 03DecideA person approves. Logged with who and why; reversible for 30 days.
Two ways to screen
AI resume screening and manual screening.
Manual screening is not wrong; it is unrepeatable at volume. The same recruiter, given the same pile twice, produces two shortlists. This is what changes when the reading is done by the software and the deciding stays with the person.
- What gets read
- Manual screeningAs much of the pile as attention allows; the rest is skimmed or sampled.
- HirevoEvery resume, in full, with the same fields filled in for each.
- The standard
- Manual screeningThe role as the reader remembers it that day, which drifts across the pile.
- HirevoThe requirements read from the job description, fixed before the first resume.
- Keywords
- Manual screeningA scan for familiar terms, which favours the resume written for the scan.
- HirevoEach requirement checked against the experience, projects and skills in the resume.
- What you get
- Manual screeningA shortlist and an impression of why.
- HirevoA job match score and category, strengths, gaps, a recommendation, and the related resume lines.
- The decision
- Manual screeningYours.
- HirevoStill yours — recorded with who made it and on what basis, reversible for 30 days.
Hirevo and your ATS
AI resume screening isn’t an ATS.
An applicant tracking system remembers candidates. Hirevo helps you choose one. The two do different jobs, and today they do them separately.
- What is it for?
- An ATSManaging applications and the recruiting workflow around them.
- HirevoAnalysing the candidates in a role and supporting the decision between them.
- What does it know about a candidate?
- An ATSWhat was submitted, where they are in the process, and what has been logged.
- HirevoWhat the resume says, how it matches the role, and what the evidence supports.
- What does it produce?
- An ATSA system of record.
- HirevoA ranked, explained view of role fit that a person decides with.
Hirevo currently operates as a decision layer alongside your existing tools. Resumes are uploaded directly; there are no ATS integrations yet. They are on the roadmap and are not something you have today.
Responsible use
AI assists. Recruiters decide.
Screening with AI only earns its place if the person using it stays in charge of the outcome. That is a design constraint in Hirevo, not a disclaimer.
- Hirevo recommends. It does not make the hiring decision, and it does not reject anyone on its own.
- Our terms require a human to review any decision that materially affects a candidate.
- Every decision is recorded with who made it and on what basis, and stays reversible for 30 days.
- A recommendation can be investigated before it is acted on — the explanation, the strengths and gaps, and the resume behind them.
On bias, honestly: we have not completed a formal bias audit, and we will not claim one until we have. What we do today is structural — every score can be traced to the analysis behind it, low confidence is shown rather than hidden, and nothing is auto-rejected. If you are subject to an audit requirement such as NYC Local Law 144, talk to us before you deploy rather than after.
Who it is for
Who AI resume screening is for.
Recruiters running their own roles
One person, several open roles, and a pile for each. Hirevo reads all of it and brings the candidates worth a closer look to the front, with the reasoning attached.
Talent acquisition teams
A shared organization where recruiters, hiring managers and interviewers see the same analysis, the same evidence, and the same record of who decided what.
Hiring managers
A ranked shortlist you can interrogate rather than a spreadsheet to trust, and interview packs grounded in what each candidate actually claims.
Teams screening at volume
When a role draws hundreds of resumes, reading every one consistently is the whole problem. That is the case Hirevo was built for — and the one the free analyses let you test.
Staffing and recruiting agencies
Agencies screening technical candidates for several clients at once. Each shortlist comes with the reasoning and the resume evidence behind it, so a submission can be explained to a client rather than asserted.
In the product today
Resume screening software, described by what it does for you.
Everything below is in the product today. Which plan includes which capability is set out on the pricing page, generated from the same catalog the product enforces.
- Resume parsing
- Turns each uploaded resume into structured experience, skills, projects and education, so the analysis reads the whole document rather than a keyword extract.
- ATS score
- A structural quality score for the resume on its own — how completely and clearly it presents the candidate — reported separately from role fit so the two are never confused.
- Full resume analysis
- The role-specific read: job match score, matching and missing skills, experience relevance, relevant and less relevant projects, strengths, gaps, and a hiring recommendation with its explanation.
