AI resume screening for technical hiring teams

See who fits the role,and why.

Add a job description and your resumes. Hirevo ranks each candidate against the role and shows the strengths, gaps, and risks behind each match.

Start free — 2 analyses, no cardSee how it ranks

Works alongside your ATSAI assists, you decide

The shortlist

Every resume, ranked against the same requirements.

The best fits rise to the top. Everyone else keeps the reason they didn’t.

What every run guarantees

We would rather show you the instrument than tell you about it.

Hirevo is early, and we are not going to dress that up with logos we have not earned. What follows is what the analysis does on every run — check it yourself on two resumes, free, without a card.

Four properties of the analysis, not four claims about customers

Every
01
Resume read in full

No keyword pre-filter decides who gets looked at.

Every
02
Claim checkable against the resume

Strengths and risks sit beside the resume lines they relate to.

Both
03
Directions of regret priced

What you lose by choosing either candidate, not just the winner.

30 days
04
Every decision reversible

Logged, attributable, and reopenable.

The Stakes

The cost of a wrong hire isn’t a bad quarter.
It’s a lost year.

A mis-hire costs ~30% of first-year salary — and the momentum you can’t get back.

One senior mis-hireIndustry benchmark
Salary written off

of first-year comp

~30%
Ramp lost

before the gap is visible

5–8 mo
Backfill cycle

to run the search again

11 wks
Team velocity

while the seat is open

−18%

None of it shows up in the quarter you made the decision.

Technical screening isn’t a volume problem.
It’s an evidence problem.

The problem

Engineering resumes are written for parsers. A keyword match rewards whoever used the posting’s vocabulary, not whoever built the system — and the strongest person in the pile can be the one who never used the magic word.

What Hirevo does

Hirevo reads each resume against the role’s actual requirements — the stack, the scale, the level — and shows the resume lines related to each claim it makes.

What you get

Strengths, gaps and risks you can point at, and a ranking you can explain to the hiring manager. The decision is still yours; the evidence for it is already on the table.

The category difference

An ATS remembers candidates. Hirevo helps you choose one.

Five questions, asked of both. An ATS answers them as a system of record. Hirevo answers them as an instrument you decide with.

Read each row left to right

The Old WayHirevo
What it holdsStores every candidateSurfaces the few who matter
What it isA searchable databaseA decision instrument
Who does the workYou go diggingIt brings them to you
What you get backA keyword match scoreStrengths, gaps and risks you can check against the resume
What it leaves behindA status changeA logged, reversible decision with its reasoning
Same five questions · two kinds of toolThe last two rows are the product
250
Arrive
30
Triage
12
Deep Review
4
Decide
2
Approve
2
Ledger
2
Outcome

One cohort of 250 · the dashed return is a decision reopened within 30 days

From the whole pile to a decision you can defend.

30 carried forward
Stage 01 — Triage

Clear hundreds.
Miss no one.

Every resume is read in full against the role’s core requirements. The ones that meet the bar move forward, and the ones that don’t come with the reason why.

0.0 min
Full pass
0%
Pile read
0
Unseen
Hirevo Triage · Senior Backend Engineer
250 inbound
Calibrated onGoDistributed systemsOwned prod at scaleIC5+
Applicants read0 · 100%
Met the bar0 · 35%
Viable for this role0 · 12%
Need a human decision0 · 3%
Why 220 did not advanceevery exclusion carries a reason
  • Missing a core requirement96
  • Insufficient depth at level74
  • Outside the comp band32
  • Duplicate application18
RKHNAOPVMDSLJTCBEWNVLMGKDSFA+236 · each with a reason
Verdicts landing
  • 0:04R. KaurAdvancedGo · distributed systems
  • 0:11H. NakamuraFilteredBelow level for scope
  • 0:19P. VargaHeldStrong, adjacent domain
  • 0:26A. OkonkwoAdvancedOwned ingestion at scale
  • 0:31M. DavisAdvancedEvent-driven re-platform
  • 0:38S. LindqvistFilteredDuplicate application
12 to deep review
Competency verification
R. Kaur · resolved 4 of 6
Evidence coverage0% · 17 related lines
  • System architecture88 Validated
  • Distributed systems91 Validated
  • Team leadership74 Partial
  • Incident response63 Partial
  • Hiring & mentoring41 Thin evidence
“Led the re-platforming of the order pipeline to an event-driven architecture serving 40k req/s, cutting p99 latency from 900ms to 120ms.”
Related resume lineExperience · role 2 of 5Relates to: system architecture, distributed systems
Stage 02 — Deep Review

Confidence you
can defend.

Every strength and risk sits beside the resume lines that relate to it, so you can check it against what the candidate wrote. Confidence is shown as it is, never rounded up.

