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Empirik raises $21M to predict and prevent IT outages

Sequoia-incubated startup Empirik has spun out with $21 million in seed funding to launch an AI-driven platform that predicts and prevents infrastructure outages before they occur.

TechCrunch AI13 hrs agoBusiness
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Empirik has officially spun out as an independent company after securing $21 million in seed funding from Sequoia Capital, Canapi, and Alumni Ventures. Originally incubated by Sequoia in 2023, the startup was conceived by tech veterans Avon Puri, former chief digital and information officer at Sequoia, and Sudheer Dhurjati. Earlier this year, the company recruited Kartik Chandrayana, the former chief product officer at Quantum Metric and vice president of observability at Salesforce, to serve as its chief executive officer.

Unlike traditional observability tools that react to system failures after they occur, Empirik aims to prevent outages entirely. The platform tracks system changes and analyzes their potential ripple effects across an organization's entire infrastructure. Sequoia partner Bogomil Balkansky described the tool as an autonomous "traffic cop" that permits low-risk updates, establishes guardrails for larger modifications, and flags the most hazardous changes for human intervention.

For DevOps and site reliability engineering teams, this technology shifts the workflow from reactive troubleshooting to proactive management. By automating routine incident resolution, engineers can offload tedious tasks and focus on higher-value priorities. The company compares its mission to what tools like Cursor and Claude Code have done for software developers, aiming to bring agentic AI automation to infrastructure engineering.

Since its launch earlier this year, Empirik has already secured a customer base ranging from early-stage startups to Fortune 500 enterprises, including S&P Global, Guardant Health, and a major consumer packaged goods company. While the startup operates alongside AI SRE platforms like Resolve and the Sequoia-backed Traversal, its creators position it as a complementary layer focused specifically on tracking complex system dependencies across massive environments.

This is our own summary of reporting by TechCrunch AI

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