Every tool tells you
who’s strongest.Hirevo tells you
who you’d regret.
Hirevo reads every résumé in full and names what a ranking hides. Every claim opens to the line it came from.
Reads every résumé, not the top twentyEvery claim traced to its sourceReversible for 30 days
- Priya Raghunathan68Legible
- A. Okonkwo64Legible
- R. Kaur61Legible
- M. Davis51Soft
2 NEAR THE LINE
Priya Raghunathan
Moderate match · Stage · Screening
THE VERDICT
Recommend interview — probe scope and tenure.
FROM RÉSUMÉMedium confidence
RISK
Tenure averages 2.1 years across senior roles, against a 2.8-year baseline for this role.
EVIDENCE
- Senior Backend Engineer, Razorpay (2021–2025)
- Backend Engineer, Freshworks (2018–2021)
REASONING
Two senior-level tenures of 4.0 and 3.0 years read as stable in isolation, but three of the five roles on this résumé ended inside 24 months. The pattern, not any single move, is what lowers confidence.
Watch a day of hiring resolve to the decisions that matter.
- Intake
- Compression
- Signal
- 0
- Parsed
- 0
- Evidence spans
- 0
- Viable
- 0
- Need a human
Staff Backend Engineer
Platform Engineer
Frontend Engineer
Data Engineer
Engineering Manager
Site Reliability Engineer
Junior Developer
Security Engineer
Machine Learning Engineer
- Skill extraction2,914 skills
- Entity recognition18,402 entities
- Experience parsing1,106 roles
- Evidence generation612 citations
- Shortlist30 viable
S. Rahman
Staff Backend Engineer
Technically sound, but historical team attrition rates are high.
- Evidence found
- 14 evidence
- Risks found
- 2 risks
- 88 Focus
M. Davis
Platform Engineer
Non-traditional background but perfectly matches core skill requirements.
- Evidence found
- 11 evidence
- Risks found
- 0 risks
- 82 Sharp
A. Okonkwo
Data Engineer
Owned the ingestion path at comparable scale for three years.
- Evidence found
- 17 evidence
- Risks found
- 1 risk
- 91 Focus
A. Patel
Frontend Engineer
Evidence is thin on the two requirements that matter most here.
- Evidence found
- 6 evidence
- Risks found
- 1 risk
- 52 Soft
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 résumés, free, without a card.
Four properties of the analysis, not four claims about customers
- Every 01
- Résumé read in full
- Every 02
- Claim linked to its source
- Both 03
- Directions of regret priced
- 30 days 04
- Every decision reversible
No keyword pre-filter decides who gets looked at.
Each statement opens to the passage it came from.
What you lose by choosing either candidate, not just the winner.
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.
- Salary written off
- ~30%
- Ramp lost
- 5–8 mo
- Backfill cycle
- 11 wks
- Team velocity
- −18%
of first-year comp
before the gap is visible
to run the search again
while the seat is open
None of it shows up in the quarter you made the decision.
Recruiting isn’t a volume problem.
It’s a focus problem.
The problem
The modern talent pipeline is choked with noise. Résumés are optimized for parsers, not for truth. Searching for signal in a sea of keywords guarantees you will miss the outliers.
The instrument
We designed Hirevo as an instrument of clarity, not a warehouse for data. It does not measure how many candidates you have. It measures how closely they align with the actual work.
The result
By applying deep semantic understanding to unstructured career trajectories, we elevate the few who matter. The result is a calmer, more decisive hiring process.
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
One cohort of 250 · the dashed return is what the next role learns from
One instrument, from the whole pile to the right decision — and back, learning each time.
Clear hundreds.
Miss no one.
AI-driven compression surfaces signal from noise instantly. Calibrated to your baseline, it identifies the viable subset without subjective bias.
- 0.0 min
- Full pass
- 0%
- Pile read
- 0
- Unseen
- Missing a core requirement96
- Insufficient depth at level74
- Outside the comp band32
- Duplicate application18
- 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
- System architecture6 spans88 Validated
- Distributed systems5 spans91 Validated
- Team leadership3 spans74 Partial
- Incident response2 spans63 Partial
- Hiring & mentoring1 span41 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.”
