Hybrid Search in Data 360 brings improved RAG to gen AI apps. Admins and developers can fine-tune & optimize RAG performance using hybrid search ranking functions to achieve elevated search results.
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Optimize Your RAG in Data 360 with Hybrid Search Ranking
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, Senior Director, AI Architect, Salesforce
, Director of Product Management, Salesforce
Role: Developer
Industry: Technology
Product: Agentforce
Session Level: Advanced
Session Type: Theater
Session Summary: The session focused on optimizing search capabilities within Salesforce's Data Cloud using hybrid search, which combines both vector and keyword search techniques. Through a real-life scenario involving extreme weather conditions in Ireland, the presenters demonstrated how hybrid search can retrieve critical, up-to-date information by balancing recency and relevance. Attendees learned about the configuration of ranking factors like recency and popularity, as well as advanced ranking functions, including a newly introduced deep learning-based fusion ranker. These innovations aim to enhance the accuracy and trustworthiness of search results by leveraging domain-specific terms and grounding AI responses with citations, improving user experience and decision-making processes.
Key Takeaways:
• Hybrid search blends the strengths of vector and keyword search to deliver accurate and relevant results, especially in scenarios involving domain-specific terms or evolving information.
• Configurable ranking factors, such as recency and popularity, allow organizations to prioritize the most relevant or frequently accessed data, ensuring timely and accurate responses to user queries.
• The introduction of advanced ranking functions, including the deep learning-based fusion ranker, enhances search performance across various use cases and domains, reducing irrelevant results while improving reliability and user trust.
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