Expo - 2026 Pricing, Features, Reviews & Alternatives

Expo is an artificial intelligence platform designed for multi-unit restaurant operations. The software consolidates disparate data sources into a unified analytical system so that operators can access a central intelligence layer across various service formats including quick-service, fast-casual, casual dining, and fine dining. The platform eliminates the need for manual data exports, spreadsheet consolidation, and dedicated business intelligence resources by connecting point-of-sale systems, inventory management, labor scheduling, and guest feedback in a single source of truth.

The platform follows a four stage workflow that transforms operational data into actionable decisions. Expo integrates automatically with common restaurant technology systems such as Toast, Restaurant365, Crunchtime, Par, NBO, Square, and DoorDash. The software assembles dashboards on a customizable schedule and distributes them to designated recipients before operational meetings. The dashboards feature metrics including net sales, labor cost allocations, and food cost measures by location.

Expo’s Model Context Protocol integration enables managers and district personnel to query consolidated data through natural language interfaces with AI tools such as Claude and ChatGPT on desktop applications. The platform interprets queries without requiring SQL, prompt engineering, or technical skills and delivers clear answers alongside specific recommendations. The system detects operational inefficiencies such as portion control discrepancies, ingredient waste patterns, and performance anomalies and proposes corrective measures such as standardizing portions at selected locations.

The platform maintains a tech stack agnostic architecture so that operators can retain existing systems regardless of vendor. Integration setup and ongoing maintenance are executed by the Expo team without internal IT resources or data analysts. Expo provides an alternative to traditional in-house analytics builds that typically require extensive development time and ongoing engineering support by delivering custom dashboards within days of deployment. The Model Context Protocol functionality removes the intermediary role of data analysts by enabling direct conversational access to business data through AI interfaces for operational decisions.