How AI restaurant reporting saved Public House Group 5 hours every week
Tom Foulser has spent twenty years in hospitality and fifteen working with tech stacks. When he joined Public House Group as a consultant in early 2026, one of his first tasks was rebuilding how the nine-site group used data. The Tenzo MCP was the first thing he reached for.
The GP discrepancy example Tom describes – two similar sites, 6% apart – took half an hour with the Tenzo connector in Claude. The output was a four-page document breaking down sales mix differences, wine versus spirits ratios, and pricing gaps across both sites. Addressing those findings is projected to recover 3-4% in GP within two weeks.
That’s the shift Tom keeps coming back to: not just that the answers are faster, but that questions operators would never have attempted before are now worth asking.
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