Reserved NVIDIA capacity
GPU hours held for your workload instead of bid for each time you need them.
Training and fine-tuning runs with a date attached to them.
We build and run on thisOur CEO co-founded this one. We are telling you first.
Podstack AI is an Indian GPU provider, and Anocloud’s CEO is one of its co-founders — a conflict we put at the top of the page rather than in a footnote. We will benchmark any Indian GPU provider you would rather use, on your own workload, before anything is signed.
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.
4 listed
Fractional GPU allocation
A slice of a card by the hour rather than the whole thing.
Development, evaluation and inference that would never fill a card.
India-resident placement
Where the workload has to stay in India, we place it with a provider that will put the region in the contract. We do not certify anybody else’s residency — that commitment comes from the provider, in writing, before anything is signed.
Regulated sectors and public-sector buyers with residency conditions in the contract.
Private model hosting
Open-weight models served on capacity that is yours, with no prompts leaving for a third-party API.
Teams whose data cannot be sent to a public endpoint.
What buying through us changes
A partnership is only worth what it changes.
Better than list on committed capacity
Committed GPU spend placed here prices below the published hourly rate. Because of the relationship, we show that quote alongside at least one other Indian provider — a discount you cannot compare is not a discount you can trust.
Named contacts — and why to discount that
Escalation goes to named engineers rather than a queue, which is partly a function of the shared history. That is a benefit and a bias at the same time, which is exactly why we also put a second provider in front of you.
Startup credits we sponsor
Indian GPU providers and the cloud programmes run credit schemes for early-stage companies. We prepare and sponsor the application. The award is the provider’s call, never ours.
How we help
The work around the product.
- Disclose the relationship in writing, in the proposal, before any commercial conversation starts.
- Benchmark your workload here and on at least one other Indian provider, and hand you both sets of numbers unedited.
- Size the capacity — how many cards, for how long, reserved or on demand — against what the profiling actually shows.
- Build and run the workload on it: images, drivers, schedulers, checkpoints and restarts.
- Handle the commitment and the billing, so there is one invoice and one line to query.
- Move you off it without argument if the numbers favour somebody else.
Where this is not the answer
The conflict is real. Anocloud’s CEO co-founded Podstack AI, so we have an interest in you choosing it — treat our recommendation on this page with more scepticism than anything else on the site, and hold us to the benchmark. If another Indian provider wins on price, availability or region, we will place your workload there and say why. You are also not obliged to come through us: you can contract with Podstack directly, and that is a legitimate thing to do.
Next step
Buying Podstack AI? 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.