IaaS – AI Infrastructure

GPU & CPU Compute Pools

Access dedicated or shared CPU and GPU resources optimised for AI and ML workloads. Scale on-demand for individual classes, projects or research tasks without costly on-premises hardware.

Multi-core CPU instances for general computation
High-end NVIDIA GPUs for deep learning, NLP and computer vision
Flexible allocation and scaling per student or research team
Monitoring & usage analytics for cost optimisation
NVMe SSD-backed storage for high-speed data access
Pre-configured AI-ready OS and drivers

Virtual AI Labs

Simulate real-world AI lab environments online. Students access pre-configured notebooks, datasets, ML frameworks and tools without worrying about setup or device limitations.

Pre-installed JupyterLab, TensorFlow, PyTorch and other frameworks
Shared & private lab spaces per student or team
Guided labs for coursework & capstone projects
Support for collaborative learning and mentoring
High-availability instances backed by enterprise-grade servers
Flexible snapshots and recovery for ongoing experiments

Secure Multi-Tenant Isolation

Ensure each student or research group has an isolated environment, preventing data leaks and interference while maintaining compliance with privacy regulations.

Container-based isolation with Kubernetes orchestration
Role-based access control and permission management
Audit logs for usage and compliance
Secure data residency within India
End-to-end network segmentation and firewall protection
Encryption at rest and in transit for all datasets

IaaS Workflow

1

Request VM / GPU Instance

2

Provision Resources

3

Access Virtual AI Lab

4

Run Experiments

5

Monitor Usage

6

Save Snapshots

Pair IaaS With

PaaS – Platforms

Add preconfigured ML frameworks, MLOps pipelines and domain datasets on top of your IaaS layer.

Learn More

Educational AI Labs

Purpose-built IaaS for colleges and universities with AICTE-aligned curriculum integration.