Welcome to our dedicated page for Elastic news (Ticker: ESTC), a resource for investors and traders seeking the latest updates and insights on Elastic stock.
Elastic N.V. reports developments in search AI software, observability, and security built on its Search AI Platform. Company news commonly covers Jina embedding models for text and multimodal retrieval, Elastic Inference Service availability, partner model deployments, and product integrations that bring search, classification, clustering, and data exploration into enterprise workflows.
Recurring updates also include Elastic Observability features such as Prometheus ingestion, PromQL support in Kibana, and incident investigation tools, as well as Elastic Security capabilities for XDR, SIEM, automation, and agentic security operations. Other company developments include cloud partnerships, air-gapped and sovereign-cloud deployments, federal cloud authorization, and pricing or packaging changes for security offerings.
Elastic (NYSE: ESTC) has partnered with LangChain to develop AI-driven security innovations for SOC teams. This collaboration has led to the creation of features like Automatic Import, Attack Discovery, and Elastic Assistant for Security on the Elastic Search AI Platform. These features aim to streamline user migration to AI-driven security analytics and expedite security operations workflows.
The integration leverages LangChain and LangGraph to enhance the Elastic AI Assistant's ability to understand complex security scenarios, identify attacks, and create accurate data integrations. Users can integrate these features with their preferred LLM through the Elastic Open Inference API and LangChain's chat model ecosystem.
Elastic (NYSE: ESTC), the Search AI Company, has announced it will release its financial results for the first quarter of fiscal 2025, ended July 31, 2024, after the U.S. market close on Thursday, August 29, 2024. The company will host a conference call at 2:00 p.m. PT/ 5:00 p.m. ET on the same day to review its financial results and business outlook. Investors can access a live webcast of the conference call from the Elastic investor relations website at ir.elastic.co. A replay of the webcast will be available for two months following the call.
Elastic (NYSE: ESTC) has introduced Elastic Distributions of OpenTelemetry (EDOT), a portfolio of OpenTelemetry (OTel) components designed to enhance infrastructure and application monitoring. EDOT offers deeper insights, troubleshooting capabilities, and enterprise-grade support from Elastic. The portfolio includes the Elastic Distribution of OpenTelemetry Collector and Elastic Distributions of Language Software Development Kits (SDKs) supporting Java, Python, NodeJS, .NET, iOS, and Android.
EDOT brings additional application performance monitoring (APM) capabilities from Elastic's APM agents into OTel language SDKs while maintaining seamless integration with Elastic Observability. Elastic plans to release OTel versions of its APM agents and continue adding language SDKs mirroring OTel. EDOT is currently available in tech preview, with details and documentation accessible in Elastic's public OpenTelemetry GitHub repository.
Elastic (NYSE: ESTC) has been recognized as a Leader in the 2024 Gartner Magic Quadrant for Observability Platforms for its Elastic Observability offering. This recognition is based on Elastic's Completeness of Vision and Ability to Execute.
Key features of Elastic Observability include:
- Proactive issue detection using AI and machine learning
- Cost-effective observability with up to 50% savings
- Open and extensible solution for future-proofing investments
- AI-augmented insights for SREs
- Fast analytics across petabytes of indexed data
- Unified data store for improved uptime and long-term analysis
Equinox, a customer, reported creating a 'single pane of glass' for data consumption and reducing fix deployment time by 50% using Elastic's solution.
Elastic (NYSE: ESTC) has launched Elastic Express Migration, a program designed to simplify the transition from legacy SIEM vendors to Elastic's AI-driven security analytics platform. The program offers migration credits to offset dual-vendor costs during transition and service credits for Elastic's migration professional services.
Key features of the migration process include:
- AI-based Automatic Import to automate custom data integrations
- 400+ prebuilt integrations for data onboarding
- Elastic AI Assistant to auto-convert existing detection rules
- ES|QL, a powerful new query language
The program aims to address challenges in SIEM migration, such as onboarding data sources and transferring detection rules, while providing a cost-effective solution for organizations seeking to modernize their security operations centers.
Elastic (NYSE: ESTC) has introduced Automatic Import, a groundbreaking feature for its Security Information and Event Management (SIEM) solution. This AI-powered tool automates custom data integrations, significantly reducing the time required to onboard new data sources from days to less than ten minutes. The innovation addresses a major pain point in SIEM migration, potentially saving large-scale customers hundreds of hours and months of implementation time.
Powered by the Elastic Search AI Platform, Automatic Import leverages large language models (LLMs) and retrieval augmented generation (RAG) to expedite labor-intensive SecOps tasks. It builds upon Elastic's previous AI-driven security analytics innovations, including Elastic AI Assistant and Attack Discovery. The feature is available to all customers with an Enterprise license and currently supports JSON and NDJSON-based log formats.
Elastic (NYSE: ESTC) has announced that its Elasticsearch vector database now supports Mistral AI embeddings. This integration allows for native chunking via a single API call, streamlining the development process for RAG applications. The collaboration between Elastic and Mistral AI aims to simplify the storage and chunking of embeddings in Elasticsearch, making it easier for developers to build advanced search applications.
Key features of this integration include:
- Support for mistral-embed
- Native integrations with the Open Inference API
- Compatibility with the semantic_text field
This update aligns with Elastic's commitment to providing open-first, enterprise-grade GenAI tools and Mistral AI's focus on open-weights and accessibility in AI development.
Elastic (NYSE: ESTC) has announced that its Elasticsearch Open Inference API and Playground now support models hosted on Amazon Bedrock. This integration offers developers the flexibility to choose from various large language models (LLMs) available on Amazon Bedrock, facilitating the development of production-ready retrieval-augmented generation (RAG) applications.
Shay Banon, Elastic's founder and CTO, emphasized that the integration aims to simplify the creation of next-generation search experiences for AWS developers. By leveraging Elasticsearch with Amazon Bedrock's extensive model library, developers can create enhanced conversational search functionalities. The support extends to a low-code playground, enabling easy A/B testing of different LLMs. The new support is available immediately, with detailed guides available on their Inference API and Playground blogs.
Elastic (NYSE: ESTC), known as the Search AI Company, is set to host a live webcast on July 17 at 10:00 AM PT. The event will feature Santosh Krishnan, General Manager of Elastic Security, who will discuss the company's security solutions. An Elastic partner will join the discussion, and Koji Ikeda, Senior Research Analyst at Bank of America Securities, will co-host the webcast. Both the live webcast and a replay will be accessible on Elastic’s Investor Relations page at ir.elastic.co.
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.