How does Vervoe’s AI feature work?

What we have developed is not a simple “one size fits all” approach. Our machine learning algorithms are multilayered, unique, and unlike any other. Not only do we learn about the candidates, but we also learn the unique preferences of each individual employer.

Vervoe's AI feature can predict scores for any type of skills assessment. We have found a way to create bespoke algorithms for every employer and specifically for every one of their open roles. The algorithms adapt to the unique preferences of the employer and don’t require a specific set of questions.

Vervoe's machine learning feature consists of 3 models that help calculate candidate scores:

1. The "how" model: This model analyzes a candidate's behavior on the platform- how they complete the assessment. For example, it observes how long it takes a candidate to respond to questions, spelling, and grammar, how many times they make changes to an answer, are they copying and pasting, etc. It is looking at many data points to help score their performance. (It's important to note that there are no right or wrong behaviors. Our machine learning models simply learn what kind of behaviors correlate with good or bad grades, and it's different for every type of role.)
2. The "what" model: The system analyzes the quality of the candidate's response. If you use questions from our library, the AI has the data it needs to analyze the responses from the start. If you customize or add your questions, then the AI will require correct answer samples plus enough good, bad, and okay answers graded for it to analyze the responses to calculate a more accurate score.
   
3. The "preferences" model: The AI is learning from the employer's preferences as they manually grade responses. For example, it might discover that an employer prefers short answers vs. long-winded answers or that an employer may be more sensitive to spelling and grammar than other companies.

Please note that for video and audio answers, the AI is not looking at facial features or voice intonation. It reviews and analyzes a transcript for that response.

The AI feature will score and rank the candidates based on the combination of data points compiled from the three models. 

To get the most out of this feature, we recommend you review this article here that explains how to optimize and train the AI to grade with more accuracy in your account.