Multi-Modal Semantic Search

Explore Superlinked's multi-modal search capabilities.

Multi-Modal Semantic Search enables you to search across diverse data types by understanding the context and meaning, rather than relying solely on keywords. Superlinked supports various modalities as primary features, including text, images, numbers, categories, and recency. If you prefer to use your own embeddings, Superlinked offers a CustomSpace feature to accommodate this need.

Superlinked allows you to fine-tune the importance of different attributes for each query by adjusting weights at query time, making the process straightforward and intuitive. To further simplify the experience, Superlinked offers a Natural Language Interface, enabling users to input their queries in plain, everyday language.

A standout feature of Superlinked is its ability to handle data objects holistically, eliminating the need for Reciprocal Rank Fusion (RRF), which significantly enhances system performance. For those who require keyword search capabilities, Superlinked also provides Hybrid Search, again without the need for RRF.

Below is a table showcasing projects built using Superlinked, demonstrating the power of multi-modal semantic search.

Recipe

App

Code

Key Features

Modalities

🏨 Hotel Search

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Repo Link