How a claim is checked

  1. Claimwhat the analysis says

    System architecture at scale

  2. Related linematched by wording in the resume

    “Led the re-platforming… 40k req/s”

  3. Competencywhat it supports

    System architecture · Validated

  4. Confidencehow much weight it holds

    88 · shown, never rounded up

4 to decide
Stage 03 — Decide

Choose, and
know why.

A side-by-side comparison of the shortlist: who leads, why, what the risks are, and what you would give up by choosing someone else.

  1. Evidence17 spans · 5 competencies
  2. WeightingRole calibration v4
  3. Comparison4 shortlisted
  4. Recommendation1 primary · 1 alternate
250 read30 triaged12 reviewed4 compared1 decision

Recommendation memo

Generated for Role ID: 884-A · 4 candidates compared

Hirevo
AO91PrimaryMD82AlternateRK77PV64
Primary

A. Okonkwo

91 Focus · 17 evidence

Alternate

M. Davis

82 Sharp · 11 evidence

Primary risk factor

Candidate demonstrates lower tenure averages in senior roles compared to baseline, presenting a potential retention risk post-18 months.

Tenure by rolebaseline 2.8 yrs
3.4
2.9
1.6
1.2
yrs
Awaiting your approval · reversible · logged to the ledgerConfidence 74 · Sharp

The short version

Hirevo, in plain terms.

  • What is Hirevo?

    Hirevo is an AI recruiting decision layer for technical hiring. Give it a role’s job description and the resumes for it, and it reads every resume in full, ranks the candidates by fit to that role, and shows the evidence behind each recommendation. It is not an ATS and does not replace one: it runs alongside whatever you already use, so a recruiter can investigate fit and make a decision they can explain.

  • How does Hirevo work?

    It starts from the job description, not the resumes. Each uploaded resume is parsed and read in full, then matched against the role’s requirements: which skills match, which are missing, how relevant the experience and projects are. Every candidate gets a job match score and category, the pipeline is ranked from those results, and each strength and risk is shown beside the resume lines related to it. A recruiter reviews the analysis and makes the final call.

  • How does Hirevo compare candidates?

    Every candidate in a role is measured against the same requirements, so the ranking reflects fit to the job rather than to each other’s resumes. From that ranked view a recruiter can put a shortlist of two to five side by side, read each one’s strengths, gaps and risks with the supporting evidence, and see why one ranks above another — and what you would give up by choosing someone else.

The full walkthrough — screen, match, rank, explain, decide — is on the AI resume screening software page. How a pile of applicants becomes a shortlist you can explain is the subject of candidate screening.

Every tool tells you who’s strongest.
Only Hirevo tells you what you’d regret.

The question no other tool asks.

Regret Analysis: Sarah vs Marcus

Role 884-A · 28 evidence spans

Strengths Alignment

Sarah 82 Sharp · Marcus 88 Focus
  • Go and observability depthSarah +27
    Sarah91
    Marcus64
  • Systems at scaleMarcus +25
    Sarah68
    Marcus93
  • Production ownershipMarcus +12
    Sarah74
    Marcus86
  • Incident responseSarah +47
    Sarah88
    Marcus41

Opportunity Cost

Selecting Marcus gives up Sarah’s depth in Go and observability, and the only incident-response record on the shortlist. The cost is a slower, riskier on-call rotation.

AI Confidence Line:52 Soft
  • If you pick Marcus

    The Go migration loses its most experienced hand — and nobody left has run an on-call rotation at this level.

  • If you pick Sarah

    The re-platform slips a quarter — nobody in the room has owned a system at 40k req/s.

Comparison written to the ledger · 14:02 · K. OseiReversible for 30 days · exportable · attributable

Not a chatbot bolted onto an ATS.
Intelligence built into the decision.

Evidence, not opinions

Strengths and risks sit beside the resume lines they relate to, so you can check them.

17 related resume lines on this candidate
Low confidence

It admits doubt

Low confidence is shown, calmly, never hidden behind false certainty.

52 Soft — shown, not rounded up

You decide, always

Hirevo recommends; you approve; everything’s reversible and logged.

Reversible · logged · attributable

Built for teams that can’t afford to be wrong — or to leak.

Row-level isolation
Enforced in the database, not the application layer
Encrypted in transit and at rest
Across storage, database and backups
Data stored in Singapore
One region today — no residency choice yet
Your data trains nothing
Never used to serve another organization
No security certification yet — the full picture is in our Privacy Policy.

Change which hires you’re proud of, not just how fast you make them.

Most engineering hiring is a volume game, and the outliers get lost in the middle of the stack. Hirevo reads every resume against the role, attaches the evidence for every claim it makes, names the risks, and prices what each choice costs you. The shift is from reacting to applications to designing a team.

Two resumes, free, no card. That is enough to see whether any of this is true.

See what each plan includes

Same analysis on every plan.

