ATS OnDemand applicant tracking system (ATS) has released a new machine learning technology to their platform. The new technology will provide a “Intelli-Match” recruit flow to drastically decrease time to fill as well as screening time for recruiters.

The technology analyzes keywords, education, experience, and other candidate information to comprise a list of the best matches. With this option, clients will be shown the most ideal candidates based on historical hiring data and unique machine learning.

The development team on the project, whose background include projects with Google and Intel, is comprised of true innovators in the machine learning space.

“Artificial Intelligence/Machine Learning is one of the most defining innovations that can be utilized in today’s recruiting. Ultimately, we will be able to define best matches utilizing this technology and then aggressively deploy it through the rest of our applications to predict the best type of hires overtime,” says ATS OnDemand CEO, Arthur Pereless.

The model does not take any of the key decision-making away from the client nor hide any information. One step further, the technology will analyze employee retention and calculate in what types of hires stay with the company for the long term. It will be able to learn far more about hiring practices than human analysis alone can provide.

“Most CEOs and CFOs realize that employee attrition is a bottom-line killer. AI / Machine learning will allow companies to notice patterns and mitigate attrition as they become more knowledgeable about hires that stick,” Pereless continued.

The new technology will be implemented on all job types and categories within ATS OnDemand, and work in conjunction with existing pre-screening question filters. With this product, every
aspect of candidate research will be enhanced by insights garnered from years of candidate data across multiple industries and job types.

For existing ATS OnDemand clients, a 3-month trial will allow clients to see the benefits of Intelli-Match in real time. It will then become an optional feature.

The model will be steps beyond what is possible for new players on the market due to the fact that ATS OnDemand has 15 years of data to use for the algorithm. From a technical standpoint, this current and old data will generate machine learning models meant to analyze the expectation that a candidate will be hired.