Textkernel & Documill: the perfect pair for staffing productivity

Textkernel & Documill: the perfect pair for staffing productivity

How to ensure that your ATS data is good and right for automated documents like resumes and CVs.

For staffing and recruitment agencies, one key benefit of document automation is that it makes it obligatory to have the data tidy and right in an Applicant Tracking System (ATS). When staffing and recruitment documents like CVs and contracts are automatically generated and populated with candidate data from the ATS, the data needs to be correct and in the right fields, so it finds its way to exactly the right fields in the document. 

But how to ensure that the data in the ATS gets correctly inserted – without it taking ages? 

Enter resume parsing. It enables automated extraction of applicant data from a resume to the ATS. This saves time and ensures high data quality. Adding data manually from resumes to the ATS is time-consuming and error-prone routine work, so why not simplify and accelerate it?  

These days, recruiting agents need to engage more and better with the applicants and candidates. In the face of the stiff competition for talent in many jobs, it is important to ensure a good candidate experience. With automated data input to the ATS, the staffing agents can spare more time for the applicants, candidates and customer organizations searching for new talent. 

In this article, I explain:

  • What a resume parser is 
  • Why a resume parser and document automation solution work so well together 
  • Document types we have helped to automate.
Scanning resumes or CVs manually can be hard work, but luckily no longer necessary.

Scanning resumes or CVs manually can be hard work, but luckily no longer necessary.

What is a resume parser?

But what exactly is this piece of software, a resume parser? Let’s look at one of the leading solutions, Textkernel. By the way, Textkernel is also a direct customer of ours, making good use of our document automation solution, Documill Dynamo. We work well together. 

Using advanced algorithms and machine learning techniques, Textkernel analyzes the content of a resume. Then it extracts specific data points such as contact details, education history, work experience, skills, and qualifications. It structures this parsed data into a standardized format in an Applicant Tracking System (ATS) or a connected database. 

Textkernel can also identify and classify information based on predefined criteria. Job titles, companies, dates, and keywords are good examples. You get the picture?  

A resume parser like Textkernel is a perfect companion for a document automation solution like Documill Dynamo. Whereas Documill Dynamo automates data output from the ATS to the dynamic fields in documents like work contracts, Textkernel ensures that the data input to the ATS goes correctly. With its AI, it also ensures that agents can search, filter, and compare applicants and candidates in the best and most productive way when selecting a new employee. 

Both solutions also support multiple document formats: PDF, Word and online/html.

How resume parsing works.

How resume parsing works.

Added agent productivity from compatible features

In fact, both of these advanced solutions can do much more to help the agents. 

As for Textkernel, these are some of the most important features, in addition to the ones described above: 

Multilingual support that accurately extracts information from resumes written in different languages. Structuring of data from resumes is supported in 29 languages and for job postings in 9 languages. This enables non-biased evaluation of candidates from diverse backgrounds. 

A job description API that leverages Large Language Models (LLMs). Users can input job-related parameters such as job title, required skills, location and the preferred tone of voice. These are then processed to generate detailed job descriptions. The functionality can also suggest skills based on a given job title for comprehensive job description generation. 

AI to check and improve data accuracy. Textkernel includes error handling mechanisms to find and correct parsing errors and inconsistencies. This ensures even higher accuracy and reliability of the extracted data.

When it comes to data output to automated documents, Documill complements Textkernel in these ways, for example: 

Multilingual support, enabled by the Documill Dynamo translation matrix. Documents can be generated using one template for multiple languages. Applicants and recruiters can feel more comfortable and secure, dealing with their native language. 

Anonymization: removing the name, age and other personal information of a candidate from documents like resumes and CVs. Where Textkernel enables non-biased candidate selection, Documill also brings fairness to selecting the winning candidate through resume and CV anonymization. Irrelevant details that might affect the recruiters’ impression of an employee can be removed from documents.  

Ready-made clauses: alternative snippets of text that the agents can choose from.  They get the choice they need for varying purposes without creating text themselves. 

Editable fields: sometimes it is still necessary for the agents to tailor certain sections of a document. This can be enabled by adding editing capability to just selected sections of a document. 

Workflows: let’s say you want to automate, for instance, document sending, approvals and signing. Documill Dynamo’s extensive workflow creation capabilities make it easy to do this – and much more. 

Forms: is there still a need for occasional manual data input? Documill Dynamo’s forms allow formalizing this. All necessary data will have to be entered in the correct fields in a form. From there, it finds its way to the right fields in the ATS. Submitting a form can be set to trigger an automated workflow, too.

Resume/CV automation can provide consistently nice-looking, easy-to-scan documents.

Resume/CV automation can provide consistently nice-looking, easy-to-scan documents.

Document types from real life

Staffing and recruitment documents come in many types and formats. Which are the ones that benefit from the interplay between Textkernel and Documill Dynamo? 

In fact, we are innovating new use cases all the time with our customers and partners. So, let’s keep things practical and just look at the kinds of cases that already have been implemented using Documill Dynamo. 


Obviously, applicant and candidate information has a key role in the documents that describe their qualifications. Of such documents, CVs are extensive lists of a person’sprofesional people’s profeachievements (including information on possible academic achievements). 


Resumes are usually 1- or 2-pagers that list just what is relevant for a given position.  

So, if somebody is applying for a position as a Salesforce developer, they will probably leave out from the resume their experience as a substitute teacher, when previously earning money for their university studies, for example. 

Candidate profiles 

A candidate profile, then, is again a more comprehensive representation of an individual’s professional qualifications, experiences, skills, and attributes relevant to a job role. These documents are sometimes used just internally by the staffing and recruitment agency, Usually, though, they are delivered to the recruiting organization as the basis for hiring decisions. 

(Note: the term candidate profile is also used about another document type of document: a personal profile of an applicant or worker. It may be based on a standardized personality test and include other information relevant to an organization and a job).

Job offers 

Sometimes, when the demand for a certain kind of a professional is high, it all goes the other way around: the staffing group sends a job offer to a contact they have. And to make the offer appealing, it is sweetened with personalized information from the ATS.  

We hear this is a fairly rare use case in the staffing and recruitment industry. Nevertheless, it is all viable for document generation – especially for companies that find contingent workers or contract employees for various temporary projects or fixed-term assignments. 

Employee/contractor agreements

When the offer has been made and accepted by the winning candidate, it is time to make an offer. The faster, the better, so enter document automation to accelerate the procedure. Again, dynamic details from the ATS are important to get the terms right and errors eliminated.

Employment certificates 

…And when that stint of employment or project is over, we all like to get a certificate to help us get the next one, don’t we? The data in the ATS comes in handy for creating one quickly and without fuss through automation – for the benefit of the employee and the employer.

Employee information forms, personnel questionnaires and other internal documents

The data parsed and stored in the ATS is useful also for organizations’ internal documents that may still be supplied by an external agency. Employee information form (or employee data sheet) is one example of such a standard-form document, whose automation we have facilitated.  

Organizations use this document type to gather essential details of their employees with sections for personal information, job-related data and emergency contact details. 

Various personnel questionnaires make another example of standardized internal documents.

Count on continuous innovation

However, as said before, there are new document automation use cases continuously coming up in the staffing and recruitment space. Did you get a new idea while reading this article? If you are using a Salesforce-based ATS like Byner or Bullhorn, Drop us a line and let’s start making it real!

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