Resume Parser

Accurate, Multilingual, GDPR-compliant Resume Parsing Software

Resume Parser

Highly accurate, multilingual resume parser. Available in 25 languages

Textkernel’s multilingual resume parser offers applicant data capture that is fast, reliable, and compliant to the latest data protection regulations.

Our highly accurate resume parser supports recruiting organizations around the world to effectively and efficiently process large volumes of candidate documents. 

Transform the millions of candidate applications into structured data that can be used to filter, search and rank candidates.

Click to see the supported languages.

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Resume parser features


    Textkernel takes our customers' data security very seriously. Textkernel adheres to strict standards through international certification and data processing agreements.

    We are ISO27001 and GDPR compliant and process your data in local data centers.


    Textkernel is the only parsing provider worldwide that guarantees consistent quality across all languages that we offer parsing coverage for.

    We offer parsing in 24 languages and our team is always busy adding more! For a full list of our language coverage, please see below.


    The Textkernel parser can process documents in any format, such as pdf, docx, doc, html, odt, txt, etc. It can also process scanned documents by applying OCR (Optical Character Recognition).


    Textkernel offers the most accurate parsing across all languages that we cover. If you are a global organization that is looking for consistent accuracy, you are at the right place. 
      Texternel uses state-of-the-art AI to extract information regardless of the document structure, language or writing style. The AI is built using documents and speakers in the native language, without using quality-degrading machine translations.

      Scroll down for a granular comparison of test results based on a variety of parsing providers. This overview comes courtesy of a Textkernel customer, which is a global staffing organization. 

    See the results

    The following resume data enrichments are available so that you can gain a deeper understanding of the candidate:
    -Skills and skill categories
    -Professions and job categories (also for ISCO and O*NET standards).
    Experience levels.
    -Geocoding, with ISO codes and lat/long (worldwide).
    -Summary information such as total years of experience and highest education level.





“Jacobson has half a million candidates we’ve built relationships with, and having better access to our database has been pivotal. We now have fewer recruiters going to outside sources first, because of the improved accessibility of our own talent.” 

Jennifer Shorr, Assistant Vice President of Operations, The Jacobson Group

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“Our relationship with Textkernel helps put us in a better place in the market. The functionality that they offer is table stakes for what we do. We wouldn’t be able to grow if we couldn’t get this one thing done really well. And they do it really well.”

Joe Miliziano, Chief Operating Officer, Harri

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“We offer candidates searching on our career portal a fast and easy path to relevant job vacancies.  Our recruiting team benefits from more, higher quality candidates and less time spent qualifying [the candidate pipeline]. We are also more confident that website visitors don’t overlook any potential vacancy matches.”

Marie Rosenberg, Team Lead Talent Acquisition, Rheinmetall AG

Read our customer case

Tested by prospects and clients against top competition with class-leading results

Thanks to the latest Natural Language Processing (NLP) technology, time-consuming and potentially error-prone manual data entry is a thing of the past.

Additional testing reviews

How resume/ CV parsing work for you

Find out how Resume Parser can work for you?

What is Resume Parser?

The resume or CV is imported into parsing software and the information contained within the document file is extracted and distilled into its elements so that the resume data can be categorized according to predefined fields. 

The extracted data is then automatically normalized. This means it is categorised according to a standard or customer specific format. Normalization ensures better searchability and analysis of the resume data processed.  

Textkernel also offers her customers the ability to enhance their parsing offering with normalisation to a specific or even custom standard.

The O*NET Profession Classification– The O*Net professional code contains hundreds of standardized and occupation-specific descriptors of approximately 1,000 occupations covering the entire U.S. economy.

ISCO profession Classification – The International Standard Classification of Occupations (ISCO) is one of the main international classifications for which the International Labor Organization is responsible.

Textkernel Profession Classification – A classification including over 4,200 professions curated by Textkernel over the past 10 years thanks to access to over one billion job vacancies.

Textkernel Skills Classification – A classification carefully built and curated by Textkernel R&D, based on the analysis of millions of candidate documents and job vacancies processed.  The Textkernel Skills Normalization Taxonomy currently contains about 135,000 terms that describe just over 11,000 skills, which are divided over four categories: 

  1. Professional skills
  2. IT skills
  3. Soft skills
  4. Languages

Learn more about how Textkernel’s Skills Classification can benefit your organization.

Machine learning is the technology that enables resume parsing.  Thanks to hundreds of hours spent by human annotators across all our languages, large volumes of cvs are broken down into their component parts:  personal and/or contact information, education, work experience, languages, etc.  Then Textketnel’s algorithms are fed millions of cvs to ‘train’ and reinforce the patterns already deciphered by the human annotators.

Once the resume has been parsed, a recruiter can easily search their database for search terms required to generate a shortlist of relevant candidates. The Textkernel resume parsing software is essential for powering semantic search.  Semantic search is a powerful search technology that adds context to the search terms and tries to understand intent in order to make the results more reliable and comprehensive. Now you can ensure that your recruiters don’t overlook potentially relevant candidates that might have otherwise been overlooked.  Learn more about Textkernel’s Search! offering.


Key benefits of the Textkernel CV/Resume Parsing solution:

Dramatically less time required to process and shortlist candidates without compromising on result accuracy.

Textkernel AI technology allows your recruiting team to focus on building human connections. The one thing that AI can never replace.

Our customers demand the highest quality results, otherwise the time savings gained through automation would be of little value. Textkernel continuously explores new techniques to optimise its extraction models.

Since 2017, Extract! has been powered by deep learning which has increased the parsing accuracy of even the most challenging cv formats. Learn more about how Textkernel was the first to launch Deep Learning to improve Textkernel resume parsing software quality.

Register to get updates on Textkernel cv/resume parsing improvements.

Increase candidate conversion by incorporating Textkernel parsing at the very beginning of the candidate journey.

Textkernel’s Extract! technology is not just a backend process. We have developed the ability to embed Textkernel resume parsing software into career portals and job sites. The benefits? Dramatically quicker and easier candidate application process that provides an improved candidate experience.

This improves your candidate experience while also giving your recruitment teams the ability to tailor the candidate journey based on their skills.
Learn more.

The Magic Behind Extract 4.0

How does Machine Learning and Natural Language Processing power Textkernel’s Resume Parsing Software?

Sequence labelling in deep learning

What about the data security of parsed information?

Textkernel takes the security and privacy of our customers’ resume data very seriously. Our stringent data security procedures ensure our customers can be confident that we are handling their data assets with utmost care and consideration.

Learn more from our Information Security Officer

Supported languages for resume data extraction

We are continually working on expanding this supported and developing language list, so if you are interested in parsing CVs in a language that is not listed above, please contact and let us know.

Textkernel's Integrations

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