Cedana
Fast, reliable, reproducible AI with GPU live migration
What they do
AI training and inference workloads are costly, slow to start, and unreliable when GPUs fail or capacity changes, making orchestration and utilization inefficient.
Cedana provides Kubernetes-integrated live migration and orchestration for CPU/GPU workloads (supporting Kueue, Slurm, and KServe) to enable fast, reliable, reproducible, and cost-optimized AI compute.
ML platform teams and infrastructure engineers at enterprises, cloud providers, and AI labs running GPU-based training and serving workloads.
Founders
CEO of Cedana. Previously CEO/co-founder of Engooden, AI-powered chronic disease management proven to improves outcomes and lower costs for patients (Series B). VP of Corp Development for Petra Systems (predictive smart grid/solar company) scaled from $0-$70M ARR. At TL Ventures ($1.6B VC fund) investing across semi, software and systems. Built a system for large-scale, automated ML and computer vision at MIT CSAIL. Patents and publications in AI, computer vision.
Co-founder/CTO at Cedana. Previously Robotics at Shopify. Previously previously Mech/Aero, published in control systems, neuromorphic computing and satellite formation flight.
Open roles 2
Company timeline
- Founded2023
- YC batchSummer 2023
- StatusActive
- Team size5 people
- LocationNew York, NY, USA; Remote
