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You Don't Need Re-Ranking: Understanding the Superlinked Vector Layer
Discover how Superlinked eliminates the need for re-ranking in vector search systems. Learn about its unified multimodal vectors, dynamic intent capture that improve search relevance, speed, and scalability.
Superlinked is a Python framework designed for AI engineers to build high-performance search and recommendation systems that unify structured and unstructured data into multi-modal vectors. This approach streamlines search processes by preserving structured attributes like popularity metrics alongside unstructured text semantics, improving retrieval relevance without additional layers or complex filtering. Superlinked makes it easier by natively supporting multimodal scoring, letting us assign dynamic weights at query time, and apply hard filters directly.
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