A new interface enables developers to iterate and build RAG applications for A/B testing LLMs, tuning prompts and chunking data
Elastic the Search AI Company, announced Playground, a low-code interface that enables developers to build RAG applications using Elasticsearch in minutes. Playground’s intuitive interface allows users to A/B test different large language models (LLMs) and refine retrieval mechanisms to ground answers with the proprietary data indexed into Elasticsearch indices.
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“While prototyping conversational search, the ability to experiment with and rapidly iterate on key components of a RAG workflow is essential to get accurate and hallucination-free responses from LLMs,” said Matt Riley, global vice president and general manager, Search at Elastic. “Developers use the Elastic Search AI platform, which includes the Elasticsearch vector database, for comprehensive hybrid search capabilities and to tap into innovation from a growing list of LLM providers. Now, the playground experience brings these capabilities together via an intuitive user interface, removing the complexity from building and iterating on generative AI experiences, ultimately accelerating time to market for our customers.”
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Playground can leverage transformer models directly in Elasticsearch and is augmented by the Elasticsearch Open Inference API, which integrates models from a growing list of inference providers, including Cohere and Azure AI Studio.
Elastic, the Search AI Company, enables everyone to find the answers they need in real-time using all their data, at scale. Elastic’s solutions for search, observability and security are built on the Elastic Search AI Platform, the development platform used by thousands of companies, including more than 50% of the Fortune 500.
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