Toast
Toast covers the restaurant floor and back office: orders and checks, menus, employees, time entries and restaurant locations. Checks carry the items, modifiers, discounts and tips; time entries carry the labor. Joined in a Lake with reservations, delivery and inventory data, Toast answers the margin questions a single location report cannot, from labor per cover to menu item profitability by daypart.
- Category
- Industry Solutions
- Type
- Restaurant POS
- Interface
- REST API
- Built with
- Connect Any API
- Credentials
- OAuth 2.0
- Docs
- Toast API docs
02Data
What you can sync.
- Orders
- Checks
- Menus
- Employees
- Time entries
- Restaurants
Report on Toast orders in DataPrism BI and ask an AI Mind questions about it in plain words.
Need more? Name any other Toast data the API returns, and the AI adds it to the connector.
03Credentials
Credentials you will need.
- OAuth 2.0 (client ID, client secret, refresh token)
Toast uses OAuth 2.0 (client ID, client secret, refresh token). You add the credentials once, when the AI asks for them, and it tells you where to create them in Toast if you need help.
04Questions
Questions you can answer.
Once Toast data is in your Lake, ask an AI Mind in plain words or build the answer in DataPrism BI.
- What is labor cost as a share of sales for each location and daypart?
- Which menu items have high sales but heavy discounting or voids?
- How do tips per server hour compare across locations?
- What is the average check size per guest on weekdays versus weekends?
- How long are checks open from first order to payment, by hour and location?
05How it works
How it works in DataMind.
-
Pick Toast.
Open Lake, pick Toast in the source picker and name the connection. Connect Any API opens with a ready prompt that points the AI at the Toast API docs.
-
Answer a few questions.
The AI reads the Toast documentation, then asks which credentials you will use, which data to sync (for example orders and checks), whether you want a one-time load or a recurring sync, and which accounts or filters apply.
-
Your data lands in Lake.
It builds the connector, tests it and shows you sample rows. Then Toast data loads into your Lake on your schedule, ready for the Warehouse, DataPrism BI and AI Minds.
06Pairs
Works well with Toast.
Sources teams join with Toast in the Warehouse, each one connected the same way.
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7shifts 7shifts schedules next to Toast time entries and sales show scheduled versus actual labor per cover. -
OpenTable OpenTable reservations matched to Toast checks give spend per reserved guest and table. -
MarginEdge MarginEdge invoice costs next to Toast item sales give theoretical food cost by menu item.
