The landscape of enterprise IT infrastructure has long operated under a reactive paradigm. For decades, multi-billion-dollar observability markets have been built around measuring the symptoms of failing systems—metrics, logs, and traces that tell engineers when a service has crashed, latency has spiked, or an error rate has climbed. However, these tools remain inherently post-mortem. Addressing this fundamental gap in modern enterprise technology, Empirik has officially emerged from stealth mode, announcing $21 million in total funding to pioneer the world’s first autonomous infrastructure engineering platform.
Led by a team of seasoned enterprise technology veterans, Empirik introduces a transformative shift in how organizations manage complex digital environments. By moving away from reactive firefighting and shifting toward a proactive, agent-driven architecture, the company aims to become the foundational system of record for operational change.
The Genesis Within Sequoia Capital: Background and Chronology
The origins of Empirik trace back to decades of frustration experienced by enterprise IT leaders. Co-founders Avon Puri, who previously served as Senior Vice President and Chief Information Officer at Rubrik and Vice President of Engineering and Applications at VMware, and Sudheer Dhurjati, who worked alongside Puri across three major technology firms, witnessed the same operational bottlenecks repeat themselves continuously. Enterprises were pouring immense capital into understanding when systems broke, yet virtually ignoring the fundamental driver of infrastructure behavior: change.
Every day, thousands of modifications occur across an organization’s digital footprint. A new identity policy is attached, a Terraform provider completes its execution, or a feature flag is flipped in a production environment. Historically, these actions have been treated as administrative constraints—static tickets, approval forms, or tribal knowledge buried within internal communication channels like Slack and email. While occasionally logged for compliance purposes, these changes were never systematically leveraged to drive infrastructure engineering workflows.
Recognizing this critical missing link, Puri and Dhurjati conceptualized the initial architecture for Empirik internally within Sequoia Capital. Observing that while software engineering was rapidly adopting AI coding agents, enterprise infrastructure remained largely unmodernized, Sequoia subjected the project to its rigorous investment evaluation process. Following a successful incubation period, the venture spun out as an independent entity.
To lead the company into its commercial phase, the founders brought in Kartik Chandrayana as Chief Executive Officer. Chandrayana is a repeat entrepreneur whose previous venture, Twin Prime, was successfully acquired by Salesforce. Following the acquisition, he spent five years as Salesforce’s Vice President of Product for Observability and Big Data, and most recently served as Chief Product Officer at Quantum Metric. With a robust executive team in place, Empirik steps out of stealth backed by $21 million in institutional funding to address a blind spot that has plagued enterprise IT for decades.
The Engineering Challenge: Why Infrastructure Lacks Version Control
To understand Empirik’s market positioning, industry analysts point to the stark contrast between modern software engineering and infrastructure management. Over the past several years, agentic coding has accelerated exponentially because application code resides in version-controlled repositories. This structure makes an application’s architecture and underlying intent completely legible to machine learning models.
Infrastructure, conversely, has never possessed this foundation. While Infrastructure-as-Code (IaC) tools represent a notable advancement, they typically depict a declared state rather than the dynamic reality running live in production. Enterprise architectures are scattered across a complex maze of multi-cloud resources, Kubernetes clusters, legacy on-premise systems, networking layers, and disparate identity providers. Crucially, infrastructure lacks a universal pull request mechanism; every alteration relies heavily on the institutional memory and manual oversight of individual engineers.
Established observability giants—including Datadog, Dynatrace, and Splunk—have built multi-billion-dollar empires by measuring metrics and alerts. Yet, these tools fundamentally answer the question of what happened, not why it happened. Empirik’s core thesis introduces what it identifies as a fourth pillar of observability: the changes themselves. Rather than generating an alert indicating that a service’s latency increased by 300 percent over a 24-hour period, Empirik’s platform correlates the issue directly to its origin, identifying precisely which configuration or deployment triggered the anomaly. Furthermore, the platform calculates risk at the inception of a change, enabling systems to warn operators or automatically block high-risk deployments before they reach production.
The Infrastructure Compiler and Agentic Workflows
At the heart of Empirik’s technology stack is a proprietary infrastructure compiler. Traditional compilers translate source code into executable software; similarly, Empirik’s compiler ingests and processes metadata from customer cloud environments, identity management systems, CI/CD pipelines, and SaaS platforms. It translates these disparate data streams into a live, unified operational graph mapping millions of relationships between enterprise assets and accounts.
This operational graph provides real-time visibility into who made a change, what was altered, and whether that specific modification caused a downstream failure. Designed specifically to handle the realities of Fortune 500 enterprises, the platform bridges the gap between modern cloud-native architectures and legacy hybrid systems. By avoiding the common startup shortcut of building exclusively for greenfield Kubernetes environments or a single public cloud provider, Empirik ensures comprehensive operational context across an organization’s entire digital surface area.
Furthermore, the platform integrates seamlessly into modern agentic workflows via the Model Context Protocol (MCP). By connecting directly into developer tools like Claude and ChatGPT, Empirik empowers both human engineers and autonomous AI agents to reason over infrastructure changes using verifiable, real-time context rather than speculation. This capability transitions the industry from manual oversight to an era of the Autonomous Infra Engineer—software capable of safely planning, assessing, and operating complex enterprise infrastructure.
Early Traction and Enterprise Validation
Even prior to its public launch, Empirik’s platform has gained significant traction across multiple industry sectors, processing millions of raw change and telemetry events every week. The platform’s dependency graphs currently map millions of enterprise resources spanning major public clouds and on-premise infrastructures.
Early deployments highlight diverse operational benefits:
- Financial Services: A major Fortune 500 financial enterprise turned to Empirik following a priority-zero (P0) outage caused by an unapproved configuration change. Similarly, payment processing firm TCBPay, which manages over $1.5 billion in annual transaction volume, reduced its sensitive configuration file detection time from 30 minutes to just 10 seconds.
- Managed Service Providers: Avahi integrated Empirik directly into its GitHub Actions workflows, enabling automated evaluation and real-time blocking of risky infrastructure changes at the source.
- Healthcare and Consumer Goods: Guardant Health expanded its initial deployment from production environments to encompass all internal development clusters as well as on-premise assets. Meanwhile, a global Fortune 50 Consumer Packaged Goods (CPG) enterprise is scaling its deployment to anchor its autonomous infrastructure roadmap.
Customer feedback indicates widespread improvements across multiple operational domains, including the prevention of high-risk deployments, rapid detection of unapproved configuration drifts, accelerated incident response timelines, and streamlined rollback decision-making.
Industry Implications and Future Outlook
The launch of Empirik arrives at a critical juncture for enterprise digital transformation. As businesses increasingly deploy autonomous agents to automate software development, customer service, and marketing workflows, IT infrastructure has remained the final operational frontier requiring modernization.
Industry analysts observe that as organizations transition toward autonomous operations, the ability to maintain a verifiable system of record for operational changes will become paramount. By bridging the gap between human engineering intent and machine execution, Empirik addresses a fundamental enterprise question: What changed, and did that cause the incident?
With $21 million in funding and a roster of enterprise clients validating its technology, Empirik is positioned to redefine the boundaries of infrastructure management, establishing a new operational standard for both human engineers and the autonomous agents of the future.
