Resolve AI Raises $125M at $1B Valuation, Turning AI SRE into a Funded New Category

Resolve AI, a two-year-old startup building autonomous AI Site Reliability Engineers, has raised $125 million in Series A funding at a $1 billion valuation, signaling that AI-driven operations has moved beyond experimentation and into mainstream enterprise infrastructure.

The round was led by Lightspeed Venture Partners, with participation from other major investors. The company has now raised more than $160 million in total funding, despite being founded only in early 2024.

What Resolve AI Actually Does

Resolve AI is designed to function as an autonomous on-call engineer.

Instead of alerting humans first when something breaks in production, Resolve AI receives alerts directly from incident tools such as PagerDuty and Opsgenie. From there, it immediately begins investigating by querying logs, metrics, traces, configurations, and recent deployments across a company’s infrastructure.

The system builds a real-time map of services and dependencies, forming a knowledge graph that reflects how systems interact. Using that context, Resolve AI evaluates possible causes, narrows down the root issue, and recommends specific fixes. In some environments, it can also execute those fixes automatically.

In many cases, the goal is to resolve incidents before a human engineer joins the war room.

Moving Beyond Dashboards to Action

Traditional observability tools focus on showing engineers what is happening. Resolve AI is built to take action.

The company positions its product not as a chatbot or analytics overlay, but as an active teammate responsible for incident response. For low-risk and well-understood failure patterns, customers can enable automatic remediation. For more complex situations, Resolve AI produces detailed recommendations, remediation steps, and supporting evidence for human approval.

After an incident, the system automatically generates post-mortems, updates tickets in tools like Jira or ServiceNow, and shares summaries in collaboration platforms such as Slack. Each incident also improves the system’s future performance through learning.

Founders and Early Traction

Resolve AI was founded by Spiros Xanthos and Mayank Agarwal, both former senior leaders at Splunk. They previously co-founded Omnition, a distributed tracing company acquired by Splunk in 2019, and have worked together for nearly two decades.

This background is significant. Site reliability engineering is one of the most complex areas of enterprise software, and large organizations are cautious about automation in production systems. Resolve AI’s early traction, including large enterprise customers and approximately $4 million in annual recurring revenue, helped justify the unusually large Series A.

Why SRE Is Ripe for AI

Modern systems rely on microservices, Kubernetes, and multi-cloud architectures. This complexity produces massive volumes of alerts, often overwhelming human teams.

Senior SRE talent is scarce and expensive. Engineers spend large portions of their time reacting to incidents rather than improving system reliability.

AI systems that can analyze telemetry at scale, reason about dependencies, and apply fixes promise measurable improvements, including:

• Faster incident resolution
• Fewer and shorter outages
• Reduced on-call burnout
• Less dependency on scarce senior SREs

Resolve AI is part of a growing group of startups pushing beyond traditional AIOps toward agentic and autonomous remediation.

Why a $1B Valuation Now

A unicorn valuation at single-digit ARR is aggressive by traditional metrics. Investors appear to be betting that AI-driven operations will become core infrastructure rather than a niche feature.

Resolve AI requires heavy upfront investment in compute, security, integrations with production systems, and enterprise sales. The company also reports a strong pipeline of large organizations evaluating or piloting the platform, suggesting the potential for rapid revenue expansion.

While some reports indicate structured deal mechanics, Resolve AI maintains that the round reflects full investor confidence in its long-term trajectory.

Risks and Open Questions

Significant challenges remain.

Enterprises must trust AI systems with live production environments. Even rare mistakes could undermine confidence. Large incumbents in observability and cloud infrastructure are also developing similar capabilities, supported by existing customer relationships and data access.

At a $1B valuation, Resolve AI is now expected to scale quickly. Any slowdown in adoption could increase pressure on pricing, positioning, and differentiation.

Why This Funding Round Matters

The importance of this round extends beyond Resolve AI itself.

A $125 million Series A at unicorn valuation effectively establishes AI SRE as a recognized enterprise software category. Investors are signaling belief that autonomous agents will handle a majority of operational incidents in the future.

This reflects a broader shift in enterprise software, moving from tools that surface information to systems that deliver outcomes.

Whether Resolve AI becomes the long-term leader or not, its funding marks a turning point. AI-driven site reliability is no longer optional or experimental. It is becoming a foundational layer of modern infrastructure operations.