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Larderly: Purchasing agent for restaurant groups

An agent that turns forecasts, stock counts and supplier prices into draft orders, with spending limits and manager approval.

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Sector
Hospitality
Typical client
Restaurant group with several city-centre sites
Typical timeline
14 weeks
Typical team
3 engineers, 1 data scientist
Procurement agent preparing supplier orders from forecasts and stock counts
Demand forecast comparing expected covers with stock and supplier lead times
Supplier order history with approvals, delivery status and price variance

About this project

Restaurant buyers place orders under time pressure, using stock counts and instinct. Over-ordering turns into waste, under-ordering disappoints guests, and price comparison rarely happens.

Larderly drafts orders from forecast covers, current stock and supplier prices. Managers approve anything above a set limit and can see the reasoning behind every suggestion.

Objectives

  • Reduce food waste through better demand forecasting
  • Compare supplier prices on every order
  • Keep humans in control of spending

What’s delivered

  • Cover forecasting from bookings, events and history
  • Stock count integration across sites
  • Supplier price comparison
  • Draft orders with approval limits
  • Waste and margin reporting

Target outcomes

-30%

target food waste

90%

forecast accuracy objective

-2 pts

target food cost

100%

orders within approved limits

Technology

  • Claude
  • Python
  • dbt
  • BigQuery
  • React

Services involved

More work like this

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