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"Leveraging Multi-Model Semantic Retrieval Augmented Generation with the Progress Data Platform"

Generative AI enables unprecedented creativity, efficiency and decision-making capabilities across industries. But it comes with significant challenges such as accuracy, context awareness and the reliability of generated content. Retrieval-Augmented Generation (RAG) helps address these limitations by seamlessly integrating real-time retrieval of accurate, proprietary data into generative processes.

This whitepaper explores how combining RAG with multi-model semantic integration can amplify your AI capabilities, creating solutions that are accurate, contextually relevant and rich in data from structured, unstructured and semi-structured sources. The Progress Data Platform supports multi-model RAG, providing enterprises with a robust, scalable and governed foundation to manage and integrate diverse data sources.   

Download the whitepaper to uncover: 

• Benefits of multi-model semantics and RAG in overcoming traditional GenAI limitations 
• Advantages of implementing multi-model RAG with the Progress Data Platform 
• Real-world applications across finance, healthcare and e-commerce, and the tangible business benefits achieved  
• Step-by-step guidance to successfully deploy multi-model RAG in your enterprise 

Harness the full potential of generative AI—download the whitepaper today and start delivering innovative solutions and driving impactful business outcomes.

Offered Free by: Progress Software Corporation
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