Note on “Open Source” claims This blog post was originally written before the publication of the Open Source AI Definition, which provides a much-needed clarification
Discover in this blog post the Solr Neural Highlighter Plugin, which uses deep learning to highlight essential text for query answering.
This blog post showcases the vector search improvements that have been introduced in the latest versions of Elasticsearch (8.6 and 8.7)
This blog post aims to explore our contribution to Apache Lucene, which integrates a Word2Vec model to generate synonyms
This blog post describes an alternative and customized approach for evaluating ranking models through the use of Kibana.
This blog post explains all the steps required to implement Text Embedding and Vector Search directly in Elasticsearch in a very simple way.
In this blog post, we show in practice how you can use Elasticsearch to run a full end-to-end neural search.
This blog post shows an example of how to create an Apache Solr performance test using the Apache JMeter tool.
An end-to-end tutorial to implement Neural Search in Vespa. From documents and model preparation, to embeddings creation and k-NN queries.
In this blog post, we show in practice how you use Apache Solr to index and search vectors and then run a full end-to-end neural search.
We are Sease, an Information Retrieval Company based in London, focused on providing R&D project guidance and implementation, Search consulting services, Training, and Search solutions using open source software like Apache Lucene/Solr, Elasticsearch, OpenSearch and Vespa.
