(Bulk) upload, Email inbox, Textkernel's Apply-With widget, Google
Drive, Microsoft OneDrive, Dropbox, LinkedIn, Xing, Google+ and
Viadeo, as well as SOAP and Rest api
Textkernel develops its resume/CV parsing software with Machine
Learning technology. Textractor, the company’s core engine, uses
thousands of examples learn how to automatically recognise data
from resumes/CVs and profiles. Textkernel is the first company to
release resume parsing models based on Deep Learning, available for
both English and German, which results in a significant error
reduction of up to 30% when parsing resumes/CVs. Deep Learning is
being rolled out to additional languages on an ongoing basis.
Extract! resume/CV parsing seamlessly integrates into the back-end
of any CRM or ATS and can be added to the front-end of your career
site through the Apply-with Widget. It can be used as a web-based
application (in the cloud) or locally installed (on-site). Data
extracted from the resumes/CVs or social profiles can be customised
according to the customer’s database fields or the requirements of
the customer’s current recruitment or HR system. They can then
build an optimum resume/CV database ideal for sourcing, analysis
and reporting.
Textkernel develops its CV parsing software with machine-learning
technology. Using thousands of examples, Textractor, the core
engine of Textkernel, learns to automatically recognise data from
CVs and profiles.
DOC, DOCX, PDF, RTF, HTML, TIFF, TXT, XML and EML. LinkedIn,
Facebook, Xing and Viadeo. Hard-copy documents, such as CVs
received by post or fax and image files.
