Conversational Analytics at Scale: How a Global Restaurant Chain Unlocked Revenue Insights with PromptQL

The company, one of the world's largest restaurant chains, faced a challenge in getting insights from its vast data warehouse and operational systems. Business teams had limited access to accurate answers due to the complexity of querying the data and the lack of expertise among analysts and data experts. However, by layering PromptQL on top of their data, they were able to transform how they engage with data, gather insights, and make decisions. With PromptQL, business users can ask real questions in plain English, such as "Why are delivery sales down in Munich?" and receive accurate answers with full reasoning and explainability. The solution introduces three major innovations: understanding the business context, self-correcting and resilient querying, and transparent and explainable results. These innovations enable PromptQL to provide reliable insights, build trust among users, and unlock revenue growth without overhauling the existing data stack. The company is now expanding PromptQL access to more teams and use cases, integrating operational actions directly into the AI loop, and building reusable programs to power repeatable workflows.

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