A parser identifies document information such as candidate name, contact details, employers, dates, education and named skills.
A screening tool uses the vacancy criteria to review how the candidate document relates to one job.
Unsupported, corrupted or unreadable files should be identified before candidate relevance is assessed.
Finding a qualification or employer name in a CV does not prove the statement. Formal checks remain separate.
A role-specific score is an interpretation of extracted content and criteria, not a field originally contained in the CV.
Recruiters need access to the original CV so they can inspect context and resolve extraction or screening errors.
Confirm that the format is supported, the file is within limits and readable content can be extracted.
Extract text and structured fields while retaining the original document for human review.
Compare the readable CV context with the job description and recruiter-supplied requirements.
Inspect the score, strengths, gaps and source CV before deciding whether the candidate should progress.
Separating extraction problems from candidate relevance prevents a technical failure from becoming a hiring judgement.
A document that cannot be extracted should be labelled Invalid, not given a low candidate score. Request or inspect a readable version before making a decision.
Columns, text boxes, images and unusual reading order can affect extraction. A well-rendered page is not always a reliably parsed document.
A parser may correctly find a skill name while providing no evidence of how it was used. Screening should consider nearby roles, projects, dates and outcomes.
Not finding a requirement in the submitted CV means the document did not provide it clearly. It does not prove the candidate lacks the skill or experience.
Parsed fields and screening outputs may move to an ATS or CRM. Confirm field mappings, duplicate handling, retention and whether the original CV remains accessible.
CVSense validates supported files, extracts readable content and then performs role-specific screening. The result includes a canonical score band and preserves original-CV access for recruiter review.
A resume parser extracts fields such as name, contact details, employers, dates, qualifications and skills from a document so the information can be stored and searched.
Screening software compares the readable candidate document with the requirements of a specific vacancy and returns information that helps a recruiter review relevance.
No. Parsing structures document data; it does not establish candidate suitability or verify that a claim is true. Even a screening score remains a decision-support signal for human review.
Complex columns, images and text boxes can change extraction order or hide information. A recruiter should retain the original CV and handle unreadable documents separately rather than treating an extraction failure as a poor match.
CVSense validates and extracts readable content from supported documents before comparing it with the vacancy. Invalid documents are labelled separately, and recruiters can inspect the original CV alongside the result.
See how CVSense turns up to 500 CVs into a ranked, reviewable candidate list.
Read the EBSV methodology, score bands, limitations and human-review principles.
Compare screening approaches, buying criteria and the questions UK recruiters should ask.
Understand where document screening ends and applicant tracking begins.
Submit evidence-backed shortlists to clients faster. Zoho Recruit integration.
Replace agency spend on volume roles — screen, score and shortlist in-house.
See how CVSense connects document validation, role-specific screening and recruiter-controlled decisions.
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