Zibra Labs
Distributed Compute for AI
What they do
AI and quantitative trading teams struggle to access affordable, scalable high-performance compute for large parallel simulation and other demanding workloads.
Zibra Labs builds distributed HPC clusters by aggregating the cheapest CPUs and GPUs across hyperscalers and neoclouds to run large-scale parallel compute workloads.
Quantitative trading firms and AI teams that need frontier-grade compute for backtesting, post-training, fine-tuning, and batch inference.
Founders
Former tech-lead of Ray. Previously building databases at LinkedIn. I've built systems that run on hundreds of thousands of machines and serve over a billion people.
After a career making software that serves over a billion people, with a background primarily in large databases, I'm now building HPC clusters at Zibra Labs The past two years I've been focused on what the next generation of AI data center software looks like — and working to shape that future. I've been fortunate to do much of this in open source, which I'm deeply passionate about. Talk to me about databases, Mahjong, guitars, or weird horror movies. I'm currently building Zibra Labs.
Company timeline
- Founded2026
- YC batchSpring 2026
- StatusActive
- Team size2 people
- LocationSan Francisco, CA, USA
