Proof from production.
How teams train, serve, and scale real AI products on Jarvislabs.
How ZYNG AI edits 5 million images a month on Jarvislabs
One GPU cloud for model training, always-on inference, and automated capacity that follows demand.
5M+
images edited every month
3
production compute modes
~10%
higher throughput reported
How Lossfunk residents run AI research on Jarvislabs
One GPU cloud for interpretability, reinforcement learning, and world-model research, from long L4 experiment runs to A100 and H100 training.
5
research projects profiled
40K+
reasoning rollouts generated on L4s
100+
steering runs across 4 open-source models
How BITS Pilani researchers image ultrafast electron dynamics on Jarvislabs
A GPU-enabled VM for ab-initio TDSE simulations of photoelectron momentum distributions, running Julia and CUDA.jl workloads without changing an established workflow.
3D
ab-initio TDSE simulations on GPUs
Julia
TDSE code accelerated with CUDA.jl
0
changes needed to deploy on Jarvislabs