Research Note: Coreweave
Executive Summary
CoreWeave has rapidly emerged as a specialized AI infrastructure provider delivering cloud services optimized specifically for GPU-intensive workloads in the exploding artificial intelligence market. The company has strategically positioned itself as "The AI Hyperscaler™" by developing a cloud platform designed from the ground up for AI model training and inference, while traditional cloud providers remain encumbered by legacy architectures optimized for web-scale applications. CoreWeave's recent $11.9 billion partnership with OpenAI firmly establishes it as a critical infrastructure provider in the AI ecosystem, complementing its existing relationships with major technology players like Microsoft and Nvidia. The company's technical architecture based on bare-metal Kubernetes infrastructure eliminates traditional virtualization overhead, enabling performance improvements of up to 20% over traditional cloud providers while delivering cost efficiencies of 35-80%. CoreWeave has demonstrated exceptional growth with revenue increasing nearly 8.4x from $228.9 million in 2023 to $1.92 billion in 2024, reflecting both the explosive demand for AI infrastructure and the company's ability to execute at scale. While the company's significant debt and historic dependence on Microsoft present potential risks, CoreWeave's expanding customer base, strategic positioning, and continued infrastructure expansion suggest sustained growth potential as the AI GPU cloud market is projected to surge from approximately $6.4 billion in 2023 to over $30 billion by 2032.
Corporate Overview
CoreWeave originated as a cryptocurrency mining operation called Atlantic Crypto, founded in 2017 by three former commodities traders - Michael Intrator, Brian Venturo, and Brannin McBee, along with Peter Salanki. The company pivoted from cryptocurrency mining to specialized cloud computing during the 2018-2019 crypto market downturn, leveraging its substantial inventory of graphics processing units (GPUs) to capitalize on emerging demand for high-performance computing. CoreWeave is headquartered at 290 West Mt Pleasant Avenue in Livingston, New Jersey, with additional offices in Roseland, New Jersey, Bellevue, Washington, New York City, Philadelphia, and Sunnyvale, California. The company maintains a distributed workforce with employees across North America, Europe, and Asia, supporting its growing global footprint of data centers. The founders' backgrounds in commodities trading provided them with expertise in managing high-value physical assets and optimizing operations for maximum returns - skills that translated effectively to building and operating GPU-intensive data centers at scale.
CoreWeave has demonstrated remarkable fundraising capabilities, having raised over $14.5 billion across debt and equity financings to fuel its rapid expansion. Major investments include Nvidia's $100 million strategic investment in April 2023, a $2.3 billion debt financing led by Magnetar Capital and Blackstone in August 2023, a $642 million funding round led by Fidelity Management & Research Company in December 2023, and a $1.1 billion Series C round in May 2024 that valued the company at $19 billion. In March 2025, CoreWeave completed its initial public offering on the Nasdaq under the symbol "CRWV," raising $1.5 billion despite reducing its IPO size from $2.7 billion. The company's post-IPO valuation stands at approximately $23 billion, making it one of the most valuable AI infrastructure startups in the world. CoreWeave's financial trajectory shows explosive growth, with revenue increasing from $228.9 million in 2023 to $1.92 billion in 2024, though this was accompanied by an expanded net loss of $863.4 million in 2024 compared to $593.7 million in 2023, reflecting the company's significant investments in infrastructure.
CoreWeave has significantly expanded its global footprint, opening its European headquarters in London in 2024 along with two UK data centers in Crawley and London Docklands that began operations in late 2024. The company recently announced a $2.2 billion investment to establish three new data centers in Norway, Sweden, and Spain by the end of 2025, bringing its total European investment to $3.5 billion. CEO Michael Intrator described Europe as "the next frontier for the AI industry," emphasizing the strategic importance of establishing a European presence with facilities designed to meet regional regulatory and operational demands while ensuring data sovereignty for European customers. All new European data centers will be powered by 100% renewable energy, reflecting the company's commitment to sustainable infrastructure development. This international expansion is part of CoreWeave's vision to become "the global AI hyperscaler of choice," positioning the company to serve multinational enterprises and AI developers with consistent infrastructure across geographies.
Management Analysis
CoreWeave's executive leadership combines deep expertise in commodities trading, infrastructure management, and cloud computing, bringing complementary skills to the company's rapid growth phase. CEO and co-founder Michael Intrator leads the company's strategic direction and has effectively transitioned the organization from its cryptocurrency mining origins to its current position as a leading AI infrastructure provider. The executive team's stability has been a notable strength, with the original founding team maintaining key leadership positions while strategically expanding the leadership bench to support scale. Co-founder Brian Venturo serves as Chief Strategy Officer, focusing on long-term growth initiatives, while fellow co-founder Brannin McBee operates as Chief Development Officer, overseeing infrastructure expansion and customer solutions. The technical foundation of the company is guided by co-founder Peter Salanki, who serves as Chief Technology Officer and directs CoreWeave's cloud platform architecture and engineering efforts.
