Jio AI Cloud Partner: Sovereign GPU Infrastructure with NVIDIA H200 for India's AI Builders
What Jio AI Cloud is
A sovereign GPU cloud, built in India, for India
Jio AI Cloud is Reliance Jio's own GPU platform, running in Jio's Indian data centres. It gives you NVIDIA and AMD accelerators on virtual machines, on managed Kubernetes, or as dedicated bare metal, on infrastructure operated inside India.
It differs from a global hyperscaler in 3 ways: where it runs, which accelerators it offers, and how you buy.
Sovereign by default
2 H200 tiers, very different prices
Reserved terms, not on demand
Jio AI Cloud and Jio Azure
Our Jio AI Cloud Service Portfolio
What the platform provides, and what we build on top
The Platform, and How We Size It
Ready-made environments
Everything else you need around the GPUs
Compute & Orchestration
Storage - 7 Tiers
Networking & Security
Managed Databases
Jio Cognitive Services
What we need to size your workload
From Provisioned Tenant to Running AI Platform
What a GPU quote does not cover
When you buy GPU capacity, what arrives is a provisioned tenant and hardware. What you need is a platform your ML team can actually ship on. Everything in between still has to be built and operated.
Pace Wisdom builds and operates that layer.
Prove It Before You Commit
Benchmark your model on H200 first
Nobody should sign a GPU commitment on a datasheet. Run your model, your data loaders and your pipeline on the hardware before you commit.
We confirm workload fit, benchmark scope and GPU availability before scheduling, then measure your workload on H200.
What it covers
How We Work
6 phases, coordinated end to end.
What we are running today
Conversational voice AI
Voice AI training and inference platform
Space technology training cluster
Industries We Serve
Pace Wisdom x Jio AI Cloud
Official JioCloud ISV Partner
We are an official ISV partner. We take the technical and commercial conversation to Jio on your behalf, so it starts from an established relationship rather than a cold enquiry.
We have already done this on this platform
We built and operate the workload that became Jio AI Cloud's first production AI customer.
We engineer the commercial model as well as the technical platform
Sizing, bill of materials, reserved-term modelling against your real usage pattern, cost governance, and the negotiation itself. Most partners hand you a quote. We work out what you should be buying first.
1 accountable team
Infrastructure and the AI platform on top of it, from the same team. No handoff between the people who provisioned it and the people who have to make it work.
Multi-cloud, so the advice is honest
We are an AWS Cloud Partner (AWS Advanced Tier Services Partner with DevOps Competency), and we work across Azure and Google Cloud. If sovereign GPU is not the right answer for your workload, we will say so.
Frequently Asked Questions
Which GPUs are available, and what if I need something else?
Jio AI Cloud offers NVIDIA H200 SXM, NVIDIA H200 NVL and AMD Instinct MI300X. If your stack is currently tuned for different hardware, that is what the benchmark is for. We confirm workload fit, scope and GPU availability before scheduling.
Is my data actually in India?
Yes. Jio AI Cloud runs in Jio's Indian data centres, operated by an Indian company. Managed key management and hardware security modules are available at the platform layer for workloads that need to demonstrate control over keys as well as location.
Who actually runs the cluster?
The platform provides provisioned infrastructure. Everything above that, including the scheduler, drivers, container runtime, model serving, monitoring and on-call, is built and operated by us under a managed service, or by your team if you would rather. We are explicit about this boundary at the sizing stage so there is no gap later.
What happens if I commit to a term and then need to scale down?
Worth understanding before you sign. There is no on-demand option for GPU, so a reserved term is the only way to buy. The shortest is 1 month, and it bills monthly rather than for the whole term in advance. Standard terms specify a minimum notice period and remaining-contract-value liability, but how those apply to a short reserved term is unresolved, so get the renewal, notice and cancellation terms into the order form before signing. For workloads with uncertain demand we recommend the shortest term first, and lengthening it only once measured utilisation justifies it.
What does it cost?
It depends on the accelerator, the form factor, the term you commit to and current availability, so any number quoted without knowing your workload would be a guess. GPU capacity is bought on a reserved term of 1, 6 or 12 months. Which H200 tier you are quoted usually moves the total more than the term does. Give us the 10 sizing inputs and we will build a real bill of materials across the options.
Are there data transfer charges?
Egress is billed on actual usage. Ingress treatment is confirmed for the configuration under consideration, and we verify both directions during sizing. For training workloads moving large datasets in and pulling weights and checkpoints out, transfer is a real line in the total cost rather than a rounding error, so we model it explicitly.
How is this different from Jio Azure?
Jio Azure is Microsoft Azure delivered from Jio's Indian data centres, with Azure services available inside India. Jio AI Cloud is Jio's own GPU and AI platform. They are different platforms for different use cases. We partner on both, so we have no reason to push you towards one.
Can you connect the cluster to our office network?
Yes. Site-to-site VPN connectivity is available, with access restricted to your network ranges. This is a standard part of how we set up training environments.
How long does it take to get GPUs?
GPU inventory varies with demand, so lead time is confirmed at the point of sizing rather than promised in advance. Define the requirement early so availability and lead time can be confirmed during sizing.
What if we outgrow this?
We work across AWS, Azure and Google Cloud as well, including as an AWS Cloud Partner. We favour Kubernetes, standard containers and widely used frameworks to reduce avoidable platform dependence. Any future migration path is assessed against the services your workload actually uses, and we will give you a straight answer on what it would take.
Find out how your model runs on H200
Bring us your workload and we will size it against your real usage, benchmark it on real hardware, and give you a bill of materials you can put in front of your board.
Contact Us
and have branch offices in California, USA and Mangalore, India.

