Infradelta Solutions helps organizations migrate to the cloud, modernize applications, build AI-ready platforms, and operate secure infrastructure at enterprise scale.
Start Your Cloud & AI TransformationPublic cloud, private cloud, or the racks in your own building. Our engineers build landing zones, Kubernetes platforms and AI infrastructure on whichever you have standardised on — or across several at once.
Landing zones, EKS, GPU instances, migration tooling, and cost governance across accounts and organizations.
Enterprise-scale landing zones, AKS, Azure OpenAI integration, hybrid identity, and Arc-managed on-premises estate.
GKE platforms, Vertex AI workloads, data pipelines, and multi-region architectures for analytics-heavy estates.
OpenStack, VMware and Nutanix estates run as a proper self-service platform, with the same automation and guardrails as public cloud.
Your own racks and GPU fleet: capacity planning, hardware refresh, networking, and Kubernetes on bare metal — for workloads and data that stay on site.
Amazon Web Services, Microsoft Azure and Google Cloud are trademarks of their respective owners. Infradelta Solutions is an independent technology services provider and references these platforms only to describe the services we deliver.
Organizations are under pressure to modernize legacy systems, control cloud costs, accelerate software delivery, and adopt AI while maintaining security and reliability.
Multi-cloud environments, increasing operational costs, and a shortage of cloud engineering expertise slow innovation.
Monolithic applications and traditional infrastructure prevent organizations from moving faster.
Enterprises need secure platforms for LLMs, AI agents, GPU workloads, and intelligent automation.
Four practices covering the full infrastructure lifecycle — from the first migration wave through to round-the-clock operations.
As organizations adopt AI agents, they need a secure operating platform to manage identity, tools, workflows, governance, and AI workloads.
Three stages, run in order. Each ends with something you can review before the next begins.
Application discovery, dependency mapping, cloud readiness analysis, and a modernization roadmap.
Containers, Kubernetes, managed databases, automation, and cloud-native architecture.
Continuous monitoring, optimization, security, and reliability engineering.
A pilot proves an idea can work. Production means it works every day, for every user, under audit, at a cost you can defend. Those are different engineering problems — and the gap between them is where we do most of our work.
Short pilot on your real data, with success criteria agreed in writing before we start.
Guardrails, evaluation suite, identity, logging and cost controls wrapped around the working pilot.
Staged rollout behind flags, starting with a small group, with automatic rollback on regression.
Monitoring, retraining, model upgrades and 24x7 support once it is carrying real traffic.
Infrastructure cost optimization
Platform availability
Faster incident resolution
Enterprise AI adoption
Three engagements we have taken from problem to working system — what each one started from, what we built, and where it stands today.
Whether it's a migration, a Kubernetes platform, or an AI workload that needs somewhere secure to run — send us a note and we'll come back with a practical next step.
