Solutions

The partnership between Elastic as a vector database and Red Hat OpenShift AI offers a compelling solution for public sector organizations looking to implement AI and ML in their environments.

The explosive growth of AI technology adds complexity in choosing production-ready tools. Elastic’s AI Ecosystem empowers developers with Elasticsearch vector database integrations and enables tech providers to accelerate innovation.

Elastic 8.16 includes many high-impact capabilities, including Elastic being the first vector database with BBQ (Better Binary Quantization), LLM observability for Amazon Bedrock, extended cloud security provider integrations, and more.

Introducing a redesigned Kibana navigation menu for Elastic Cloud Hosted deployments. Three new "Solution Views" organize the interface into specialized menus for Search, Observability, and Security.

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.

AutoOps significantly simplifies Elasticsearch cluster management with performance recommendations, resource utilization and cost insights, real-time issue detection, and resolution paths.

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.

Modern search systems have made great leaps in the accuracy, relevancy, and usefulness of results by leveraging AI-based capabilities. Now, generative AI is changing how forward-looking organizations approach search and knowledge management.

US Tribal Nations are exploring opportunities to use generative AI to enhance customer experiences at casinos, resorts, and more. However, to fully harness the power of generative AI, Tribal Nations first need to overcome key data challenges.