Solution Accelerator Series | Improve On-Shelf Availability with Databricks Lakehouse

Om_Jha — Wed, 25 Feb 2026 09:34:34 GMT

Use AI to predict out-of-stock and keep shelves full!

Out-of-stock (OOS) is one of the biggest drivers of lost sales and poor customer experience in retail. This Improve On-Shelf Availability Solution Accelerator shows how to use real-time data, AI-driven OOS modeling and the Databricks Lakehouse Platform to detect and fix on-shelf gaps before they hurt revenue.

Get everything you need in a ready-to-run Databricks notebook, including pre-built code, sample data, and step-by-step instructions.

Key highlights

Use real-time insights to react faster: Ingest streaming data to detect OOS situations in near real time and trigger rapid responses across stores and channels.
Drive more sales with better availability: Apply AI-based out-of-stock modeling to keep products on shelves and reduce missed sales opportunities.
Power both retail and supply chain use cases: Extend the accelerator from store-level on-shelf availability into broader supply chain optimization scenarios.
Scale to any size operation: Build on the Lakehouse so your solution can grow from a single banner or region to global, enterprise-wide deployments.

Ready to start improving on-shelf availability with AI? Use this Accelerator to go from insight to impact and turn OOS into a competitive advantage.

topic Solution Accelerator Series | Improve On-Shelf Availability with Databricks Lakehouse in Announcements

Solution Accelerator Series | Improve On-Shelf Availability with Databricks Lakehouse

Key highlights