We are thrilled to finally share what we’ve been building at Traversal and to announce our launch out of stealth, along with our $48M seed and Series A funding rounds, led by Sequoia and Kleiner Perkins, with participation from NFDG and Hanabi.

Collectively, our team has spent decades at the intersection of academia and industry united by a shared obsession for one of the most stubborn problems in technology: when production software systems go down, why is it still so hard—even with all our dashboards, data, and observability tools—to find the real cause, fast? 

Our founding team brings deep expertise in causal machine learning, with three of us having spent years advancing the science of causality as AI researchers. We're a motley crew in a lot of ways—Columbia and Cornell professors, an MIT-trained researcher, and a Citadel Securities trader, united by a common experience: we've seen how hard this problem is to solve, but also why it’s the perfect problem for us to solve together. The blend of our team’s academic research and hands-on experience in high-stakes production environments gave us a unique perspective—and conviction—that we could finally crack root cause analysis (RCA) at enterprise scale.

Reliability in the Age of AI-Generated Code

Downtime is already a massive problem, costing enterprises $400 billion annually and up to $1 million per hour during major incidents. With AI soon expected to write the majority of our code, system reliability is poised to become an even more acute challenge: software will break more often, and people simply won’t be able to keep up as systems grow too complex and interdependent for any one team to fully understand. This complexity, amplified by AI-generated code that is harder to maintain and debug, actually risks eroding trust in AI as teams spend more time firefighting outages and less time building. If downtime and technical debt continue to rise, organizations may hesitate to embrace AI-driven software development, fearing that the productivity gains are outweighed by the operational headaches. The potential impact is staggering—lost customer trust, burned-out engineering teams, and endless “dashboard dumpster diving.”

Today’s observability tools represent the second-largest software expense after cloud computing, yet they often overwhelm teams with noise rather than providing actionable insights. As a result, engineers can spend up to 30% of their on-call time firefighting and root-causing incidents, instead of building and innovating. Traversal changes this by automating troubleshooting and incident response, reducing the on-call burden and empowering engineers to focus on creative, high-impact work that enhances long-term system health—rather than operating in a constant state of crisis.

The AI SRE for the Enterprise

Traversal was purpose-built for this moment. We’ve built the AI SRE agent for the enterprise - it autonomously troubleshoots, remediates, and even prevents the most complex production incidents companies face. Our architecture pushes the frontier of AI agents and combines it with our research in causal machine learning, enabling Traversal to “traverse” massive datasets, orchestrate tool calls, and pinpoint true root causes—not just symptoms—in real-time.

This isn’t just theory. Traversal is already deployed in mission-critical environments, including at Digital Ocean, Eventbrite, Cloudways, and some of the largest financial institutions in the Fortune 100. Engineers at these companies rely on Traversal as their first line of defense, and we’re seeing >90% accuracy on hundreds of high-impact incidents. We meet customers where they are, allowing for read-only access to their data and flexible on-premise deployments. Even outside of incidents, Traversal acts as an AI-powered “health check,” proactively preventing problems before they escalate and de-noising countless alerts. 

But don’t take our word for it—Bratin Saha, Chief Product and Technology Officer at DigitalOcean shares here why he chose to trust Traversal with his team and customers after evaluating more than half a dozen alternatives.

What’s Next

At Traversal, our roots remain deeply embedded in AI research, and we’re channeling that scientific rigor and creativity into building the premier AI agent lab for the enterprise. We’re convinced that the most exciting advances in AI are now happening in startups with research in their DNA, taking on the toughest technical problems. That’s where we believe the next wave of breakthroughs will emerge: at the intersection of cutting-edge research and real-world impact for enterprises.

This vision has resonated with a remarkable group of early believers and partners, including Bogomil Balkansky & Charlie Curnin of Sequoia, Mamoon Hamid & Aditya Naganath of Kleiner Perkins, Nat Friedman & Patrick Hsu of NFDG, Bryan Offutt, Ishani Thakur & Mike Volpi of Hanabi along with an incredible set of angels that are leaders in infrastructure and AI. Their support has been instrumental as we scale Traversal and push the boundaries of what’s possible in AI-driven reliability.

What we’re proudest of is assembling the most talented yet nicest group of individuals at Traversal to take on one of the hardest problems for AI to solve. Without the entire team, none of this would be possible. If you share our passion for redefining software reliability and want to help shape the future of AI in the enterprise, we’d love to hear from you. 

And if you want to learn more about how Traversal can help you and your teams, check out our demo here.

—Anish Agarwal, Raj Agrawal, Raaz Dwivedi, Ahmed Lone

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