GPU notebooks
for research teams.
Built for PhD students, university labs, and ag-science hackathon teams. Sign up, form a team, launch a Jupyter notebook on a real GPU — in under 15 minutes.
No credit card. No GPU quota application. No driver setup.
Built for
PhD & MS students
Skip the cluster ticketing queue. Get to your first epoch in one afternoon.
Hackathon teams
48-hour ag-science sprints with pre-loaded USDA corn/soy data and a shared GPU pool.
University cohorts
Course instructors provision a cohort, set per-team hours, and watch progress live.
Launch in minutes
Automated environment setup. Forget Docker headaches and driver versioning; focus entirely on your model architecture.
Pre-loaded datasets
Native access to the UC Davis corn and soy multi-spectral datasets. Validated, cleaned, mounted at /data on every notebook.
Team workspace
Centralized GPU allocation. Manage compute credits and shared experimental results across your entire research lab.
The dataset
USDA corn & soy, ready to train
Multi-spectral field imagery, hand-labeled by graduate researchers across three growing seasons. Cleaned, train/val/test split, and mounted read-only on every notebook so your team doesn't burn hours on data plumbing.
- 12 spectral bands, 2cm/pixel resolution
- Disease, water stress, and yield labels
- Parquet + GeoTIFF, indexed by plot ID
- Shared cache across team members
From soil to silicon
Three simple steps to high-performance compute.
Join your cohort
Sign up with academic email or Google. Pick your cohort, create or join a team.
Launch a notebook
One click. Your session goes from queued → starting → ready in seconds.
Track allocation
Live GPU-hour meter per team. Leads see usage, members see what's left.
Pricing
Free during MVP for university cohorts
We're working with a small group of universities and hackathons through the open beta. Cohorts get GPU-hour allocations at no cost. After GA, academic pricing stays free for individual coursework with paid tiers for labs that need more compute.
Frequently asked
What GPUs do I get?
Notebooks run on shared NVIDIA L4 and A10G instances during the MVP. Larger jobs (A100/H100) are coming through partner GPU providers and will surface in the launch dialog when available.
Do my notebook sessions persist?
Yes. Your home directory and any files outside /data persist across sessions. The /data mount is shared, read-only, and shared across your team.
What happens to my work after the hackathon ends?
Your notebooks, files, and team workspace stay accessible read-only for 90 days after the cohort closes. You can export everything as a zip at any time.
Is my data private?
Notebooks are scoped to your team via row-level security on the backend. Cohort organizers see aggregate usage but not your code or files.
Is Keeboh really open source?
Yes — MIT licensed. You can self-host the platform if you prefer to run it on your own GPU cluster. See GitHub for the deploy guide.
Our mission
"Our mission is to enable the next great discovery through AI, access to compute, and cross-department collaboration."