NeevCloud, India’s AI-native sovereign cloud and AI SuperCloud platform, participated at KubeCon + CloudNativeCon India 2026. The company showcased its Kubernetes-native AI infrastructure platform built for developers, enterprises and platform engineering teams deploying AI applications at scale.
At the event, NeevCloud demonstrated how AI workloads can function as first-class Kubernetes primitives through native control loops, operators, CRDs and GitOps-ready workflows, enabling organizations to build and scale AI applications without relying on proprietary AI consoles or fragmented infrastructure environments.
AI-native SuperCloud built specifically for India’s emerging AI ecosystem, NeevCloud combines sovereign infrastructure, secure computing, GPU cloud, inference services, agentic studio and developer tooling into a unified platform purpose-built for AI innovation and enterprise adoption.
“NeevCloud is built on a simple belief, the future of AI infrastructure cannot be dependent on foreign jurisdictions, opaque platforms or disconnected tooling,” said Mr. Narendra Sen, Founder & CEO, NeevCloud. “At KubeCon India, we showcased a fundamentally different approach to AI infrastructure, one where AI workloads are native to Kubernetes, sovereignty is built into the architecture by default and developers retain full control over how they build, deploy and govern AI systems.”
NeevCloud’s platform architecture spans the full AI infrastructure stack, from liquid-cooled data centers and GPU infrastructure to AI storage fabrics, inference platforms and developer environments. According to the company, this vertically integrated approach enables tighter performance optimization, predictable costs and stronger guarantees around data residency and compliance.
“Our thesis is straightforward, if AI is going to run in production, it has to live where the rest of production already lives, which is inside Kubernetes,” said Mr. Vijayakumar, Chief AI Officer, NeevCloud.
A major focus area at the event was NeevCloud’s dedicated model inferencing capabilities, designed to give enterprises and AI-native businesses single-tenant, GPU-isolated private inference endpoints with predictable ultra-low latency, committed throughput and transparent per-token economics. Unlike shared serverless inference, dedicated inferencing on NeevCloud allocates reserved GPU capacity to a single workload eliminating noisy-neighbour effects, enabling consistent SLAs, and giving customers full control over model version, runtime configuration and batching behaviours.
The company also highlighted its “Twin Studios” framework comprising Agentic Studio and Developer Studio, designed to simplify how developers build, deploy, govern and observe AI agents and inference workloads. The platform supports MCP-native integrations along with SDKs and APIs for Python, TypeScript and Go, enabling interoperability across modern AI agent frameworks and cloud-native development environments.
Unlike traditional hyperscaler AI offerings that often bypass Kubernetes-native workflows, NeevCloud extends Kubernetes primitives for AI operations, allowing platform engineering teams to manage AI workloads using familiar cloud-native tooling and operational models.
“At a time when enterprises are looking to operationalize AI responsibly, the infrastructure layer becomes the strategic layer,” added Sen. “India has the opportunity to build an AI ecosystem that is sovereign, developer-first and cloud-native from day one. That is the ecosystem NeevCloud is building for.”
Visitors at the NeevCloud booth during KubeCon + CloudNativeCon India 2026 experienced live demonstrations of Kubernetes-native AI orchestration, secure AI infrastructure capabilities and developer tooling, agentic studio designed to help teams deploy AI agents and inference services in production environments.
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