Resolve AI, an emerging startup at the intersection of artificial intelligence and infrastructure management, is building what it calls an autonomous Site Reliability Engineer (SRE) — an advanced software system designed to automatically maintain, monitor, and repair digital environments without human intervention. According to three individuals with direct awareness of the transaction, the company has successfully secured a Series A investment round led by Lightspeed Venture Partners, underscoring both its technological promise and investor enthusiasm for automation-driven operational reliability.
Sources indicate that the headline valuation attached to this new funding round stands at an impressive $1 billion, effectively granting Resolve AI the coveted “unicorn” status. However, a closer look at the financing structure reveals a more nuanced picture: because the round was divided into multiple tranches, the company’s average, or blended, valuation was somewhat lower. In this arrangement, certain portions of equity were sold at the headline $1 billion figure, while the remaining shares—reportedly representing the larger fraction of the capital raised—were priced below that mark. This layered funding strategy has gained traction among venture capitalists and has recently become a favored mechanism for high-demand artificial intelligence startups. Investors regard it as a balanced approach that rewards early confidence but continues to anchor valuations in measurable performance.
Resolve AI currently reports an estimated annual recurring revenue (ARR) of about $4 million, according to two of the aforementioned sources. While precise details about the total amount raised in this Series A round remain undisclosed, the achieved valuation demonstrates a strong market appetite for automation tools capable of addressing the growing complexity of modern software infrastructure. Representatives from both Resolve AI and Lightspeed Venture Partners declined to provide additional comments on the deal.
The company is relatively young, having been established less than two years ago. It is helmed by a pair of long-time collaborators: Spiros Xanthos, previously an executive at Splunk, and Mayank Agarwal, Splunk’s former chief architect for observability technologies. Their professional relationship extends back some two decades to their time as graduate students at the University of Illinois Urbana-Champaign. Resolve AI marks the continuation of their long-standing partnership, following their earlier co-founding of Omnition, a startup in the observability space that was successfully acquired by Splunk in 2019. Their repeated collaboration illustrates a shared vision for advancing system reliability through data-driven intelligence and automation.
In traditional software operations, human SREs are tasked with identifying, diagnosing, and resolving system incidents that disrupt service stability. These responsibilities can be labor-intensive, error-prone, and difficult to scale as digital systems grow increasingly intricate. Resolve AI’s technology seeks to revolutionize this process by applying artificial intelligence to autonomously detect and address production issues in real time. Through continuous monitoring and adaptive learning, its platform can isolate root causes of failures, deploy correctives instantly, and restore normal operations—functions that would otherwise require the constant attentiveness of on-call engineers.
This form of automation offers a critical solution to one of the industry’s most pressing challenges: the scarcity of skilled reliability engineers in an era when software ecosystems are distributed across multiple clouds and dependent on countless interconnected services. As organizations expand their digital footprints, maintaining uptime and stability has become both an operational necessity and a formidable challenge. Automating routine troubleshooting not only reduces downtime and lowers maintenance costs but also liberates engineering teams from perpetual firefighting. This, in turn, allows them to invest their time and creativity in developing new features, improving user experience, and driving innovation forward.
Resolve AI’s rapid trajectory has already attracted prominent backers. Just one year prior, in its seed stage, the company raised $35 million in a round led by Greylock Partners, with participation from notable figures including Fei-Fei Li, founder of World Labs, and Jeff Dean, a leading scientist at Google DeepMind. These early supporters positioned the company as one of the most promising entrants in the expanding field of AIOps—artificial intelligence for IT operations.
The competitive landscape for automated SRE platforms is heating up. Resolve AI’s most direct rival is Traversal, another AI-driven reliability startup that recently announced a $48 million Series A funding led by Kleiner Perkins, with additional backing from Sequoia Capital. Both companies exemplify the accelerating race to build systems capable of self-sustaining software environments—a frontier that may redefine how enterprises manage technical complexity in the years ahead. As investors and engineers alike look to the future of autonomous operations, Resolve AI’s emergence as a newly minted unicorn signals that this transformation is not merely theoretical but already underway.
Sourse: https://techcrunch.com/2025/12/19/ex-splunk-execs-startup-resolve-ai-hits-1-billion-valuation-with-series-a/
