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Introducing Resolve AI

Insider Brief

  • Resolve AI launched with a $35 million seed round led by Greylock to equip engineers with AI tools that automate software operations, reducing Mean Time to Resolve (MTTR) and improving productivity.
  • Its first product, an AI Production Engineer, autonomously troubleshoots production issues, handles operational tasks, and aims to resolve 80% of alerts without human intervention, enhancing system reliability and reducing burnout.
  • By automating on-call incident management and infrastructure tasks, Resolve AI aims to allow engineers to focus on higher-level innovation, transforming the way software systems are built and maintained.

PRESS RELEASE — Resolve AI, launched this week, aims to equip engineers with AI tools that automate software operations. Its first product functions as an AI Production Engineer, autonomously troubleshooting production issues and handling operational tasks, significantly reducing Mean Time to Resolve (MTTR) and enabling engineers to focus on innovation. By integrating a deep understanding of production environments with advanced AI, Resolve AI seeks to enhance the way engineers build, deploy, and maintain real-world software systems.

The company has announced a $35 million seed round led by Greylock, with support from Unusual Ventures and a group of prominent angel investors.

The startup is addressing a common challenge engineers face: spending most of their time on operational tasks such as on-call troubleshooting, infrastructure management, and security. These tasks demand knowledge from multiple tools that weren’t designed to work together, increasing complexity and time consumption. CEO and co-founder shared that during his tenure at Splunk’s Observability business, 90% of the SRE team left due to burnout, mainly from on-call duties, emphasizing the critical need to alleviate such burdens.

To improve MTTR and productivity, Resolve AI automates on-call incident troubleshooting and remediation, significantly reducing stress for engineers and improving system reliability. Currently deployed in several production environments, the AI is already delivering results by enhancing uptime and team productivity.

Resolve AI’s system operates like a human engineer, utilizing tools such as AWS, Kubernetes, GitHub, and Slack. It quickly resolves alerts and incidents, answers questions about system health, and connects data from observability tools, infrastructure, code, and release pipelines. The system aims to automatically resolve 80% of alerts and incidents without human intervention, with future plans to extend its capabilities to incident prevention and cloud cost optimization.

Over time, Resolve AI envisions engineers managing production systems at a higher level of abstraction, allowing AI to handle the operational complexity. This shift is expected to drive greater velocity and efficiency in software development and operations.

Resolve AI’s leadership team, including the co-founders who have worked together for over a decade, is committed to empowering engineers through AI. With a strong network of customers such as DataStax, Uni, and Blueground, and support from investors, the company is poised to transform how software systems are operated and maintained.

SOURCE

Featured image: Credit: Resolve AI

James Dargan
About the author
James Dargan

James Dargan is a writer and researcher at The AI Insider. His focus is on the AI startup ecosystem and he writes articles on the space that have a tone accessible to the average reader.

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