Resolve AI raises $125M Series A to scale AI for prod

We launched Resolve AI a bit more than a year ago to build agents that help engineers debug and run production. Since then, it’s been deployed in production at some of the largest technology, financial services, and consumer application companies, improving reliability while materially reducing operational toil for engineers and SREs.

Today, we’re announcing our $125M Series A funding led by Lightspeed Venture Partners, with pro-rata or above participation from Greylock, Unusual Ventures, Artisanal, and A*. The non-blended Series A round values Resolve AI at $1B bringing our total funding to more than $150M.

Running production at scale is hard for humans and agents

The hardest part of software engineering isn't writing code. It's running production. Problems rarely live in a single system, and the root cause is usually in the relationships between tools: a latency spike that is tied to a recent deployment, or a configuration change that is affecting a specific database shard.

The result is that reliability is hard to achieve and comes at a huge cost, not just in terms of tools but also in human effort. Incidents regularly pull in groups of engineers to reconstruct context across disconnected systems, and the most experienced spend more time firefighting than building. On top of all of that, we overprovision infrastructure to compensate. All of these challenges are now amplified by our ability to generate code much faster using AI.

Production is also a uniquely difficult environment for agents. The tools were designed for humans, the data is fragmented across systems, and any decision requires reasoning across code, telemetry, infrastructure, and changes simultaneously. Much of the most important context is undocumented. It lives in human minds as tribal knowledge.

AI for prod

We started Resolve AI as an AI SRE that can resolve alerts and incidents. Along the way, we learned something fundamental to our mission: even for simple alerts, production agents need to build a deep, environment-specific understanding of how systems actually run. That means going beyond general-purpose models and learning the context that lives across disparate tools and systems.

AI for prod is an agentic interface to production itself. It continuously pulls context across code, observability, deployments, cloud infrastructure, configuration, and operational history. It reasons over evidence and produces clear, actionable recommendations, working alongside engineers and SREs while keeping humans in control.

With this foundation, the same agents can handle most production work: incident diagnosis, rollback decisions, capacity adjustments, configuration changes, infrastructure actions, and guided code changes.

We’re seeing AI for prod deliver measurable results across business-critical applications that millions of people rely on daily. Teams at Coinbase, DoorDash, MongoDB, MSCI, Salesforce, Zscaler, and others use Resolve AI to run more resilient systems, reduce operational risk, and reclaim engineering time for building. Coinbase has improved MTTR, with a measured 72% reduction in time to investigate critical incidents. Zscaler has reduced the number of engineers required per incident by 30%. More broadly, Resolve AI is helping teams respond to production challenges faster, bring fewer people into war rooms, and keep production from becoming the bottleneck as change accelerates.

To solve this problem, we’ve built a unique team that combines frontier AI researchers that pioneered agentic AI with deep expertise in production systems, including engineers who have run some of the world's most demanding production environments.

What comes next

This funding will be focused on three priorities:

1. R&D: advancing Resolve AI as a world-class Applied AI lab for Software Engineering. We are invested in staying at the forefront of agent development and model training.
2. Product depth: improving production reasoning, moving toward closed-loop systems, and expanding integrations across the production stack with enterprise-grade controls.
3. Customer success: supporting growing global enterprise deployments.

Today, Resolve AI works alongside engineers and SREs in Slack, Microsoft Teams, and the terminal. What comes next is a future where AI doesn’t just react to alerts and incidents, it helps prevent and contain production issues before customers notice.

The agent era will create far more software than any era before it. The teams that win won’t be the ones that write code the fastest. They’ll be the ones who can run what they write, reliably and securely, at the same pace.

That’s what AI for prod enables, and this Series A allows us to keep building it.

Thanks to everyone who is with us on this journey

To our investors: thank you for believing in our team before it was obvious. Sebastian Duesterhoeft and Raviraj Jain at Lightspeed, Saam Motamedi and Corinne Riley at Greylock, John Vrionis at Unusual Ventures, and Andy Price at Artisanal have been true partners.

To our customers: thank you for betting on a young startup. We are proud to have your trust and honored to be building alongside you.

To the 125+ team members at Resolve AI: thank you for betting on this mission. You all left great opportunities to bet on something bigger at Resolve AI, and you're the reason any of this is possible. Your hard work, dedication, and commitment are what make Resolve AI special.