Using AI to illuminate “the dark side of the moon”

The HFS take on how Soroco’s flagship product Scout uses AI to find and fix hidden pains impacting how enterprises get work done

Despite an ever-changing work landscape and enterprise tech market, the key objectives for a business remain the same: revenue growth, cost reduction, superior customer and employee experience, and business continuity. Enterprises invest heavily in transformation programs to drive these goals, but most programs fall short. A significant blind spot causing this failure is the lack of understanding around an untapped source of business intelligence: interaction data.

While enterprises have visibility into their typical systems of work, such as ERP (enterprise resource planning) systems, enterprise applications, usual tools, and dashboards, there is a massively overlooked dataset that can provide game-changing insights. This dataset is generated from the trillions of human-software interactions that happen outside of typical systems of record. Teams spend large parts of their workday interacting with various applications and software, none of which are currently analyzed for improvements. But mining this “interaction data” can provide a rich source of insights that, if also correctly acted upon, unlock several competitive advantages.

Human-machine interaction data is complex and unstructured—and pervasive—in a business. Soroco’s flagship product, Scout, uses an artificial intelligence-multimodal (AI-multimodal) model to generate a work graph aimed at addressing this blind spot. It illuminates this untapped interaction data—what Soroco calls the “dark side of the moon”—to transform how enterprises work at multiple levels. Scout’s AI-multimodal model analyzes interaction data to unlock hidden opportunities for improvements in the areas of process excellence, cost optimization, customer and employee experience, revenue growth, and business continuity. Empathy is a foremost principle, facilitating employee privacy by anonymizing interaction data and only analyzing it at a group level.

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