Causely, the AI-powered Site Reliability Engineering (SRE) platform built around a structured causal graph for deterministic automation, has integrated Google’s Gemini models to enhance its Causal Reasoning Engine. The updated solution is now available on Google Cloud Marketplace, enabling customers to deploy, manage, and scale the platform on Google Cloud’s secure, global infrastructure. By combining Causely’s causal inference engine with Gemini’s advanced language capabilities, the platform can now automatically generate clear, context-aware explanations and actionable remediation guidance. This integration helps engineering teams detect, diagnose, and resolve reliability issues faster and more confidently—often before they impact users. Causely’s causal reasoning engine models the behavior of complex distributed systems, pinpointing root causes of performance degradation such as increased latency or error rates, assessing their potential impact, and recommending specific actions to restore service health. With Gemini, the system translates these technical insights into natural language summaries and step-by-step recovery plans, reducing the need for manual triage and emergency incident response. “Bringing Causely to Google Cloud Marketplace will help customers quickly deploy, manage, and grow the Causal Reasoning Engine on Google Cloud's trusted, global infrastructure,” said Dai Vu, Managing Director, Marketplace & ISV GTM Programs at Google Cloud. Yotam Yemini, CEO of Causely, emphasized the transformational impact: “Our causal engine identifies why services are failing. Google’s Gemini models help us explain what to do next—turning complex diagnostics into clear, automated actions. We’re eliminating the need for incident war rooms and enabling true proactive reliability.” Two new features now powered by Gemini include: - Natural language query generation that allows users to ask questions in plain English and receive accurate, system-specific answers. - Automated incident summarization and remediation suggestions that provide concise, context-rich guidance tailored to the specific failure scenario. Early adopters have reported up to a 75% reduction in mean time to recovery and a 25% decrease in incident volume, leading to improved system uptime and team productivity. While optimized for Google Cloud, Causely remains multi-cloud and model-agnostic, supporting deployment across public clouds, hybrid environments, and on-premises infrastructure. It also integrates with various large language models, giving organizations flexibility in their AI stack. Causely is an AI startup focused on redefining Site Reliability Engineering through intelligent automation, causal reasoning, and developer-first tools. Its mission is to help organizations manage the growing complexity of modern distributed systems with greater speed, accuracy, and confidence.