- Candidate comparison
- Puts a shortlist of two to five candidates side by side, ranks them, and explains the ordering — so the question becomes “why this person over that one?” rather than “who scored highest?”
- AI Copilot
- Ask questions about your pipeline in plain language and get answers drawn from the candidates and roles you already have in Hirevo.
- Semantic search
- Search your talent pool by meaning rather than exact words, so a candidate described differently from the way you searched still surfaces.
- Interview intelligence
- Generated interview packs grounded in the candidate’s own resume, so the questions probe what the person actually claims rather than a generic list.
- Advanced analytics
- Pipeline health, funnel conversion and hiring velocity across your roles, from the same data the screening produced.
- Predictive intelligence
- What-if scenario simulation over your own pipeline data, run on demand from Copilot when you ask a what-if question.
- API access
- Run resume analysis and job matching programmatically with scoped organization keys, drawing on the same credit wallet as the app.
- Audit logs
- A searchable record of the actions taken in your organization, so a screening decision can be accounted for after the fact.
FAQ
AI resume screening, answered plainly.
What is AI resume screening?
AI resume screening is software that reads resumes and evaluates each candidate against a role, instead of filtering them on keywords or leaving the pile to be skimmed by hand. Hirevo reads every resume you upload in full, matches it to the job description, scores and ranks the candidates, and shows the reasoning and resume content behind each result so a recruiter can check it before deciding anything.
How does AI resume screening work in Hirevo?
You create a role with its job description and upload the resumes for it. Hirevo parses each resume, analyses it against the role, and returns a job match score with the matching and missing skills, how relevant the experience and projects are, the candidate’s strengths and gaps, and a hiring recommendation with its explanation. Candidates are ranked from those results, and you can compare a shortlist side by side. A person reviews the recommendation and makes the decision.
Can Hirevo screen resumes against a job description?
Yes. Screening against the job description is the core of the product. Every analysis is run for a specific role, and the output is expressed in the role’s terms: which of its requirements the resume meets, which it does not, and how the candidate’s experience lines up with what the role asks for. A separate ATS score measures the structural quality of the resume itself and does not depend on the role.
Does Hirevo replace an ATS?
No. An applicant tracking system manages applications and workflow; Hirevo is a decision layer that analyses the candidates in a role and supports the choice between them. Today you upload resumes directly. There are no ATS integrations yet — they are on the roadmap and are not something you have today — so Hirevo runs alongside whatever you already use rather than plugging into it.
Does Hirevo automatically reject candidates?
No. Hirevo ranks and recommends; it does not reject anyone on its own. Our terms require a human to review any decision that materially affects a candidate, and the product records who made each call and on what basis. Decisions are logged and reversible for 30 days.
Can recruiters see why a candidate was ranked where they were?
Yes. Every recommendation comes with its explanation, and every analysis lists the strengths, gaps, and matching and missing skills that produced it. From a candidate’s record you can see each strength and risk beside the resume lines related to it — found by matching wording, not cited — and where the analysis is uncertain, that is shown rather than rounded up. The aim is that a ranking you disagree with can be checked and challenged rather than taken on faith.
What does Hirevo analyse in a resume?
For each resume Hirevo produces a job match score from 0 to 100 and a match category, the skills that match the role and the skills it requires that are missing, an assessment of how relevant the candidate’s experience is, the projects that support the requirements and those that do not, recruiter-focused strengths, constructive gaps, and a hiring recommendation with a short explanation. It also gives a structural ATS score for the resume on its own.
How do I get started with AI resume screening?
Create an account, add a role with its job description, and upload the resumes. There is nothing to install and no data to migrate. Every new organization gets 2 full analyses free, without a card, which is enough to see the output on your own resumes before you decide whether it is worth paying for.
Stop screening the pile. Start investigating the decision.
Add a role, upload the resumes, and read what Hirevo makes of them. Every new organization gets 2 full analyses free, without a card.
Not sure it fits how you hire? See what Hirevo does or talk to a person.