Superlinked

Superlinked

The Vector Computer

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Superlinked is a compute framework for your information retrieval and feature engineering systems, focused on turning complex data into vector embeddings. Vectors power most of what you already do online - hailing a cab, finding a funny video, getting a date, scrolling through a feed or paying with a tap. And yet, building production systems powered by vectors is still too hard! Our goal is to help enterprises put vectors at the center of their data & compute infrastructure, to build smarter and more reliable software.

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Features

Advantages

  • Combine text, images and structured metadata into multi-modal vectors that fully describe your entities in their complex context.
  • Smoothly navigate the trade-off between multiple competing objectives like relevance, freshness and popularity.
  • Manage the compute layer that sits between your data infrastructure and your vector database through a simple python SDK.
  • Combine semantic relevance and user feedback to reliably retrieve the optimal document chunks in your Retrieval Augmented Generation system.
  • Combine semantic relevance and document freshness in your search system, because more recent results tend to be more accurate.

Disadvantages

  • Can be complex to set up and configure.
  • May require specialized expertise to use effectively.
  • Can be expensive to implement and maintain.

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