Dasera
A California data security platform, developed out of UC Berkeley research, that automates governance and risk management across the cloud data lifecycle.
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Dasera builds a data security and governance platform focused on automating oversight of how data is accessed, used, and moved across cloud environments, targeting finance, healthcare, and technology enterprises. The product originated from research at UC Berkeley and was co-founded by Ani Chaudhuri and Noah Johnson, the latter holding a PhD in computer science from Berkeley.
The company raised a $6 million seed round in May 2021, led by Sierra Ventures, and a $12 million Series A in April 2023, also led by Storm Ventures, bringing disclosed total funding to roughly $20 million. Its pitch centers on automating data governance and risk controls across the full cloud data lifecycle rather than treating data security and compliance as separate, manually reconciled workstreams.
Public reporting on Dasera has been sparse since its 2023 Series A, with no newer funding round, named enterprise customer, or independent efficacy evidence surfacing in available sources. That makes it difficult to assess whether the company’s product vision has translated into meaningful market traction in the two-plus years since, and it should be weighed as an early-stage platform whose current momentum is not well documented publicly.
Innovation Matrix Assessment
Progressed from a Berkeley research project to a seed and Series A product within a few years, but public evidence of continued iteration since 2023 is sparse.
Automating data governance across the full cloud data lifecycle addresses a genuine gap between security and compliance teams that often work from separate tools.
Only two disclosed rounds, both before 2024, and no named enterprise customers or newer funding appear in available public reporting.
Cloud data governance automation is a reasonable but increasingly common approach rather than a structurally new way of solving the data security problem.
No independent test results, named customer case studies, or incident evidence were found in public sources.
Automated data governance remains a relevant need, though the company's current traction trajectory is unclear from public information.
Why CISOs Should Care
Aims to reduce the manual reconciliation between data security controls and compliance obligations across cloud data stores.
What Makes It Different
Built on academic research into automated data governance rather than retrofitting traditional DLP tooling for the cloud.
The Matrix Verdict
48/100 — EMERGING / UNRANKED
Falls into Emerging/Unranked: a credible technical origin and two real funding rounds, but public evidence of recent traction or independent validation is too thin to score higher with confidence.
Editorial Note: Claims vs. Verified Findings
Founding year and headquarters details come from a single aggregator source (Zonebourse) and were not independently cross-confirmed; no vendor efficacy claims beyond general product description were found to flag.
Sources
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