Screen CVs Faster with Match Signals

CV fraud, misrepresentation, and template reuse are common enough that a second look can pay off before a call gets booked. The fraud risk score surfaces that check early, with evidence attached, rather than relying on intuition.

Email, phone, and LinkedIn details are usually already on the CV. Copying them into a separate list is repetitive work the extension can handle while it reads the CV anyway.

CrossClassify compares the skills, experience, responsibilities, and keywords in a CV with the recruiter’s job description. It then surfaces three to five positive and negative signals that show what supports or weakens the match, helping the recruiter decide whether the candidate fits the role.

The fraud risk score highlights patterns in a CV that may be worth a closer look. These patterns are called risk signals. They can include things like inconsistent employment dates, conflicting information between sections, unusual formatting, or other signs that the CV may need further review. Each signal shows what was detected, the supporting evidence, and a risk level (low, medium, or high), so recruiters can review the finding themselves rather than rely on the score alone.

Text extraction happens locally in the extension. The extracted text, CV filename, and job description are sent to the CrossClassify analysis endpoint. The original PDF or DOCX file never leaves your browser.

As reliable as what is written in the CV. The extension pulls whatever email, phone number and LinkedIn profile appear in the readable text; it does not guess, autocomplete or source information from anywhere else.