Elastic launches low-code RAG development interface
Search AI company Elastic has launched a new low-code interface designed to help developers quickly build retrieval augmented generation (RAG) applications.
Elastic said the interface, Playground, can help developers integrate and build RAG applications within minutes. Developers can A/B test different large language models and refine retrieval mechanisms to ground answers with proprietary data indexed into Elasticsearch.
The platform is augmented by the Elasticsearch Open Inference API, which integrates models from a range of inference providers including Cohere and Azure AI Studio. Playground currently supports chat completion models from OpenAI and the Azure OpenAI Service.
Elastic Global VP and GM for Search Matt Riley said the ability to rapidly iterate on key components of a RAG workflow is essential to ensure accurate and hallucination-free responses from large language models.
“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,” he said. “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.”
ACS backs digital productivity vision but urges action on AI regulation
Rather than promoting a wholesale rethink of AI regulation, ACS is calling for parallel progress,...
ACS releases annual Digital Pulse report
Ten-point plan calls for national action to unlock billions in economic growth and productivity.
Tenable uses AI to further refine threat risk rating
Tenable has announced enhancements to its Tenable Vulnerability Priority Rating aimed at helping...
