Transform Retail with Retrieval Augmented Generation (RAG): The Future of Personalized Shopping

The combination of retrieval augmented generation (RAG), CPUs, and model optimization techniques delivers the trifecta of inference engine quality: latency, fidelity, and scalability.

Companies that want to deploy an AI application (such as a support chatbot) can use OpenVINO and LangChain to implement an efficient RAG pipeline, and utilize OpenVINO's benefits.

FoundationFlow, Bud Ecosystem, and Intel collaborate for an innovative RAG solution, delivering 60% improvement in handling product catalog queries.

This solution brief outlines a reference design for an Intel-optimized Retrieval-Augmented Generation (RAG) solution and demonstrates its compatibility with industry-standard software components.

RAG architecture with annotated training data can help public sector employees collaborate and access relevant information faster.