Screen every CV consistently
Apply the same confirmed criteria across the whole batch, without prompt drift or spreadsheet work.
Criteria
Evidence
Buckets
AI CV screening for high-volume roles
Turn 500 CVs into a reasoned shortlist in minutes.
Screen against approved criteria, then keep evidence, notes, bias checks, and team decisions in one AI workspace.
Try Marxel free. 200 CVs/month, no credit card required.
500
CVs in one screening run
200
free screens each month
4
decision buckets for review
Screening run
Senior Product Designer
147
processed
3m 42s
runtime
18
aligned
Aligned18
Potential34
Hold41
Unclear54
Why Sarah is aligned
Matches the senior design scope, shows portfolio-led process, and has stakeholder experience for a cross-functional product team.
One workspace for screening decisions
Screening is only the start.
Once Marxel reviews the batch, your team can inspect evidence, ask questions across the candidate pool, check criteria risk, and keep the decision record attached to the role.
Ask the candidate pool
Compare applicants, surface past candidates, and query CV evidence, scores, notes, and recommendations.
Keep decisions reviewable
Preserve reasoning, bias-aware checks, notes, and shortlist context for hiring managers and compliance review.
Candidate-pool question
“Who has B2B SaaS experience but needs domain ramp-up?”
Ask across CV evidence, notes, scores, and prior evaluations without rebuilding the role context.
Maya Patel
B2B SaaS onboarding, 6 years, strong stakeholder notes
Oliver Grant
Marketplace product work, clear discovery examples
Nadia Brooks
Previous Hold candidate with updated fintech project
Four steps from brief to shortlist.
Review the criteria before screening starts, then hand the hiring team a shortlist they can understand and act on.
View full walkthroughBrief the role
Upload the job description and briefing notes.
Confirm criteria
Review and adjust the suggested screening criteria.
Screen the batch
Upload CVs and let Marxel process the batch.
Review evidence
Review bucketed candidates with explainable notes.
See the reasoning, not just a score
Every candidate comes with the evidence behind the bucket.
Marxel shows which criteria a candidate matched, the concerns worth a closer look, and how confident it is, so your hiring team can act, or follow up, without re-reading the CV.
See a full example assessmentSarah Jones
Senior Product Designer
Why this bucket
- 7 years product design across B2B SaaS
- Portfolio demonstrates end-to-end process
- Led stakeholder management on cross-functional teams
Potential concerns
- No fintech experience. Confirm domain ramp-up in interview.
High confidence. Illustrative example.
Why Marxel, not a ChatGPT workflow
You could paste CVs into ChatGPT. Here's what breaks at scale.
A blank chat box can summarise a single CV. Screening a real pipeline needs governance, auditability, regulatory-ready records, and a clear trail for every decision.
Governance and auditability
Every role keeps approved criteria, reviewer notes, bucket changes, and decision reasoning in one auditable record.
Regulatory-ready review
Human approval, bias-aware checks, and explainable outputs support compliance review instead of leaving decisions in a loose chat thread.
Consistent scoring across every CV
The same confirmed criteria are applied across the whole batch, with no drift as a chat thread gets longer.
Criteria locked in before screening
Review and approve a structured rubric up front instead of re-pasting instructions into every prompt.
Bias-aware review built in
Risky language and vague criteria are flagged automatically, not only when someone remembers to ask.
Bulk throughput, not copy-paste
Upload up to 500 CVs and let Marxel parse, evaluate, and bucket the batch in parallel.
Exportable shortlists
Hand the hiring team bucketed candidates and reasoning they can act on, not a chat transcript.
| Screening workflow | Marxel | ChatGPT |
|---|---|---|
| Governance and audit trail | Included | Not included |
| Regulatory-ready review records | Included | Not included |
| Saved, reusable scoring rubric | Included | Not included |
| Bulk screening up to 500 CVs | Included | Not included |
| Consistent scoring across the batch | Included | Not included |
| Bias-aware criteria checks | Included | Not included |
| Candidate buckets and shortlists | Included | Not included |
| Shared team workflow and records | Included | Not included |
FAQs
Common questions about Marxel.
What does Marxel do?
Marxel is an AI screening workspace for hiring teams that need to review large batches of CVs against consistent, role-specific criteria before making a shortlist.
Does Marxel replace an ATS?
No. Marxel is built for first-pass CV screening and shortlist evidence. It can sit alongside an ATS when the ATS manages applicants but does not give recruiters enough screening depth or consistency.
Can Marxel help with GDPR-conscious screening?
Marxel keeps humans in control of criteria and hiring decisions, provides explainable screening notes, and does not use uploaded CVs to train Marxel-owned AI models.
What does bias-aware review check?
Marxel flags vague, risky, or potentially discriminatory criteria before they shape candidate scoring. It supports human review; it does not guarantee unbiased hiring decisions.
What can I ask the candidate pool?
You can compare candidates across CV evidence, scores, notes, recommendations, and prior evaluations so recruiters do not have to rebuild context from spreadsheets or chat transcripts.
Start with one role.
Test Marxel on a real hiring workflow, then decide whether it belongs in your wider screening process.
GDPR-conscious. CVs are not used to train Marxel-owned AI models.