Elastic Enterprise Search 8.8: Semantic search in a few clicks
Blog post from Elastic
Elastic Enterprise Search 8.8 introduces enhanced AI-powered search capabilities, including the new Elastic Learned Sparse EncodeR (ELSER) model, which improves search relevance without extensive expertise in machine learning. This release features an expanded catalog of open code database and storage connectors, allowing seamless integration and syncing of data from popular systems like MongoDB, MySQL, Postgres, and Microsoft SQL, which are optimized for advanced search applications. Elastic has also enhanced its Web and Search Analytics tools, providing out-of-the-box dashboard visualizations that help measure search success by analyzing query terms and user behavior. Additionally, the release includes a technical preview of Search Applications, enabling developers to simplify search architecture by using preset templates that combine lexical searches and ELSER-powered queries. Available on Elastic Cloud, this version offers a comprehensive suite of tools for creating personalized, robust search experiences and includes numerous usability improvements alongside new connectors for workplace content like Atlassian Jira and Microsoft SharePoint.
| Trend | Post Mentions | Total Month Mentions | Posts | Companies | MoM |
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| AI Model Fine-tuning | 1 | 169 | 75 | 54 | - |
| Kubernetes | 1 | 1,589 | 172 | 71 | +19% |
| Vector Search | 1 | 1,125 | 124 | 52 | +87% |
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