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Layke Analytics

Layke Analytics

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Business Description
Layke is an API solution for intelligent screening and matching of candidates. Trained on a large amount of data, our algorithm has the capacity to read, interpret and analyze resumes as a human resource, but faster. What has always been largely done by a human being can now be done by a machine.
Long Business Description

Layke gains access to its customers through a single integration. By integrating Layke with third-party suppliers, we have the opportunity to reach a broad customer base via a single integration. In this way, the product is scalable.

In an ever-growing market, Layke supports recruiting companies to fill in positions faster and more efficiently based on clear and objective data. Our algorithm transforms a process where the unconscious human bias sometimes can’t be avoided and encourages transparent, skill-based recruitment.

Trained on a large amount of data, Layke’s algorithm has the capacity to structure, read and analyse documents as a human resource, but faster. The solution is built using advanced machine learning technology and can be seamlessly integrated with existing systems through a single API.

Supported by advanced machine learning technology, Layke can be divided into two parts: extracting information from documents and matching them with each other. When extracting the unstructured information, Layke uses modern machine learning technology where graph networks are in focus. When it comes to matching, with the help of language comprehension (NLP), Layke can compare different candidates to a job advertisement and answer which ones match best. By learning to group words together, the language model learns to understand different word classes but also which words belong together.

Among many competitive factors, the true strength of the solution lies in that it works on material that all candidates already have, and in systems already used by Layke’s customers.

Layke's technical solution is based on a combination of language models and graph networks, which makes our algorithm unique, thus not possible to copy.

Moreover, we have built our own tool for data labelling, meaning that we can identify raw data so that a machine learning model can learn from it and make predictions on new data.

And last but not least, our team possesses domain knowledge as well as technical expertise, which enables us to look at the solution from two crucial perspectives.

Based in
innovation, competence-based recruitment, integration
Total Funding
No funding announced yet
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