Confidence you
can defend.
Every assertion backed by extracted evidence. The system maps raw unstructured data against your specific requirements, quantifying fit objectively.
Every number traces back
- Claimthe sentence on the résumé
“Led the re-platforming… 40k req/s”
- Source spanwhere it was said
Résumé · page 2 · role 2 of 5
- Competencywhat it supports
System architecture · Validated
- Confidencehow much weight it holds
88 · shown, never rounded up
Choose, and
know why.
Synthesized, defensible recommendations delivered in a high-fidelity memo. It highlights strengths, isolates risks, and tells you what you’d regret.
- Evidence17 spans · 5 competencies
- WeightingRole calibration v4
- Comparison4 shortlisted
- Recommendation1 primary · 1 alternate
Recommendation memo
Generated for Role ID: 884-A · 4 candidates compared
A. Okonkwo
91 Focus · 17 evidence
M. Davis
82 Sharp · 11 evidence
Candidate demonstrates lower tenure averages in senior roles compared to baseline, presenting a potential retention risk post-18 months.
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
Strengths Alignment
Sarah 82 Sharp · Marcus 88 Focus- Domain depthSarah +27Sarah91Marcus64
- Systems scaleMarcus +25Sarah68Marcus93
- Team leadershipMarcus +12Sarah74Marcus86
- GTM motionSarah +47Sarah88Marcus41
Opportunity Cost
Selecting Marcus sacrifices Sarah’s deep domain expertise in early-stage GTM motion. The cost is slower time-to-market in Q3.
- If you pick Marcus
Slower time-to-market in Q3 — nobody left who has run early-stage GTM.
- If you pick Sarah
Re-architecture slips a quarter — the scale experience is not in the room.
Not a chatbot bolted onto an ATS.
Intelligence built into the decision.
Evidence, not opinions
Every claim opens to its source. No hallucinated summaries.
It admits doubt
Low confidence is shown, calmly, never hidden behind false certainty.
You decide, always
Hirevo recommends; you approve; everything’s reversible and logged.
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
Change which hires you’re proud of, not just how fast you make them.
Most engineering recruitment is a volume game: speed over alignment, and the outliers lost somewhere in the middle of the stack. Hirevo does not just filter résumés — it surfaces the nuance you would have missed, attaches the evidence for every claim it makes, and prices what each choice costs you. The shift is from reacting to applications to designing a team.
Two résumés, free, no card. That is enough to see whether any of this is true.
- 14:02Approved A. Okonkwo · Role 884-A
- 14:02Memo, evidence and alternates sealed
- Day 12Decision reopened — new reference signal
- Day 12Evidence re-run · alternate re-compared
- Day 13Re-decided: A. Okonkwo confirmed
Transparent access.
Designed for teams that value precision over noise.
Free
Try the full analysis on a couple of résumés before you commit anything.
10 Hirevo Credits to try · ≈2 résumé analyses · 1 seat
- Resume Parser
- ATS Score
- Basic AI Summary
Plus
For the recruiter running their own roles end to end.
1,000 Hirevo Credits / month · ≈200 résumé analyses · 3 seats
- Everything in Free, plus:
- Full Resume Analysis
- Candidate Comparison
- PDF Export
Pro
Most teamsFor a hiring team that needs the intelligence layer and shared memory.
5,000 Hirevo Credits / month · ≈1,000 résumé analyses · 25 seats
- Everything in Plus, plus:
- AI Copilot
- Semantic Search
- Interview Intelligence
- Advanced Analytics
Custom
For organizations with their own AI, their own identity, and their own rules.
25,000 Hirevo Credits / month · ≈5,000 résumé analyses · Unlimited seats
- Everything in Pro, plus:
- Autonomous Agent
- Webhooks
- Single Sign-On
- Audit Logs
Common inquiries
Bring every hire into focus.
- 14:02K. OseiApproved A. Okonkwo · Role 884-A
- 14:02HirevoMemo, evidence, and alternates sealed
- 14:03LedgerEntry written · reversible 30 days