Glassbox Launches Generative AI Assistant

Glassbox Launches Generative AI Assistant

GIA allows Glassbox users to uncover deep digital insights quickly and without technical knowledge or reliance on data and analytics teams.

Glassbox, a provider of digital experience intelligence for web and mobile applications,  announced the availability of its enterprise-ready AI assistant, which the company has named GIA (Glassbox Insights Assistant). Glassbox turned to Microsoft Azure OpenAI Service, which hosts OpenAI models fully within the secure Azure environment, to elevate the security and privacy standards of its previously announced AI assistant. In combination with Glassbox’s patented data privacy measures, users of the AI assistant can be confident that the conversational interface is protected with the level of rigor they expect from both Microsoft and Glassbox.

Glassbox co-founder and Chief Technology Officer Yaron Gueta, said, “We developed the AI assistant earlier based on OpenAI’s GPT model. However, our commitment to responsible AI and our exacting security, data privacy and compliance standards compelled us to turn to the Microsoft Azure OpenAI Service for its additional protections for potentially sensitive data shared or accessed through the new generative AI (GenAI) interface. GIA sets a new bar for what organizations should expect of GenAI solutions from their software providers.”

John Montgomery, CVP, Azure AI at Microsoft, said, “Microsoft Azure OpenAI Service is ideal for companies like Glassbox that need to deliver enterprise-grade GenAI solutions based on vast, proprietary datasets. “By using the power of our generative AI capabilities, Glassbox’s AI assistant can deliver a better experience to customers with the security measures of Azure.”

Glassbox captures millions or billions of digital experience data points for each of its customers every month that give them the richest possible set of data about their digital customer experience. GIA allows Glassbox users to uncover deep digital insights quickly and without technical knowledge or reliance on data and analytics teams.