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Solution Accelerator

Large Language Models (LLMs) for Retail

Pre-built code, sample data and step-by-step instructions ready to go in a Databricks notebook

LLMs for Retail

The practical impact of generative AI and large language models (LLMs) on society is growing by the day. Within the retail industry, practical applications for innovations such as ChatGPT and Dolly are widespread — including the rapid search of large product catalogs, streamlining customer service with intelligent chatbots, analyzing customer data and sentiments for personalization, and more — all with the goal of increasing customer satisfaction, loyalty and sales.

The fuel that makes an LLM run effectively is high-quality data, and lots of it. Databricks Lakehouse for Retail provides the underlying architecture and tooling to harness your customer and operational data to easily deliver generative AI and LLM models to your entire organization.

Deploying LLMs with Databricks: To use the latest Databricks technology for Retrieval Augmented Generation (RAG) in your GenAI applications, please reference the LLM Chatbot with RAG Demo 

LLMs for Retail

Enhancing product search

Large language models (LLMs) can be used to harness the rapidly growing range of content and goods to ensure customer searches yield the desired results. With the Databricks Lakehouse for Retail, organizations can:

  • Unify product, query and label data within a retailer’s product catalog

  • Enable rapid search with analytics against numerical arrays

  • Train and deploy an LLM model with Databricks Model Serving

Download notebook

Build an LLM-enabled chatbot

Use this Solution Accelerator to build a context-enabled LLM-based chatbot solution using content taken from our own knowledge base (made publicly available so that users can recreate our work).

The step-by-step code behind this work includes data preparation, agent development and deployment to a microservice that allows you to integrate the agent into any number of applications, and provides sufficient comments and documentation to help your organization understand the solution and get started with their own.

Download notebook

Automate product review summarization

Use this Solution Accelerator to streamline the summarization of customer feedback, allowing your organization to:

  • Process a high volume of reviews at a lower cost

  • Collect feedback from a wider range of products and summarize these on a regular basis

  • Task an LLM to extract different sets of information from each high-level category of reviews

Download notebook



Enhancing Product Search with Large Language Models (LLMs)


Retail in the Age of Generative AI


Fine-Tuning Large Language Models with Hugging Face and DeepSpeed

Deliver AI innovation faster with Solution Accelerators for popular industry use case. See our full library of solutions

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