Kunal Agarwal

Co-Founder & CEO Unravel Data

Last Reviewed: September 18, 2026

Executive Summary

Kunal Agarwal is the co-founder and Chief Executive Officer of Unravel Data, a Palo Alto company he started in 2013 that applies purpose-built AI to data observability and FinOps — understanding why large-scale data infrastructure fails, and why it costs what it does. The two questions turn out to be the same one. When a data pipeline runs slowly, an enterprise can usually fix it by adding compute, which works and is expensive; over time that reflex produces platforms that are simultaneously unreliable and ruinously costly, with nobody able to explain which workloads are responsible. Agarwal came to the problem from both sides, having run big data infrastructure at Sun Microsystems and led Oracle implementations at Fortune 100 companies.

Career Highlights

• Co-founded Unravel Data in 2013 and leads it as CEO.
• Led the company through a $50 million Series D round in 2022 backed by Third Point Ventures.
• Co-founded Yuuze.com, an early personalized shopping and recommendation venture.
• Ran big data infrastructure at Sun Microsystems, including the Sun Grid Computing Engine.
• Led Oracle product sales and implementation at several Fortune 100 companies.
• Member of the Fast Company Executive Board and the Forbes Technology Council.
• Holds a Computer Engineering degree from Valparaiso University and an MBA from Duke’s Fuqua School of Business.

Professional Journey

Agarwal studied computer engineering at Valparaiso University and later took an MBA at Duke University’s Fuqua School of Business. His early career combined deep infrastructure work with enterprise delivery: at Sun Microsystems he worked on big data infrastructure including the Sun Grid Computing Engine, the distributed workload scheduler that was among the earlier mainstream attempts to manage computation across clusters rather than machines, and he led sales and implementation of Oracle products at several Fortune 100 companies. He also co-founded Yuuze.com, an early venture in personalized shopping and what-to-wear recommendations.

That combination — the scheduling layer underneath distributed computing, and the experience of actually deploying enterprise software inside very large organizations — is the specific background Unravel Data required. He co-founded the company in 2013, at the point where enterprises were moving decisively onto Hadoop and its successors and discovering that distributed data platforms fail differently from databases. A slow query on a single database has an identifiable cause; a slow job on a cluster may be contending with hundreds of others for memory, competing for I/O, skewed across partitions, or simply mis-configured, and the tooling to tell them apart did not exist.

Unravel built that diagnostic layer, applying machine learning to the performance telemetry of data platforms to identify root causes rather than merely reporting symptoms. As workloads moved to cloud platforms, the same capability acquired a second and arguably more urgent application: cost. Cloud data infrastructure bills by consumption, so an inefficient pipeline is not just slow but continuously expensive, and finance teams began asking questions that engineering teams could not answer. The company positioned itself accordingly across both data observability and FinOps, and Agarwal raised a $50 million Series D in 2022 led by Third Point Ventures.

He speaks regularly at industry events and writes on data observability, and is a member of the Fast Company Executive Board and the Forbes Technology Council.

Education

Duke University, The Fuqua School of Business

MBA

Valparaiso University

Bachelor’s degree, Computer Engineering