What changes is how many resumes you read, how many of you there are, and how much of the intelligence layer you want.

Free

Try the full analysis on a couple of resumes before you commit anything.

Free

10 Hirevo Credits to try · ≈2 resume analyses · 1 seat

  • Resume Parser
  • ATS Score
  • Resume Analysis
See Free

Plus

For the recruiter running their own roles end to end.

₹999/month

1,000 Hirevo Credits / month · ≈200 resume analyses · 3 seats

  • Everything in Free, plus:
  • Larger Analysis Allowance
  • Candidate Comparison
  • PDF Export
See Plus

Pro

Most teams

For a hiring team that needs the intelligence layer and shared memory.

₹2,499/month

5,000 Hirevo Credits / month · ≈1,000 resume analyses · 25 seats

  • Everything in Plus, plus:
  • AI Copilot
  • Semantic Search
  • Interview Intelligence
  • Advanced Analytics
See Pro

Custom

For organizations with their own AI, their own identity, and their own rules.

Custom

25,000 Hirevo Credits / month · ≈5,000 resume analyses · Unlimited seats

  • Everything in Pro, plus:
  • Autonomous Agent
  • Webhooks
  • Single Sign-On
  • Audit Logs
Talk to sales
Compare every plan

Questions hiring teams ask.

Is Hirevo an ATS?
No, and it does not replace one. Hirevo is a decision layer: you bring resumes for a role, it reads all of them, and it gives you evidence, risk and what each choice would cost you. Today you upload resumes directly — there are no ATS integrations yet, so it runs alongside whatever you already use rather than plugging into it. Integrations are on the roadmap and are not something you have today.
What is AI resume screening, and is that what Hirevo does?
AI resume screening is software that reads and evaluates resumes against a role, rather than leaving the pile to be skimmed by hand or filtered on keywords. Yes, that is what Hirevo does: it reads every uploaded resume in full, matches it to the job description, scores and ranks the candidates, and shows the reasoning and the resume evidence behind each result. The recruiter makes the decision.
Does it replace my recruiters?
No. It reads the pile so a recruiter does not have to, and it explains every recommendation it makes — but it recommends and a person decides. 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.
How does Hirevo rank candidates?
Every candidate in a role is analysed against the same job description, and each analysis produces a job match score from 0 to 100 and a match category. The role’s pipeline is ranked from those results. The order is not a verdict: you can open any candidate to see the matched and missing skills, the strengths and gaps, and the resume lines related to them, so you can check why one person sits above another and disagree with it.
Does Hirevo reject candidates automatically?
No. Hirevo ranks and recommends; it does not reject anyone on its own. A person makes every decision — our terms require human review of any decision that materially affects a candidate — and the product records who made each call and on what basis. Decisions are logged and stay reversible for 30 days.
How do you handle 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 is broken down into its parts and every strength and risk sits beside the resume lines related to it, so a judgement you disagree with can be checked rather than taken on faith; low confidence is shown rather than rounded up; and nothing is auto-rejected — the tool ranks, a person decides, and the decision is logged with its reasoning. If you are subject to an audit requirement such as NYC Local Law 144, talk to us before you deploy rather than after.
How is my data used?
To serve your organization and nothing else. Your resumes, decisions and notes are never used to train models that serve anyone but you, we do not sell personal data, and there is no advertising or third-party tracking on any signed-in page. Data is stored in Singapore; resume text is sent to a US inference provider to produce the analysis. The full list of who touches your data is in our Privacy Policy.
What does it take to get started?
An account, a job description and some resumes. There is nothing to install, no data migration and no implementation project, because there is nothing to integrate with yet. Every new organization gets two full analyses free, without a card, which is enough to tell whether the output is worth anything to you.
Which roles is Hirevo built for?
Technical roles first: software, backend, full-stack, data, ML and DevOps engineers. The analysis reads the requirements of whatever job description you give it, so it runs on other roles too, but its skills vocabulary and its calibration were built on engineering job descriptions and engineering resumes, and that is where the free analyses will show it at its best.
Is the scoring consistent?
Partly, and we would rather tell you exactly which part. The requirements a role is scored against come from the job description alone, so every candidate in a role is measured against the same set. The checks against the resume’s own skills, structure, experience and education are rule-based and give the same result every run, and so is the ATS score, which measures the resume’s structure on its own. The parts that come from the model’s reading — which skills it lists as matched or missing, which projects it calls relevant, and the written strengths and gaps — can vary between runs, so the final job match score can move. A match the resume itself supports is always counted, whatever the model says.

Make your next engineering hire one you can defend.

Start free — 2 analyses, no cardTalk to a person
Decision ledgerToday
  1. 14:02K. OseiApproved A. Okonkwo · Role 884-A
  2. 14:02HirevoMemo, evidence, and alternates sealed
  3. 14:03LedgerEntry written · reversible 30 days