Imagine stumbling upon a shiny platform that claims to offer “done-for-you” searches with AI-powered relevance and conversational chat, all rolled into one, perfectly working out
Explore Semantic Highlighting feature in OpenSearch v3.0, how it works, and how it compares to the Sease Solr Neural Highlighting plugin.
It explores an AI-powered Filter Assistant to improve User eXperience in navigating search results efficiently and effectively.
Learn all the secrets of the new semantic search in Apache Solr 9.8 that uses LLMs to vectorise text and support natural language queries.
This blog post focuses on limitations in OpenSearch v2.17 during the implementation of search features and proposes practical workarounds.
This blog post explains a workaround implemented in Solr’s CloudMLTQParser to handle fields populated via copyField.
Curious about which large language models are dominating 2025? This comprehensive guide breaks down the top options—open-source, hybrid, and commercial, helping you choose the right AI tool for your needs.
This blog post explore a practical way to evaluate the performance of vector search results in Apache Solr.
How do you retrieve mathematical formulae? What are the main problems and challenges in mathematical formulae retrieval?
It explores translating natural language queries into structured Solr queries using LLM and metadata to improve search and user experience.
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.
