Mid Market Account Executive

Elastic announced it is integrating OpenAI GPT cyber models directly into Elastic Security workflows. The integration aims to enable AI-driven threat detection, investigation, and response within Elastic Security, moving towards more automated security operations for customers. The GPT cyber models operate through Elastic's Inference Service, allowing customers to use GPU-intensive AI without running their own model infrastructure. This positions Elastic as a unified platform where increased AI-driven workloads drive deeper usage of its cloud services. The move aligns with Elastic's strategy to leverage generative AI demand and data-intensive workloads as key growth catalysts. Management is differentiating itself through AI and ML-powered security features rather than basic search alone. Investors should monitor how Elastic ties this integration to Security and Elastic Cloud performance in upcoming fiscal 2027 quarters. The company has guided revenue of $486-487 million for Q2.

Tencent Cloud and Elastic strengthen strategic collaboration to build context infrastructure for the AI era. SHENZHEN, China, Aug. 31, 2026 /PRNewswire/ - Tencent Cloud, the cloud business of global technology company Tencent, and Elastic announced an expanded strategic collaboration in Shenzhen. The companies will deepen their technical and product collaboration across AI search, enterprise data, and agentic applications, helping enterprises establish dedicated context infrastructure for the AI era. The two companies also jointly launched Tencent Cloud Elasticsearch Service (ES) Enterprise Edition, which introduces Elastic's enterprise-grade search and AI capabilities to the platform. Elasticsearch is one of the world's most widely used open-source search engines. Elastic's Search AI Platform, the foundation for its search, observability, and security solutions, is used by thousands of companies, including more than 50% of the Fortune 500. It supports tasks such as product search in e-commerce, in-app search, and the troubleshooting and analysis of system logs. Tencent Cloud has been offering cloud services based on Elasticsearch since 2016. AI is fundamentally changing the role of enterprise search, serving as the essential bridge that retrieves real-time context from internal data to ground large language models (LLMs). These models do not inherently understand an enterprise's internal information. To answer business questions, they need to retrieve relevant content from enterprise data in real time. Agents also need to continuously locate information and tools as they carry out tasks. Search is becoming a way to provide AI systems with grounded enterprise data. Patrick Dixon, Senior Director of Channels & Alliances for APJ and Vice President for China at Elastic, said that as large language model capabilities advance, context is becoming increasingly important to enterprise AI applications. For agents, the ability to locate accurate and reliable enterprise data when it is needed directly affects the quality of subsequent responses, decisions, and execution. Tencent Cloud Elasticsearch Service (ES) Enterprise Edition strengthens AI search, model integration, and agent connectivity. Enterprises can combine keyword and semantic search, enable large language models and agents to call search results directly, and keep large volumes of historical data searchable to provide AI with more complete business context. Alongside Elastic's native capabilities, Tencent Cloud has continued to enhance ES with in-house engineering. In selected AI search scenarios, performance has improved by up to 5x, hybrid search latency has fallen by 60%, and memory consumption has been reduced by more than 50%. Enterprises can add AI search capabilities without changing their existing data architecture and can use the service together with Tencent Hunyuan large language models and the Tencent Cloud TCRay inference platform. Customers running open-source editions or self-managed clusters can also access technical migration and upgrade services. Enterprises are already leveraging these advanced search capabilities to optimize their AI and security workflows. Tencent ima uses ES as the underlying retrieval layer for its knowledge base, supporting both keyword and semantic search. After Tencent Cloud optimized the system for many users searching the knowledge base concurrently, memory consumption fell by 71% and retrieval performance improved by 58%. At NIO, Tencent Cloud Elasticsearch Service (ES) serves as part of a security data intelligence foundation. It identifies the information most relevant to a current event from large volumes of security data, which AI then analyzes further. The system processes hundreds of billions of records in a single quarter. In one real-world attack, an attack chain that previously took analysts most of a day to investigate manually can now be retrieved and reconstructed in just two minutes. Cheng Bin, General Manager of Data Platform Products at Tencent Cloud Data Analytics, said, "AI search is evolving from a standalone retrieval capability into infrastructure that connects enterprise data, models, and agentic applications. Tencent Cloud will combine Elastic's enterprise-grade capabilities with its own experience in operating large-scale systems and its AI ecosystem, helping more enterprises establish context infrastructure for the AI era." Han Xiao, Vice President of AI at Elastic, said that as large language models turn toward longer-horizon tasks in 2026, search has more room to contribute. "Search in 2026 is, in essence, about test-time compute." He added, "When search quality falls short, teams should first consider whether additional inference compute can address the problem before adding data or switching to a larger model." Tencent Cloud was among the early cloud providers in China to form a Platinum-level partnership with Elastic. Over the past seven years, Tencent Cloud has consistently ranked among the leading contributors to the Elastic open-source community. Tencent Cloud Elasticsearch Service (ES) now runs 20,000 clusters and 100,000 nodes, reliably supporting search traffic peaks for large-scale live events, including the China Media Group (CMG) Spring Festival Gala and the Paris Olympic Games. About Tencent Cloud Tencent Cloud is one of the world's fastest-growing cloud service providers, committed to delivering innovative solutions that address everyday life and business challenges, and empowering the digital transformation of smart industries. Tencent Cloud has always upheld its mission to meet the needs of diverse industries, leveraging cloud computing, big data analytics, AI, IoT and cybersecurity, together with its extensive global infrastructure, to provide businesses with stable, secure, and industry-leading cloud products and services across a wide range of sectors, including education, finance, healthcare, gaming, media and entertainment, property, retail, travel, and transportation. SOURCE Tencent Cloud

