CVVIZ AI RESUME PARSER
Parse resumes at scale, standardize candidate profiles and return usable data through the CVViZ resume parsing API or export workflow. Build faster application, search and recruitment experiences while keeping people in control of decisions.


























FROM DOCUMENT TO WORKFLOW
Resume parsing converts unstructured CV content into consistent fields that your ATS, job board, HRMS or internal recruitment application can use.
EXTRACT
Convert resume content into structured fields that are easier to search, display and move through downstream workflows.
STANDARDIZE
Present candidate information in a common format instead of asking teams to interpret a different resume layout every time.
AUTOFILL
Use parsed information to prefill candidate profiles and applications, then let the candidate or recruiter review what was captured.
INTEGRATE
Use the parser API or supported exports to connect structured resume data with the systems and processes your team already operates.
RESUME PARSING API
Send a resume to CVViZ, receive structured candidate information and map the returned fields into your product experience. Use it to accelerate profile creation, candidate search, matching inputs and data migration workflows.
BUILT FOR PRODUCT AND OPERATIONS TEAMS
CVViZ supports standalone parsing needs as well as parsing inside recruitment workflows.
RECRUITING PLATFORMS
Use parsed data to create searchable profiles, improve imports and reduce the manual work required to normalize candidate information.
JOB BOARDS
Prefill profile fields from an uploaded resume and let candidates verify the information before submitting their application.
HIRING TEAMS
Parse multiple resumes, export structured information and give recruiters a consistent dataset for review and reporting.
PRIVACY AND HUMAN CONTROL
Resume parsing organizes candidate-provided information. Your team remains responsible for validating extracted fields, choosing what data to use, managing consent and retention, and making every employment decision.
ValidateReview important extracted fields
MinimizeUse only relevant candidate data
ControlManage access and retention
DecideKeep people accountable for outcomes
RESUME PARSER PRICING
These standalone Resume Parser prices are copied from the current CVViZ production pricing page.
If you hire for more than 50 positions or need to parse more than 100,000 resumes in a month then contact us at he***@***iz.com
Standalone Resume Parser pricing starts at $625 USD for 10,000 Credits/Year.
FREQUENTLY ASKED QUESTIONS
Understand what parsing does, how it connects to other systems and where human review still matters.
A resume parser converts information in a resume into structured fields that can be stored, searched, displayed or passed into another recruitment workflow.
Resume parsing extracts and structures information from a resume. Resume screening compares candidate information with a particular job and helps recruiters organize candidates for review. Parsing does not decide who should be hired.
Yes. The CVViZ resume parsing API is designed for integration with applicant tracking systems, job boards and other recruiting applications. Confirm the required data mapping, volume and implementation details with the CVViZ team.
The current CVViZ offering supports resume parsing API output and exports to JSON, XML, Excel and CSV. Confirm the best format and integration method for your use case during evaluation.
Yes. CVViZ supports bulk resume parsing for teams that need to structure or export candidate information at scale.
No technology can guarantee the removal of hiring bias. Parsed data can help teams standardize profiles or choose to hide selected fields, but people must define responsible processes, review outputs and make every hiring decision.
The production plans shown here are $625 for 10,000 credits per year, $2500 for 50,000 credits per year and $4500 for 100,000 credits per year. Contact CVViZ for the customized-volume condition shown on this page.
START WITH REAL RESUMES
Try the parser with your use case or discuss API mapping, volume and integration requirements with the CVViZ team.