Tune Relevance with the Best AI and Large Language Models

Lucidworks makes it easy to capture greater intent and personalize search and discovery experiences using AI and data science models in Fusion.


Neural Hybrid Search

Lucidworks Neural Hybrid Search is a unique search methodology that utilizes the power of both deep learning and neural networks combined with traditional lexical and semantic search techniques. This offers a more intelligent and adaptive search experience that is better able to understand and respond to the needs of users, leading to more accurate and relevant results.

By combining these two approaches, Fusion offers several advantages over traditional search methods.

Neural— Powered by Neural Networks and Deep Learning

The neural component of Fusion enables it to understand the context and intent behind a search query. Fusion can analyze not just the keywords in the query, but also the relationships between them, to provide more accurate and relevant results.

Fusion learns from user behavior and feedback, further refining its results and improving user satisfaction. This makes Fusion more effective at understanding and responding to natural language queries

Hybrid— The Combination of Lexical and Semantic Search

The hybrid approach ensures that Fusion is not limited to a strict set of rules or predefined parameters.

Fusion can adapt to new data and language use patterns over time, improving its accuracy and relevance with continued use

AI for Search and Discovery

Fusion uses structured and unstructured data, product views or catalogs, and customer interactions to understand user’s context and intent and provide relevant search results.

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Ready to create better experiences in the moment? Contact us today to learn how Lucidworks can help you gather insights across all your customers’ touchpoints to deliver better outcomes across commerce, customer service, and your workplace.