Elastic Introduces Playground to Accelerate RAG Development with Elasticsearch

Rhea-AI Summary

Elastic (NYSE: ESTC), the Search AI Company, has announced the launch of Playground, a low-code interface designed to accelerate the development of Retrieval-Augmented Generation (RAG) applications using Elasticsearch. This new tool enables developers to rapidly build and iterate RAG applications for A/B testing large language models (LLMs), tuning prompts, and chunking data.

Playground offers an intuitive UI that supports hybrid search capabilities by integrating the Elasticsearch vector database and leveraging transformer models. It works with chat completion models from OpenAI and Azure OpenAI Service, and supports integrations with providers like Cohere and Azure AI Studio via the Elasticsearch Open Inference API.

This innovation aims to simplify the process of building generative AI experiences, reduce complexity, and speed up the time to market for Elastic's customers.

Positive

• Launch of Playground to accelerate RAG application development.
• Enables A/B testing of LLMs and fine-tuning of retrieval mechanisms.
• Supports integrations with OpenAI, Azure OpenAI Service, Cohere, and Azure AI Studio.
• Aims to reduce complexity and speed up time to market for customers.

Negative

• None.

A new interface enables developers to iterate and build RAG applications for A/B testing LLMs, tuning prompts and chunking data

SAN FRANCISCO--(BUSINESS WIRE)-- Elastic (NYSE: ESTC), 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.

“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.”

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.

About Elastic

Elastic (NYSE: ESTC), 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 at elastic.co.

Elastic and associated marks are trademarks or registered trademarks of Elastic N.V. and its subsidiaries. All other company and product names may be trademarks of their respective owners.

View source version on businesswire.com: https://www.businesswire.com/news/home/20240628691317/en/

Media Contact

Elastic Global PR

PR-team@elastic.co

Source: Elastic N.V.

FAQ

What is Elastic's Playground interface?

Elastic's Playground is a low-code interface that helps developers build and iterate on Retrieval-Augmented Generation (RAG) applications using Elasticsearch.

How does the Playground interface benefit developers?

Playground allows developers to A/B test large language models, tune prompts, and chunk data, accelerating the development of RAG applications.

Which models and services does the Playground support?

Playground supports chat completion models from OpenAI and Azure OpenAI Service, and integrates with providers like Cohere and Azure AI Studio using the Elasticsearch Open Inference API.

What is the main advantage of using Elastic's Playground?

The main advantage is that it simplifies the process of building generative AI experiences, reducing complexity and speeding up time to market for customers.