Solutions
Learn more about Elastic enterprise search, observability, and security solutions, built on a single, flexible technology stack that can be deployed anywhere.
Search
Observability
Security
ElasticGPT: Empowering our workforce with generative AI
ElasticGPT is a generative AI assistant designed to help Elastic employees quickly find information and answers from company data. Teams can use ElasticGPT via a self-service experience to summarize, categorize, and analyze information and data.
From App Search to Elasticsearch — Tap into the future of search
We're discontinuing App Search in version 9.0, but Elasticsearch offers everything you need to build AI-powered search experiences. With integrated ML tools, semantic search, and reranking Elasticsearch simplifies search development and migration.
More on Elastic Search
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0 to 60 with Elastic AI Assistant for Search and Azure OpenAI
Elastic’s new AI Assistant for Search will be available soon. It can use Azure OpenAI models to be the built-in copilot for developers building with Elasticsearch from within Kibana to make interactions within Elastic smoother and more intuitive.
Elasticsearch achieves Certified Software Solution status for Microsoft Azure
Elastic has achieved another significant milestone by becoming a Certified Software Solution for Microsoft Azure. This rigorous validation process ensures that Elastic adheres to Microsoft’s high standards for security, performance, and reliability.
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Elasticsearch 8.16: Production-ready hybrid conversational search and an innovative quantization for vector data that outperforms Product Quantization (PQ)
Elasticsearch 8.16 introduces Better Binary Quantization (BBQ), generally available reciprocal rank fusion (RRF) and retrievers for a production-ready hybrid conversational search, and a suite of tools to streamline your workflows.
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Optimize your RAG workflows with Elasticsearch and Vectorize
Vectorize’s integration with the Elasticsearch vector database allows AI engineers to quickly create a reliable RAG pipeline and focus on building applications instead of spending time on preprocessing and determining the best vectorization strategy.
