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Recruit.ai, a startup by Nazarbayev University students, will reduce candidate analysis time from several weeks to 2–3 days. The program uses a neural network to automate the initial stages of selection, reducing recruitment costs by 2.4 times and the profile review period by 40%. The accuracy of matching criteria is approximately 91%, while the final selection remains with a human.
Often, employees have to wait several weeks to be selected from all candidates. Neural networks will reduce the analysis to 2-3 days. Recruit.ai - a startup for automating the recruitment process of the innovative cluster of Nazarbayev University Risk-taking Inspiration Synergy. Students Nabi Muratbek, Maxim Mametkulov, Timur Aldishev developed a program for candidate selection. The startup received funding in the amount of 2 million tenge. According to the developers, Recruit.ai will reduce recruitment costs by 2.4 times. It will also reduce the period of consideration of candidate profiles by 40%. At the same time, the accuracy of matching candidates to criteria is about 91%. Many organizations approach recruitment in a standard way: resume analysis, tests, and interviews (often multi-level). This approach allows for a comprehensive evaluation of the candidate but takes a lot of time. Of course, no one manually checks tests, but the recruiter is responsible for reviewing and analyzing resumes. The creators of Recruit.ai propose using artificial intelligence and machine learning. This will automate the first three stages of selection and combine them into one program. That is, three weeks of analysis will turn into 2-3 days. Some companies already use similar practices. In the US, AI filters 70% of all resumes. But the developers explain that Recruit.ai is unique in its comprehensive approach and in the created self-learning neural network. Thus, the program will help find the ideal combination of employee-employer. The feature of the technology is gamification of the recruitment process. The Recruit.ai game involves performing actions according to a given plot. Based on the candidate's choices and actions in various situations, the program's neural network will create a psychological and personal portrait of the person. A similar method was used by PricewaterhouseCoopers, moving from verbal and numerical tests to games. Using a series of short games, PwC evaluates logic, mathematical abilities, reaction, and memory. Personal experience allows us to assert that games are no less capable of characterizing a person. This format relaxes, reduces stress levels, and allows understanding the true mindset of a person. But this does not mean that the program will completely handle personnel selection. Recruit.ai only handles the initial stages of recruitment. Only candidates who meet the company's criteria will reach the interview with managers. That is, the final part of the selection will still be conducted by a person. At the same time, the HR manager will have access to a full analysis compiled by the program. Thus, within a short period, a candidate's portrait will be created that most accurately corresponds to reality.
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