Harver launched Harver CHAT, its new conversational AI hiring tool which claims to automate the job application process and streamline the candidate experience. With it, the company hopes to help organizations reduce time-to hire while also boosting their employer brand.
Harver CHAT uses AI to ask candidate screening questions in “a conversational way,” guiding them through the application process. Harver believes this approach will better engage prospective employees than the traditional job application forms.
The company said that between the competition in the current market and the “increasing candidate expectations,” organizations need to create a better hiring experience. Harver CEO Scott Landers commented, “Today’s workforce challenges require employers to be efficient and engaging at all touchpoints along the hiring process.”
According to the company, Harver CHAT is capable of responding to questions the candidates pose in real time; its conversational knowledge is fully configurable, allowing employers to train the solution to not discuss sensitive or unrelated topics.
Job Application Assistance
The new tool makes the application process easier for candidates, by allowing them to ask questions and get them answered on-demand 24/7, without the need to contact an employee. The product can also help them to gain a better understanding of the role and the company they are applying to, such as the company culture, benefits, pay or hours.
In addition, Harver said CHAT can help save TA teams time by “collecting required candidate details before logging them within the appropriate applicant tracking software and routing the candidate to the next step in the process.”
In May, Harver implemented TruEra, a management solutions provider, to help with the performance of Harver’s behavioral assessment solutions and ensure compliance with New York City’s AI regulations for HR applications. Harver said it uses AI diagnostics, testing and monitoring to evaluate its behavioral assessment solutions on an ongoing basis, including the bias metrics specified by regulators.
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