Control Plane Corporation
Control Plane's mission is to let development teams leverage any cloud infrastructure as if it were one. It virtualizes compute, networking, identity and services across public clouds, private infrastructure, bare metal and Kubernetes into an AI-native virtual cloud with one operational model.
At a Glance
- Startups, enterprises and government organizations
- SaaS and high-traffic web applications
- AI-native companies and ML/GPU users
- FinTech, healthcare, education, cybersecurity, legal technology and e-commerce
- +2 more
AI Tools by Control Plane Corporation
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Control Plane
Multi Cloud Virtualization Platform
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Products & Services
The core virtual-cloud environment: a named set of locations that combines clouds, regions, private infrastructure, Kubernetes and bare metal into one deployable cloud abstraction.
A symmetric console, CLI, IaC, REST API and MCP-accessible platform for deploying, scaling, observing and securing containers, VMs, AI agents, stateful services, cron workloads and serverless workloads.
Patented identity brokering that lets a workload mix services from AWS, GCP, Azure, OCI and private environments without embedding provider credentials.
Continuous right-sizing and adaptive provisioning that allocates CPU and RAM to workload demand, supports scale-to-zero and is marketed to reduce compute spend.
Market Position
Control Plane positions itself as a virtual-cloud layer that does for the cloud what VMware did for hardware: one abstraction and operational model across AWS, GCP, Azure, OCI, private clouds, Kubernetes, VMs and bare metal. Its differentiation is cross-cloud workload portability, Universal Cloud Identity, adaptive capacity and built-in operations; it competes for use cases served by Heroku, Lambda, managed Kubernetes offerings and multi-cloud management/platform-engineering tools.
Leadership
Founders
Doron Grinstein
Co-founder and CEO; spent years as Chief Software Architect at Disney, SAP, Dell and VMware before leaving VMware in 2019 to build Control Plane. He has more than 25 years of software-architecture experience.
Dan Wilson
Co-founder and CTO; recruited by Doron Grinstein as an engineer who had encountered the same cloud-infrastructure fragmentation problem.
Thomas Stewart
Chairman, co-founder and CFO; a specialist in high-growth SaaS and cloud business models.
Executive Team
Doron Grinstein
Co-Founder and CEO
Former Chief Software Architect at Disney, SAP, Dell and VMware; more than 25 years in software architecture.
Dan Wilson
Co-Founder and CTO
Co-founder and technology leader recruited to solve the same infrastructure-fragmentation problems that motivated Control Plane.
Board of Directors
Founding Story
Doron Grinstein saw teams repeatedly rebuild networking, identity, TLS, observability and scaling plumbing, while also struggling with fragmented combinations of bare metal, VMs, managed Kubernetes and serverless. Inspired by VMware's hardware virtualization, he left VMware in 2019 to virtualize the whole cloud stack into a single manageable cloud; he recruited engineers including Dan Wilson and built Control Plane around that vision.
Business Model
Revenue Model
B2B cloud-infrastructure platform. Customers can use Control Plane-provided compute in a serverless/pay-as-you-go model, or run in customer-supplied environments and pay for managed CPU/GPU capacity and platform resources. Pricing is usage-based for CPU millicores, RAM, storage, observability, egress, load balancers and GPU-hours; enterprise customers can request demos and managed services.
Pricing Tiers
No contracts, minimums or lock-ins. CPU is $0.06205654 per millicore-month, RAM $0.00706330 per MB-month, egress $0.12/GB and shared observability includes the first 100 GB-months of storage and first 50M metric samples.
Per-second billing on NVIDIA accelerators, from T4 at $0.35/GPU-hour to B200 at $7.93/GPU-hour, subject to availability.
The company says it offers a generous free trial and provides a free private image registry; trial duration is arranged with sales.
Target Markets
- Startups, enterprises and government organizations
- SaaS and high-traffic web applications
- AI-native companies and ML/GPU users
- FinTech, healthcare, education, cybersecurity, legal technology and e-commerce
- Platform engineering, DevOps and SRE teams
- Organizations operating multi-cloud, hybrid, on-premises or edge infrastructure
- Deploying and operating AI-native applications and coding/research agents
- Multi-cloud and hybrid-cloud application deployment
- Managed Kubernetes without building a platform team
- GPU and ML inference workloads
- High-availability, low-latency and disaster-recovery architectures
- Cloud-cost reduction through right-sizing and workload placement
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