Nalvera is a streamlined platform for medical imaging research. Upload your scans, pick a peer-reviewed model, and run inference on managed cloud GPUs — segmentation, classification, generation, and more. Reproducible results, no infrastructure overhead.
Submit multi-file jobs and a GPU worker picks it up in seconds. No queue tooling to install, no Python or CUDA versions to match.
Peer-reviewed AI models in medical image segmentation, classification, and generation
Configure each run in seconds: choose a task or submodel and assign it to a personal or lab budget.
We don’t train on your data by default. Research sharing is explicit opt-in. Delete is one click.
Compute, storage, and database stay inside the EU.
Top up once, invite colleagues, run jobs against a pooled balance. Per-member spending caps included.
No payment details required. Start with a handful of starter credits and top up further whenever you need — credits never expire.
Memberships add a recurring monthly quota and unlock following perks:
You can spend either type on any job.
Comes with your plan, and resets each billing cycle.
Top up whenever you need extra capacity. Credits don't expire — your balance only drops when you actually submit a job.
A whole-body CT segmentation runs around 2–3 credits — that's €0.50–€0.75 at the €0.25 standard price, or as little as €0.34–€0.51 on the highest member tier. Smaller ROIs and single-slice jobs cost a fraction of a credit.
The exact price is calculated from your scan's voxel count and shown live in the submit form — before you confirm. No surprise bills.
For academic groups, labs, and vendors with a peer-reviewed model. Publish, get cited, and get compensated using our platform.
Provide us with your model (weights). We take care of everything around it:
Drag-drop a NIfTI .nii.gz file up to 250 MB. We validate the shape and content before queuing.
Browse the model catalog and pick what fits your image — segmentation, classification, generation, or analysis. The cost preview updates live.
A worker picks up your job. Watch progress live on the Job Queue, with expected runtime and status updates.
Open the inference result in the built-in image viewer and/or download the NIfTI / JSON output — ready for ITK-SNAP, 3D Slicer, FIJI, or your own pipeline.