Case Study: Grainger achieves faster, more accurate product discovery with Databricks

Using GenAI innovation to help keep industries up and running

Grainger, a leading North American MRO distributor, needed a faster way to retrieve product information from its massive 2.5 million-item catalog to support a high-traffic e-commerce site and customer service team. With Databricks and its Mosaic AI capabilities, Grainger worked to improve search, data handling, and AI model workflows for more responsive product discovery.

Databricks implemented a RAG-based solution using Vector Search and Model Serving to sync product data in real time, automate embeddings, and let Grainger experiment with multiple LLMs through a single API. The result was more accurate, near-instant search responses, less manual pipeline maintenance, and improved scalability, efficiency, and customer satisfaction.

Grainger

Ranga Raghunathan

Director, Applied Machine Learning