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The roadmap from narrow dedicated offerings through managed clusters to a governed multi-tenant GPU platform — engineered for enterprise AI workloads across training, inference and research.
NOVACORE Compute delivers high-performance GPU infrastructure purpose-built for AI training, inference and research. The platform spans dedicated single-tenant servers, reserved capacity blocks, managed AI clusters and eventually a full multi-tenant GPU cloud — each stage validated against real customer demand before capital is committed. The architecture is built from the ground up around InfiniBand NDR fabric, NVMe-tiered storage and enterprise-grade security controls, ensuring that AI teams get predictable throughput, strong workload isolation and transparent unit economics at every scale.
Simple, predictable, strongly isolated — the first commercial offer. Entire GPU servers rented to single tenants with dedicated storage, networking and monitoring. Designed for enterprises that require complete tenancy separation and predictable monthly billing with no shared infrastructure.
Monthly, quarterly or annual GPU commitments that stabilise financing and guarantee availability. Customers reserve a minimum GPU footprint in exchange for discounted rates and capacity guarantees. Suitable for teams with predictable baseline workloads and procurement cycles that reward long-term planning.
NOVACORE assumes responsibility for drivers, storage, networking, monitoring, job scheduling and security patching. Customers focus on model development and deployment while the platform team handles infrastructure operations. Kubernetes-based orchestration with integrated observability, logging and alerting across the entire cluster.
A scaled, orchestrated and metered platform serving a broad customer base with self-service provisioning, elastic scaling and programmatic API access. Multiple tenants share physical infrastructure with logical isolation enforced at the hypervisor, network and storage layers. Usage-based billing with fine-grained metering across GPU hours, storage consumption and network egress.
Software companies, universities, AI startups, engineering and research organisations, media companies and public institutions deploying private AI. The platform is designed for organisations that require governed infrastructure with strong isolation guarantees — not for casual experimentation on shared public cloud.
Secure AI and high-performance computing for enterprises, governments and research.