Solution Accelerator Series | Building Common Sense Product Recommendations With LLMs

Tushar_Parekar — Tue, 14 Jul 2026 14:51:42 GMT

Product recommendations help guide customers through their shopping journey. The Building Common Sense Product Recommendations With LLMs Solution Accelerator shows how retailers can use LLMs to develop recommendations for new-to-market products by turning product descriptions and metadata into embeddings, storing them in a searchable index, and using an LLM to recommend related products.

With this Accelerator, you get

Ready-to-use resources: pre-built code, sample data and step-by-step instructions ready to go in a Databricks notebook
Create embeddings from product data: convert product descriptions and metadata into embeddings.
Build a searchable index: store product information in a format that can be searched efficiently.
Recommend related products: use an LLM to suggest products based on their connection to other relevant items.
Support recommendation use cases for new products: apply common sense linkages where historical behavior may be limited.

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Solution Accelerator Series | Building Common Sense Product Recommendations With LLMs

With this Accelerator, you get