Elastic Q1 earnings call highlights. Elastic (NYSE:ESTC) reported first-quarter fiscal 2027 revenue of $478 million, up 15% from a year earlier, as the company cited continued sales execution and demand across its search and AI, security and observability offerings. Sales-led subscription revenue rose 18% to $399 million, while non-GAAP operating margin reached 16.2%. Chief Executive Officer Ash Kulkarni said the company exceeded all of its guided metrics and began the fiscal year with accelerating constant-currency growth in both total revenue and sales-led subscription revenue. Discover more Weapon development trends Stocks & Bonds Nano Nuclear Energy "Customer demand was strong across all solution areas, especially in search and AI and security," Kulkarni said. Large-Customer growth and contracted commitments. Elastic ended the quarter with more than 1,800 customers with annual contract value of at least $100,000. The company added more than 80 net new customers to that cohort during the quarter, its largest increase to date. Customers in the group accounted for 90% of sales-led subscription revenue, compared with 87% a year earlier. Chief Financial Officer Navam Welihinda said the growth reflected improvements in sales capacity, productivity and pipeline generation, as well as ongoing consumption of commitments secured in fiscal 2026. Current remaining performance obligations, or CRPO, totaled $1.2 billion, growing 21% as reported and 20% on a constant-currency basis. Total RPO was $1.9 billion, up 27%. Kulkarni said the results indicated that customers were increasingly making multiyear commitments to Elastic's platform as they pursue AI-related transformations. Elastic's net expansion rate was 111%, compared with 112% in the prior quarter. Welihinda said the metric is calculated on a trailing four-quarter basis and should improve within four quarters as the company's constant-currency revenue growth accelerates through fiscal 2027. AI, security and observability initiatives. Kulkarni said Elastic is positioning Elasticsearch as a data store and retrieval layer for AI applications that require text, vector and hybrid search across structured and unstructured data. During the quarter, the company released VectorDB index mode and auto-calibration capabilities intended to provide vector-search performance without manual tuning. The company also extended Jina's multimodal and multilingual semantic-search capabilities, including embedding and re-ranker models, to on-premises and air-gapped deployments. Elastic said its Agent Builder product added agent observability, monitoring and human-in-the-loop approval workflows. More than 37% of Elastic's customers with ACV above $100,000 were using its AI features at the end of the quarter, up from about 21% a year earlier. The company said that represented more than 670 customers, including 70 net additions during the first quarter. Welihinda said customers using AI capabilities have a higher growth propensity than customers that do not use those features. In observability, Elastic relaunched its metrics offering and introduced Columnar Mode in Elasticsearch 9.5 as a technical preview. Kulkarni said the index mode is designed for time-series data and can reduce storage costs by 20% to about three bytes per metric sample. The company also added native Prometheus ingestion and PromQL support. Elastic acquired Deductive AI, which it described as a provider of AI site reliability engineering technology. Kulkarni said Deductive's reinforcement-learning harness can automate complex investigations by using information from code repositories, Elastic alerts, Slack, PagerDuty and ServiceNow to build decision trees based on previous and ongoing investigations. On the security side, Elastic said its Attack Discovery offering now autonomously investigates and validates threats. Kulkarni said the company is targeting an "AI-driven SOC," or security operations center, in response to a faster-moving cyberthreat environment. Elastic was named a leader in IDC's MarketScape for worldwide SIEM and a strong performer in Forrester's Wave for extended detection and response, according to the company. Profitability, capital returns and outlook. On a non-GAAP basis, Elastic reported subscription gross margin of 81%, total gross margin of 77% and adjusted free-cash-flow margin of 30%. The free-cash-flow result included $13 million in cash paid for restructuring and other charges related to organizational changes announced in June. The company repurchased approximately 800,000 shares for about $40 million during the quarter. Since launching its $500 million repurchase program in October 2025, Elastic has spent $380 million to repurchase 5.2 million shares as of the end of the first quarter. Elastic raised its fiscal 2027 outlook following the quarter. For the second quarter, it expects: * Total revenue of $486 million to $487 million, representing about 15% growth at the midpoint. * Sales-led subscription revenue of $407.5 million to $408.5 million, representing about 16.9% growth at the midpoint. * Non-GAAP operating margin of approximately 19%. * Non-GAAP diluted earnings per share of $0.80 to $0.82. For fiscal 2027, Elastic forecast total revenue of $1.998 billion to $2.010 billion and sales-led subscription revenue of $1.682 billion to $1.694 billion. The company expects non-GAAP operating margin of about 19.4%, adjusted free-cash-flow margin of 21.5% and non-GAAP diluted earnings per share of $3.29 to $3.37. Welihinda said Elastic expects growth in total revenue and sales-led subscription revenue to accelerate during the second half of the fiscal year, with the fourth quarter producing the highest year-over-year growth rate. The company also expects positive GAAP operating margin in the second quarter and for the full fiscal year. Kulkarni also announced that Caryn Marooney will leave Elastic's board after a long tenure and that Julia Liuson, formerly president of Developer Tools at Microsoft, has been nominated to join the board. About Elastic (NYSE:ESTC). Elastic N.V. operates as a search and analytics company, offering a suite of open source and subscription-based solutions for search, observability and security use cases. Its flagship product, Elasticsearch, enables fast and scalable full-text search and analytics across large volumes of structured and unstructured data. Complementary tools such as Kibana provide visualization capabilities, while Beats and Logstash serve as lightweight data shippers and data processing pipelines, respectively. The company was founded in 2012 by Shay Banon, who serves as chief technology officer, and Steven Schuurman.