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CoreWeave
CoreWeave is a full-stack AI-native cloud platform and the Essential Cloud for AI. It provides GPU compute, purpose-built storage, and high-performance...
CoreWeave
CoreWeave is a full-stack AI-native cloud platform and the Essential Cloud for AI. It provides GPU compute, purpose-built storage, and high-performance networking for AI training and inference through a Kubernetes-native environment. The company delivers bare-metal infrastructure, managed software services, and early access to NVIDIA GPUs for AI labs, platforms, and enterprises.
General information
Firm type
Asset Manager
Location
Region
North America
Country
United States
City
Livingston
Corporate office
Roseland, NJ, United States
Principals
Mike Intrator
Chief Executive Officer, Co-founder
Brian Venturo
Chief Strategy Officer, Co-founder
Brannin McBee
Chief Development Officer, Co-founder
Peter Salanki
Chief Technology Officer, Co-founder
Nitin Agrawal
Chief Financial Officer
Chen Goldberg
Executive Vice President, Product & Engineering
Sachin Jain
Chief Operating Officer
Michelle O'Rourke
Chief People Officer
Kristen McVeety
General Counsel
Max Hjelm
Executive Vice President, Strategic Deals
Jean English
Chief Marketing Officer
Sandy Venugopal
Chief Information Officer
James Higgins
Chief Information Security Officer
Jeff Baker
Chief Accounting Officer
Jon Jones
Chief Revenue Officer
Brian Venturo
Chief Strategy Officer, Co-founder; board member since April 2019
Brannin McBee
Chief Development Officer, Co-founder since March 2024
Sector focus
Frequently asked questions
Who are CoreWeave's largest known customers?
CoreWeave's publicly disclosed customers include OpenAI, Mistral AI, and IBM, all of which have provided testimonials on CoreWeave's website. OpenAI CEO Sam Altman has described CoreWeave as one of the lab's earliest and largest compute partners, helping build training clusters for models. Mistral AI credited CoreWeave with cutting training time in half for its open-source reasoning models. IBM reported accelerating its Granite model workloads by up to 80% using CoreWeave infrastructure. The firm also serves companies like McDonald's for interactive experiences, but does not disclose its full customer list.
How does CoreWeave's infrastructure differ from AWS, Azure, or Google Cloud?
CoreWeave operates a Kubernetes-native, bare-metal cloud platform built specifically for AI workloads — rather than offering general-purpose cloud services. The firm provides early access to NVIDIA GPUs, automated provisioning, and node lifecycle management optimized for training and inference at scale. CoreWeave claims up to 96% goodput, meaning fewer interruptions and higher cluster utilization than typical hyperscaler environments. Unlike hyperscalers, CoreWeave does not offer a broad range of SaaS products or legacy enterprise services; its stack is purpose-built for AI compute, storage, and networking.
What GPU hardware does CoreWeave offer access to?
CoreWeave's platform emphasizes early access to NVIDIA GPUs, though the firm does not publicly list specific hardware generations on its website. Customer testimonials reference 'cutting-edge hardware' and the firm markets its ability to deliver next-generation GPUs ahead of broad availability. CoreWeave's documented customer results — including 2.5x training speed improvements and 3x faster inference serving — are tied to high-performance NVIDIA GPU clusters configured through its bare-metal Kubernetes environment.
Does CoreWeave take equity stakes in its AI customers?
There is no public evidence that CoreWeave takes equity positions in its customers. The firm operates as an infrastructure provider offering GPU cloud services on a commercial basis. Its disclosed relationships with OpenAI, Mistral AI, and IBM are framed as customer-supplier arrangements rather than investment partnerships. CoreWeave has not disclosed any venture capital or investment activities.
Profile maintained by Altss using OSINT (open-source intelligence), regulatory filings, licensed data partners, and verified direct submissions. Read the methodology. Last updated: . Continuous refresh with full update cycles at least every 30 days.
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