Lucidworks Neural Hybrid Search™ utilizes the power of deep learning to combine the best Lexical and Semantic Vector models for accurate search results across the enterprise. Unlike other solutions, Neural Hybrid Search harmoniously blends out-of-the-box functionality and deep customization, particularly for custom-trained embedding models, LLM and AI models.
The neural component of Neural Hybrid Search enables it to understand the context and intent behind a search query. Analyze the keywords in the query and the relationships between them to provide more accurate and relevant results.
Neural Hybrid Search’s hybrid approach ensures that clients aren’t limited to a strict set of rules or predefined parameters. Easily adapt to new data and language patterns, improving accuracy and relevance with continued use.
91%Reduction in zero-results queries
10%+Mean Reciprocal Rank improvements
Neural Hybrid Search harmoniously blends out-of-the-box functionality and deep customization, particularly the ability to use custom-trained embeddings models, to set it apart in the search and discovery market
— Eric Immermann, Practice Director - Search and Content, Perficient
Significantly improve user search experiences by accurately interpreting the true meaning and context behind a user’s search to return highly relevant and satisfying results.
Unlike other vendors, Neural Hybrid Search gives enterprises a selection of embedding models (e.g. Lucidworks AI, bring your own models) to power the semantic component.
Lucidworks’ unified architecture consolidates different lexical and semantic components, allowing shared context and end-to-end optimization to reduce search ambiguity and operational cost.
By leveraging AI to power relevance, the system significantly reduces the reliance on manual rules, streamlining maintenance and improving adaptability.
Get started quickly with pre-trained embedding models and further enhance performance with custom-training models. relevance further with custom-training models
Personalize user experiences at scale with signal metadata and enterprise-trusted embeddings.
Lucidworks helps enterprises find the right models for their business with a selection of pre-trained open-source and custom-trained embedding models.
Reduce resource demand using proprietary AI to eliminate the need for constant rule curation.
Platform configuration to deliver high-performance search, reducing rule curation to near-zero
No delay or waiting for a batch job to assemble what similar products are available for each product.
Lucidworks was named a leader in the 2024 Gartner Magic Quadrant for Search and Product Discovery
Forrester Total Economic Impact for Lucidworks 2023: $13.9M net present value, <6 months payback
of documents indexed
50% of the top U.S. online retailers use Lucidworks
