Playground for Developers: Elastic Introduces New Innovation to Accelerate RAG Development with Elasticsearch

Elastic, the Search AI Company, has announced Elastic 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.

“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.”

Elastic Playground to Leverage Transformer Models 

Elastic 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.

Playground currently supports chat completion models from OpenAI and Azure OpenAI Service. To get started, read the Elastic blog.

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.

Learn more about Elastic Playground at elastic.co.