Demand forecasting
[ TODO: SKU-level weekly/daily forecasts across stores, channels, and promo windows. ]
SOLUTIONS · RETAIL
Train ML on your retail data — not someone else's benchmark
Orders, inventory, SKUs, promotions, store metadata — Langsat learns from your whole graph and deploys predictions to where your team already works.
USE CASES
What retailers build on Langsat
Personalization
[ TODO: next-basket and next-product recommendations for email, home, and PDP. ]
Stockout prevention
[ TODO: predict which SKU-store pairs will run out in the next 7 days. ]
Cart abandonment scoring
[ TODO: score likelihood of recovery and trigger the right incentive. ]
CUSTOMER
RetailCo: 30% fewer stockouts in 6 months
A mid-sized retailer replaced spreadsheets with Langsat relational ML.
[ TODO: one-paragraph summary. Full story below. ]
Read the full story →See retail ML in action
Book a demo. We'll build a model on a sample of your data in the call.