Built by researchers who knew the data problem was holding AI back
Two Carnegie Mellon professors set out to solve the challenge they kept hitting in research — and that every enterprise AI team faces in production: the data you need doesn't exist yet, and waiting for it is not an option.
Our Mission
Give every time-series ML team the data they need to build AI that works in production — not just in the lab. No waiting on rare events. No manual labeling sprints.
Our Vision
A world where data scarcity is never the bottleneck - where AI teams can generate the exact training and evaluation data they need, for any domain, on demand.
The people behind Rockfish — from CMU research labs to product and engineering
We're a small, technical team that has spent years working on data systems, security, observability, ML infrastructure, and large-scale networking problems.
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Advised by operators and researchers
who've done this before
Our advisors bring experience from Google, Cisco, the US Military, and enterprise AI — giving us direct access to the buyers, builders, and domains we serve.
Customer Advisory Board
Practitioners from enterprise AI teams who help us stay close to real-world deployment challenges.
Backed by investors who understand enterprise infrastructure
Practitioners from enterprise AI tWe're grateful for the support of firms focused on deep-tech and enterprise AI.eams who help us stay close to real-world deployment challenges.
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ANGEL INVESTORS
Interested in joining the team?
We don't have open roles right now, but we're always happy to hear from people who care about data systems, ML infrastructure, or making AI reliable at scale. Reach out and introduce yourself.