Case Study: Verisk improves customer satisfaction with super.AI

Verisk speeds sales call processing with super.AI to boost customer satisfaction

Verisk, a leading predictive analytics provider, wanted to build an active learning tool to optimize sales calls and improve customer satisfaction. They partnered with super.AI to help with the scalable processing of their customer call data, seeking a solution with multi-modal data processing and active learning capabilities.

super.AI implemented an audio processing solution that included audio transcription and query intent matching. This allowed Verisk to maintain strict data privacy by using their own internal data processors. The solution enabled them to process a large volume of calls quickly and input the data into an active learning algorithm in parallel. This significantly reduced deployment timelines and ultimately allowed Verisk to increase the relevance of sales call recommendations, leading to improved customer satisfaction, retention, and revenue.

Verisk