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Until now, analytics teams have relied on data kept in the data lakehouse/warehouse. Any additional value that could be derived from the remaining 80% of unstructured data (conversations, transcriptions, and beyond) has been inaccessible without painful, manual exploration.
Want to understand the latest competitive threats? Or find a broken product feature driving churn? What about an internal bottleneck causing employees to waste time submitting expense reports? Or the promises being made by sales outside of contracts because the process was too laborious to record otherwise? These problems fester until they become too big to fix, and yet they would never show up in a dashboard.
Every week, teams deliver reports that indicate change. Maybe the top of a sales funnel is getting bigger or a customer success team is driving down time to resolution. Or perhaps an A/P team is getting faster at paying invoices, though possibly at the cost of some increased legal risk. But none of these headlines fully explains what’s happening.
How can teams better understand the factors behind change? The answer lies in the work itself - unstructured conversations between customers, employees, and partners. By fitting those to the data, leadership teams can more confidently make decisions that have last impact.
Three converging forces make this the time to take a new approach: First, enterprise knowledge is increasingly digital and accessible. Second, foundation models have reached a threshold of understanding context and semantics across different media. And third, notification fatigue has created demand for truly intelligent systems.
With distributed teams becoming the norm, the need for the deeper understanding of data has never been greater. The cost of missed connections between scattered information continues to grow, while the technical barriers to solving these problems have dramatically fallen. Let us show you what the future of insights looks like.
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