AI & GPU Cloud
AI runs on accelerators, not promises. GPU capacity on demand, India-sovereign infrastructure, and an MLOps path from experiment to production — no CapEx gamble.
GPU as a service for AI training and inference, sovereign AI cloud environments, AI studio workspaces and data platforms. Accelerators on demand, no upfront CapEx, with India-located residency for workloads that must stay in-country.
Products in this family
Each capability is delivered as a managed service. Select one to scope a solution or request a quote.
GPU as a Service
On-demand GPU accelerators for training and inference — from a single card to multi-GPU nodes with NVLink — billed only for active compute time. Sessions provision in minutes with pre-installed ML frameworks, so you never buy silicon that sits idle.
Learn moreSovereign AI & GPU Cloud
India-located AI infrastructure: GPUs, data, and models all resident within Indian jurisdiction. Built for regulated sectors and government workloads where the DPDP Act and data-residency mandates are hard requirements — no building a private data centre to meet them.
Learn moreAI Studio & Data Platform
Integrated MLOps platform — feature stores, versioned datasets, notebook workspaces, pipeline orchestration, and inference endpoints in one environment. Closes the handoff gap between data prep, training, and deployment so the full AI lifecycle lives in one place.
Learn moreAI Inference Endpoints
Production-grade model serving behind a scalable API — autoscaling, canary rollouts, A/B testing, and p99 latency observability. Models warm to eliminate cold starts and cache answers for repeated requests. One endpoint to take any trained model live.
Learn moreTraining Clusters
Multi-GPU compute clusters wired with InfiniBand or RoCE for distributed deep-learning training where the bottleneck is your research, not the fabric. GPUDirect RDMA, job scheduling, and automated checkpointing mean a node failure costs an epoch, not the entire run.
Learn moreNotebook Workspaces
GPU-backed Jupyter and VS Code workspaces with curated ML environments (PyTorch, TensorFlow, RAPIDS) and persistent storage. Sessions spin up in seconds with on-demand GPU attachment and release when idle — no more setting up libraries for every experiment.
Learn moreData Integration & Governance
ETL/ELT pipelines with field-level lineage, automated quality checks that catch bad data before it trains a model, and freshness monitoring that pages someone when a source goes quiet. Trace a training table back to its source and prove it's the clean, current version.
Learn moreData Visualization
Interactive dashboards with drill-down, role-based views, and live data connectors to the systems you already run. Designed for the person who makes the decision — not a static PDF report that arrives stale.
Learn moreArtificial Intelligence
Disciplined AI strategy and delivery — ML, computer vision, and NLP applied to business decisions like demand forecasting, document extraction, and support triage. We start from the decision you need and work backward to the model, with a human-in-the-loop where the cost of error is real.
Learn moreAI Agent Development
Autonomous AI agents that complete tasks end-to-end — triage tickets, query databases, draft responses, move data between systems — with bounded scope and exception escalation to humans. Tool-calling, RAG, and guardrails keep them inside the lane you set.
Learn moreWhat a AI & GPU Cloud engagement covers
GPU capacity on demand
NVIDIA A100 and H100 capacity from a single card upward, including multi-node NVLink and InfiniBand or RoCE cluster fabric for distributed training.
Sovereign AI environments
Accelerated infrastructure located in Indian regions for workloads constrained by data residency, with DPDP-aligned controls and no cross-border egress by default.
MLOps path to production
Notebook workspaces, pipeline orchestration, feature stores, model registries and served inference endpoints that scale on request.
Data platform
Ingestion, transformation, governance and visualisation, so models train on data that is governed rather than on whatever copy was nearest.
Applied AI and agents
Retrieval, document processing and agent development against your own data, scoped to a business process with measurable output.
The operating model behind the technology
Size against the workload
Training and inference have different economics. We model memory, interconnect and duty cycle so you rent capacity that fits the job rather than the largest available instance.
Start small, then scale
Most engagements begin with a bounded experiment on a small cluster. Capacity expands once the approach has shown it works on your data.
Guardrails on spend
Budget alerts, quota per team and idle-resource reclamation stop an experiment from turning into a standing charge nobody reviewed.
Hand over the pipeline
We document and hand over the code, container images and pipeline definitions so your team can operate and extend the platform without us in the loop.
Questions buyers actually ask
Do we need to buy GPUs outright?
No. Capacity is rented, which matters because accelerator generations turn over faster than typical hardware depreciation cycles. You avoid owning an asset that is superseded before it is written down.
Which accelerators are available?
NVIDIA A100 and H100 are the standard offerings, with cluster fabric options for distributed training. Availability and lead time are confirmed per engagement rather than assumed.
Can sensitive training data stay in India?
Yes. Sovereign environments keep compute and storage in Indian regions with access controls aligned to DPDP, which is usually the deciding requirement for regulated sectors.
How is GPU time billed?
Engagements are quoted, and the commercial shape follows the workload: reserved capacity for steady training pipelines, on-demand for experiments and inference that fluctuates.
Can you build on models we already use?
Yes. We work with open-weight models, your fine-tuned checkpoints and managed provider APIs, and we say plainly when an API is the cheaper answer than running your own.
Need a solution tailored to your environment?
Our solutions architects will scope the right product mix for your infrastructure, timeline and budget — no obligation.