Precision planning for restaurant operations.

Demand Forecasting

uses machine learning algorithms trained on a large library of external datasets (e.g. weather, holidays, school schedules) and historical sales for products at the individual store level.
Recommended Ordering Quantity

provides easy-to-use ordering guides with suggested ordering quantities. Managers can double-click on suggested order quantities to understand the “why” behind each prediction.
Integrations with POS Systems

make managers and operators’ lives easier. With a simple workflow, managers can replenish their inventory and get ready for the week with a click of a button.

We work with multi-unit restaurants who are excited to dive into their data and manage food cost variance. Reach out to us if you are curious about Tarragon Systems and want to give it a try for free.
We are a team of MIT researchers focusing on machine learning in supply chain logistics. Our prior backgrounds in software engineering, sustainability, and restaurant management make us uniquely positioned to help managers leverage their own data to reduce waste and improve profits.

Demand Forecasting