Layke Analytics offers an AI solution for recruiting automation (selection-and matching) during the hiring process. The embedded algorithm allows the tool to read, interpret and analyze the job seeker's CV by determining whether the candidate is a proper match to the job description. This whole process, which is now automated, is usually time-consuming. The company's primary target groups are recruiting firms and staffing agencies, HR departments.
Anna Rapp, CEO of Layke Analytics
When we interviewed Layke Analytics’ CEO, Anna Rapp, a couple of years ago, the startup company has been at the beginning of its journey, starting using several of the JobTech Development's APIs.
We continue using Historical Ads, JobSearch, and JobAd Enrichments that have been part of our business development journey since the beginning of 2020. Since last year, we have started using JobSearch in developing a new service tool, which makes it easier for the user to search efficiently through candidate databases. The APIs are used partly as a basis for training data, and to create lists of roles and competencies.
Our next step is to roll out the search tool and the technology we have developed to the market to make it available to anyone who wants to optimize the candidate search in internal and external databases. The long-term goal is to contribute to a better standard of how we work efficiently with candidate databases. Simply, we do not have the necessary conditions to be able to search for candidates effectively. It results in losing great talents and relevant resources. A frequent feedback from our users, which in most cases are recruitment and staffing agencies, is that they usually use about 10% of their existing candidate databases. There is an already unused enormous potential in the current candidate databases, if one has the right tools and conditions to search thoroughly.
A lot of what we are doing refers to language understanding and the connection between different roles and competencies. Therefore, it is of utmost importance for us to build a good language model using relevant data on the market we are operating on. Collaborating with JobTech Development gives us access to large amounts of data from the open platform, namely from the Swedish labour market, and contributes to developing our services and tools. There is a relevance in the database, which cannot be compared to the extracted data from the American market, for example.
While continuing to develop our services and technical solutions, I consider JobTech Development among our key partnerships. We are constantly looking for more and new data sources. It means we are not replacing what we have already had and built; we are complementing it. Furthermore, I know that JobTech has a lot of exciting future projects in the education market, which I think we can benefit from in developing new services and tools.