AI CV Screening for Tech Recruiters
— Cut through inflated CVs and buzzword bingo
Go beyond keyword counts. Review evidence in context.
CVSense® Evidence-Based Skill Validation (EBSV) examines the evidence presented in each CV against your job criteria. It distinguishes skills supported by projects, roles, dates or outcomes from claims that need recruiter review and requirements not found in the document.
Evidence-based scoring
Every claimed skill is cross-checked against the candidate’s own experience, projects and outcomes — not just job titles.
Reviewable skill context
Each required skill can be shown as Evidenced, Claimed or Missing, with context from the submitted CV for the recruiter to assess.
Claims that need review
CVSense highlights skills mentioned without supporting context in the submitted CV. Recruiters can then verify those claims through interviews, references or formal checks.
Why tech recruiters choose CVSense
Stack-depth scoring on evidence
EBSV scores each tech skill on real project evidence — not on a skills-tag at the bottom of the CV.
Catches CV padding
Surfaces CVs that name-drop trendy frameworks (Kubernetes, Rust, LLMs) without any project, role or outcome evidence.
Senior vs junior signal
Tri-state classification lets you separate hands-on engineers from CV-keyword tourists.
Bulk PDF & DOCX upload
Process 500+ engineer CVs in a single batch — PDFs, DOCX, scanned-text PDFs all supported.
Defensible scoring rationale
Every score comes with the supporting CV evidence quoted back — show your hiring manager exactly why a candidate ranks.
UK-hosted, GDPR-compliant
Candidate data stays in the UK. No training models on candidate CVs. Full DSAR support.
How tech recruiters use CVSense
- 1
Add the role
Paste the JD plus essential and desirable criteria.
- 2
Upload the CV batch
Drag and drop PDFs / DOCX from your inbox, job board, ATS or CRM.
- 3
AI scores every CV on evidence
CVSense® EBSV ranks every candidate with a written rationale per score.
- 4
Review and export
Open the ranked shortlist, read the rationale, export as CSV.
Tech Recruiters — FAQs
Does CVSense distinguish hands-on engineers from skills-tag candidates?+
Yes. EBSV's tri-state classification (Evidenced / Claimed / Missing) is purpose-built for this. A candidate who lists 'Kubernetes' in skills but never references it in a project, role or outcome will be classified as Claimed — and flagged for the recruiter.
Can CVSense screen for specific tech stacks?+
Yes — paste the JD with your required stack into CVSense and EBSV will score each required technology on the evidence in every CV.
What about polyglot engineers with broad CVs?+
Strong polyglot CVs typically have project-level evidence for each major technology — EBSV will surface that. Weak generalist CVs that name-drop everything without project evidence are flagged.
Does CVSense work for engineering manager / CTO CVs?+
Yes. EBSV scores leadership, scaling and ownership evidence the same way it scores technical skills — on the basis of evidence in the CV (team sizes, outcomes, project scope).
Related solutions
AI CV and Resume Screening
See how CVSense turns up to 500 CVs into a ranked, reviewable candidate list.
How CVSense Reviews CV Evidence
Read the EBSV methodology, score bands, limitations and human-review principles.
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For Recruitment Agencies
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For In-house Talent Teams
Replace agency spend on volume roles — screen, score and shortlist in-house.
Hire engineers on evidence, not buzzwords.
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