Imagine your plight scrolling through your inbox and searching for the right candidate!
Moreover, the resumes are in various languages. How many resumes would pop up in your email every day?
Well, maybe 10 to 50 resumes per vacancy. A rough estimate would be around 200 CVs per day. Isn’t screening so many resumes terrifying?
Wouldn’t it be good if you didn’t have to do all this manually? Now, this is where a multilingual resume parser fits in!
Resume Parser and its Benefits
A resume parser is a deep learning/AI framework that identifies complete information from resumes and converts unstructured data into structured data.
RChilli’s resume parser extracts candidate data from resumes in 140+ data fields.
This simple process saves recruiters’ hours every day, allowing them to spend more time on candidate interviews. A resume parser removes several manual functions for both recruiters and applicants and speeds up the screening process.
Who Uses It?
A resume/cv parser is used on job boards, applicant tracking systems (ATS), and enterprises to parse and accelerate the application process.
Many Languages, One Parser - Multilingual Resume Parser
A multilingual resume parser parses in multiple languages. RChilli’s resume parser auto-identifies the language of the resume and efficiently extracts the data. Currently, we parse in 30+ languages and offer full parsing in the following languages:
Why Do Businesses Need Multilingual Employees?
Modern businesses need employees who can interact with clients in their language. It helps organizations to give better customer support to their non-English speaking clientele.
According to the American Council on the Teaching of Foreign Languages (ACTFL), the following are the key findings of the report published in August 2019:
Nearly 32% of employers are highly dependent on language skills other than English.
Spanish, Chinese, and French languages are currently in the highest demand among U.S. employers.
Nearly 34% of U.S. employers report that their staff is not currently meeting their foreign language needs.
What Sets RChilli Apart from Others?
What makes us stand out from the rest is our rich feature list and easy integration. Some crucial elements of our cv parser are:
Fast and accurate
Scalable and configurable
Uses AI and NLP
Parsing in 30+ languages
7 Factors to Consider while Choosing a Resume Parser
While selecting a CV/resume parser, keep the following points in mind:
Parse resumes in all formats, such as DOC, DOCX, PDF, RTF, TXT, ODT, HTM and HTML, DOCM, DOTM, DOT, DOTX
Easily integrates with your existing HR system
It should be capable of extracting the complete resume information in maximum data fields
Creates an executive or management summary so that it can be of help to the recruiters
Multilingual support that automatically identifies region and language to parse information
Should be able to parse resumes in bulk
Allows users to parse resumes/jobs from single or multiple email boxes
From supporting multiple file-formats to extracting data from various inboxes, RChilli provides all the above features.
Return on Investment (ROI) and Resume Parser
When you’re thinking of getting a resume parsing tool, you need to ensure that you receive a sizable return on investment (ROI).
When you invest in a lower quality system, you may find that it doesn’t do the job well. It hasn’t added any benefit to your existing structure. So, why not invest in a better system so that you could get a much better ROI?
Well, you won’t be disappointed if you invest in RChilli’s multilingual resume parser. Our resume parser supports parsing in 30+ languages. It auto-identifies the languages of resumes and extracts the data.
Our resume parser offers unmatched accuracy while converting resumes and CVs into XML or JSON output. With a comprehensive feature set such as multilingual and taxonomy support, RChilli’s cv parser is beyond comparable.
Now that you know about resume parsing and its associated benefits, don’t waste your precious time going through infinite resumes.
Get rid of the old-school technique of reading resumes and invest in RChilli’s resume parser.
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