Restaurant lookups and writes
- 種類
- Demonstration project
- プロジェクト
- Restaurant guest service demonstration project
- 業界
- 飲食
The scenario and numbers in this demonstration project are simulated data.
- Industry
- Restaurants
- What was built
- Agents, tools and a semantic model, built on demonstration data
- Where the knowledge came from
- Demonstration restaurant chain data
Departments covered
- This demonstration project has these agents: customer service, operations, procurement and inventory, finance, and R&D.
Restaurant chain semantic model
- This demonstration project builds a semantic model on demonstration restaurant chain data.
What the toolkits do
- Each agent has its own toolkit.
- The lookups in this demonstration project include the menu, common questions and bookable time slots.
- The agents use tools to look up store revenue by time slot, dish margins, stock below the reorder point, and supplier prices and lead times.
- The agents also use tools to create purchase orders and add marketing campaigns.
Continuous improvement
- At restaurants like this, menus and common questions will change with the seasons.
- The agent will collect feedback on its answers from users. The feedback will go to Odin.
- Wrong answers will become tests. A change will be kept only if scores improve.
Get started
Book a two-hour workshop
AI feasibility review of a live workflow