Cloud GPU instances
NVIDIA GPU instances by the hour or on commitment, from a single card up to multi-GPU.
Fine-tuning, experiments and inference that does not need a whole cluster.
We build and run on thisAn Indian GPU cloud for the runs that do not fit elsewhere.
NeevCloud is an Indian AI cloud built around NVIDIA GPUs. We build and run training and inference workloads on it, and can place committed spend through our partnership.
Not a boxed licence — we design and operate workloads here, and can place your committed spend through us.
What we work with
The products, and who each one suits.
5 listed
Bare-metal GPU clusters
Dedicated nodes with interconnect between them, for jobs that will not fit on one machine.
Multi-node training where the network between GPUs is the bottleneck.
Inference capacity
GPU capacity sized for serving rather than training — a different shape of load and a different bill.
Products with a model behind them and users in front of it.
Storage for training data
High-throughput storage sitting beside the compute, for datasets and checkpoints.
Training sets too large to shuttle between regions for every run.
Indian data centre footprint
Capacity hosted in Indian data centres, so the data does not leave the country. Currency and contracting entity are settled in the contract, not assumed here.
Organisations with residency written into a contract or a policy.
What buying through us changes
A partnership is only worth what it changes.
Better than list
On committed GPU capacity. The price of a GPU hour moves with term and volume — where you commit, we place it through our partnership rather than at list.
Named contacts
An escalation path into NeevCloud rather than a web form. Hardware faults and capacity questions go to a person, in working hours you share.
Startup credits
Where NeevCloud runs a credits or startup programme, we sponsor the application and write the technical case. The award is theirs to make.
How we help
The work around the product.
- Sizing and benchmarking — which GPU class the job needs, and what it costs here against the alternatives, before a term is signed.
- Environment build — drivers, CUDA, container images, distributed training setup and storage mounts.
- Multi-node training — scheduling, checkpointing and restart, so a failed node costs hours rather than the whole run.
- Inference serving — batching, autoscaling and an endpoint the application can depend on.
- Residency — training data, checkpoints and logs kept in India, documented well enough to show a customer or a regulator.
- Utilisation review — idle GPU billed by the hour is the fastest way to lose the saving, so we schedule and shut down.
Where this is not the answer
NeevCloud is a GPU cloud, not a general-purpose one. Your application, database and the rest of the estate will usually still live somewhere else, and we design for that split rather than pretending it away. It is also a younger provider than the hyperscalers — narrower catalogue, shorter operational history. If a workload needs breadth or a long track record more than it needs Indian GPUs, we will say so, and we will benchmark against any provider you prefer.
Also in this category
Cloud & infrastructure
Next step
Buying NeevCloud? Talk to us first.
Tell us what you are trying to do and we will come back with the sizing, the licensing and the price — from a partner, within two working days.