Empirik: Predicting Infrastructure Failures Before They Happen

Building a Future Without Outages

As artificial intelligence becomes increasingly central to how we build and manage technology systems, new startups are emerging to help engineers keep pace with ever-growing complexity. One such company, Empirik, is working on something particularly ambitious: a tool that can predict infrastructure failures before they happen. The idea may sound futuristic, but it's already beginning to reshape how IT teams approach system stability.

I first learned about Empirik through its origins story — a tale of two seasoned tech leaders who recognized a critical gap in how large-scale systems are currently managed. Avon Puri, who previously led digital and information operations at VMware and Rubrik, joined Sequoia Capital in 2020 as chief digital and information officer. There, he met Sudheer Dhurjati, another Sequoia IT veteran. Together, they realized that while AI was transforming software development, there had been little progress in applying similar thinking to infrastructure.

"There has always been a lot of money spent in keeping systems up and running," said Sequoia partner Bogomil Balkansky, referencing Empirik's unique approach to infrastructure management. "Most existing observability tools fail to understand complex system dependencies."

That realization sparked Empirik's creation — an autonomous platform that tracks changes across entire systems and predicts their ripple effects. It's not just about monitoring what's happening now, but rather anticipating what might go wrong next.

The Challenge of Modern Infrastructure

In today's digital landscape, infrastructure is more complex than ever. With microservices, cloud-native architectures, and distributed systems running in real-time environments, even a small configuration change can cascade into massive failures. Traditional observability tools offer reactive insights — they help you understand what went wrong after the fact.

But as more organizations embrace AI to automate workflows and speed up innovation cycles, the pressure on infrastructure teams has intensified. DevOps and Site Reliability Engineers (SREs) are often overwhelmed with routine troubleshooting tasks, leaving little time for strategic initiatives. Empirik aims to free up those engineers by automating much of this work.

The platform acts like an intelligent assistant or traffic cop for infrastructure. It allows low-risk changes to proceed automatically while flagging high-risk updates that require human review. In doing so, Empirik offers a new category of tool that complements, rather than replaces, current AI-powered SRE platforms.

From Idea to Investment

Empirik was incubated within Sequoia Capital's portfolio in 2023. The investment firm saw potential not just in the product, but in its underlying vision. To lead Empirik as CEO, Sequoia recruited Kartik Chandrayana, a veteran of companies like Quantum Metric and Salesforce, who brings deep experience in enterprise observability.

Earlier this year, Empirik officially spun out from Sequoia and announced $21 million in seed funding from investors including Sequoia itself, Canapi, and Alumni Ventures. This move signals both confidence in the product and a commitment to independence — something crucial for a startup aiming to scale quickly.

"What agentic AI did for software, Empirik wants to do for infrastructure engineering," Chandrayana told TechCrunch. "We're trying to bring that same level of autonomy and intelligence to how infrastructure is managed."

Real-World Impact

Since its launch earlier this year, Empirik has already gained traction with customers ranging from startups to Fortune 500 companies. Notable names include Guardant Health and a major consumer packaged goods (CPG) company — both of which have leveraged the platform to reduce downtime and improve operational efficiency.

What sets Empirik apart is how it aligns with modern development practices. It's designed not just for engineers, but for teams that need to collaborate seamlessly across departments. Whether you're a CTO worried about system reliability or an SRE looking to reduce incident response time, Empirik provides the predictive insight needed to stay ahead of potential problems.

Looking Ahead

The infrastructure landscape is rapidly evolving, and tools like Empirik are at the forefront of this transformation. As companies continue to adopt AI across their stacks, the need for intelligent infrastructure monitoring grows exponentially. If Empirik can deliver on its promise, it could become one of the essential tools in every enterprise's tech stack.

And yet, challenges remain. Integrating AI into systems that have historically operated without such predictive capabilities requires careful planning and deep expertise. The platform must also navigate competition from other observability solutions — some already leveraging AI to varying degrees.

Still, the potential is clear. Empirik's approach — combining real-time data with machine learning models trained on historical infrastructure behavior — represents a major shift in how we think about infrastructure management. It's no longer just about reacting to failures; it's about preventing them.

This isn't just another tech startup trying to get rich off the hype cycle. This is a genuine attempt to solve one of the most persistent and costly problems in engineering: how to maintain uptime in an increasingly complex world. And with Sequoia's backing and strong early adoption, Empirik may be well-positioned to lead that charge.

Final Thoughts

In many ways, Empirik mirrors the broader transformation happening across the tech industry — where artificial intelligence is becoming not just a tool, but a fundamental part of how we build, manage, and monitor systems. It's about moving from a world of guesswork to one where decisions are informed by data and predictive modeling.

For those in IT roles, Empirik offers a compelling vision: the ability to work smarter, not harder, by offloading routine tasks and focusing on innovation instead. For investors and entrepreneurs alike, it shows how AI can be used to tackle long-standing inefficiencies in enterprise infrastructure — and do so at scale.

As we move forward, tools like Empirik will likely become increasingly common — but they also raise questions about who controls the future of our systems. Will infrastructure decisions be guided by human intuition or algorithmic insight? Empirik doesn't answer that question directly, but it certainly sets up an important discussion.