[D] Are you seeing any compelling use cases of semantic search being leveraged at scale?

This page summarizes the projects mentioned and recommended in the original post on /r/MachineLearning

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  • WorkOS - The modern identity platform for B2B SaaS
  • InfluxDB - Power Real-Time Data Analytics at Scale
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  • Elasticsearch

    Free and Open, Distributed, RESTful Search Engine

  • Currently Elasticsearch does not support vector search, rather, they retrieve many records using their usual query approach and then rerank them with cosine similarity. So they use sparse retrieval followed by dense vector reranking.

  • semantic-search-through-wikipedia-with-weaviate

    Discontinued Semantic search through a vectorized Wikipedia (SentenceBERT) with the Weaviate vector search engine

  • Semantic search through Wikipedia with the Weaviate vector search engine

  • WorkOS

    The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.

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  • Weaviate

    Weaviate is an open-source vector database that stores both objects and vectors, allowing for the combination of vector search with structured filtering with the fault tolerance and scalability of a cloud-native database​.

  • Weaviate docs

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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