"Our Search AI Lake inherently supports dense vectors and features crucial for applications like GenAI and RAG," said Chief Product Officer Ken Exner.
"With this focus, customer budgets should remain manageable and scalable when needed, offering more control over managing workloads for different applications."
The platform uses indexing technology for search and cloud-native object storage, allowing the architecture to scale effortlessly while maintaining Elasticsearch's low-latency search performance.
Elastic differentiates between the various use cases of its search AI platform, introducing three serverless options to cater to specific application needs.
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