The company has strategically augmented its founding team with experienced executives from leading technology companies to support its rapid growth trajectory. In March 2024, CoreWeave appointed Nitin Agrawal as Chief Financial Officer, bringing valuable experience from his previous roles as Vice President of Finance at Google Cloud and CFO of Amazon Web Services' Compute Services division. The company has also recruited Chetan Kapoor from Amazon Web Services as Chief Product Officer and Sachin Jain as Chief Operating Officer, who previously led AI infrastructure and IaaS products at Oracle Cloud. This blend of founding vision and external enterprise expertise has enabled CoreWeave to maintain its entrepreneurial culture while developing the operational discipline needed to support large-scale enterprise customers and navigate public markets. The management team's success in scaling from three data centers in 2022 to 32 data centers by early 2025 demonstrates their exceptional execution capabilities in a capital-intensive and technically complex industry.
Market Analysis
The global cloud GPU market represents an extraordinary growth opportunity, projected to expand from approximately $3.2 billion in 2023 to over $47 billion by 2032, reflecting a compound annual growth rate (CAGR) of 35.0%. This substantial market growth is being driven primarily by the surge in artificial intelligence applications, with enterprises across industries implementing machine learning and deep learning solutions that require massive computing resources. The GPU as a Service (GPUaaS) segment, which CoreWeave specifically targets, was valued at $6.4 billion in 2023 and is forecast to grow at a CAGR of over 30% through 2032. The broader AI infrastructure market is expected to reach $223.85 billion by 2029, growing at a 31.9% CAGR, as organizations worldwide invest heavily in the foundational technologies needed to develop and deploy AI solutions. Market analysts highlight the increasing demand for high-performance computing (HPC) capabilities as a key driver, with AI training and inference workloads requiring unprecedented computational power.
CoreWeave's position within this rapidly expanding market is strategically focused on the highest growth segments requiring specialized infrastructure. The company holds a significant market share in the AI cloud infrastructure space, though exact figures are not publicly disclosed. Major competitors in this market include traditional cloud providers like Amazon Web Services, Microsoft Azure, and Google Cloud, as well as specialized GPU cloud providers such as Lambda and Crusoe. CoreWeave's competitive positioning centers on its purpose-built infrastructure that delivers superior performance and cost efficiency compared to general-purpose cloud platforms. While traditional cloud providers still dominate the broader market, CoreWeave's specialized focus on AI workloads has enabled it to capture significant business from leading AI developers. The North American region currently dominates the global cloud GPU market with a share of approximately 40%, followed by Asia-Pacific at 30%, providing CoreWeave with a strong home market advantage as it continues to expand internationally.
The cloud GPU market is experiencing significant shifts in customer purchasing patterns, with enterprises increasingly valuing specialized infrastructure that delivers optimal performance for AI workloads rather than just raw computing capacity. The market is also seeing growing demand for hybrid deployment models that combine on-premises GPU infrastructure with cloud-based resources, providing flexibility and cost optimization. CoreWeave benefits from several structural advantages in this evolving market, including its close relationship with Nvidia, which gives it preferential access to the latest GPU technologies. Market forecasts suggest that demand for AI infrastructure will continue to outstrip supply for the next 3-5 years, creating favorable pricing conditions for providers like CoreWeave. Industry analysts project that global AI-related data center investments will push total infrastructure spending to $1 trillion by 2028, representing a 24% CAGR in the data center market over the next five years.
CoreWeave has secured significant customer commitments that provide a stable foundation for future growth. Microsoft represented approximately 62% of the company's revenue in 2024, though this concentration is likely to decrease following CoreWeave's strategic $11.9 billion, five-year agreement with OpenAI announced in March 2025. This diversification of major customers reduces CoreWeave's dependence on any single client while maintaining relationships with the industry's most demanding AI developers. The company's success in landing contracts with both Microsoft and OpenAI positions it advantageously within the competitive AI ecosystem, as these two companies represent the leading forces in commercial AI development. The broader market trend toward practical AI applications across industries from healthcare to financial services to automotive suggests continued strong demand for the high-performance GPU infrastructure that CoreWeave provides, with particular growth expected in inference workloads as more AI models move into production.
Product Analysis
CoreWeave's core product offering is its specialized cloud platform optimized for GPU-intensive workloads, with a particular focus on AI model training and inference. The company provides a comprehensive suite of infrastructure services including GPU compute, CPU compute, storage, and networking, all delivered through a Kubernetes-native architecture that eliminates traditional virtualization overhead. CoreWeave's compute offerings include access to various NVIDIA GPU models including H100, H200, A100, A6000, and the latest Blackwell architecture chips, with the company being among the first cloud providers to offer NVIDIA's GB200 NVL72-based instances. This diverse GPU portfolio enables customers to match their computational resources precisely to their workload requirements, optimizing both performance and cost efficiency. CoreWeave differentiates itself by providing bare-metal access to these GPUs rather than virtualized instances, delivering up to 20% higher performance compared to traditional cloud providers for complex AI workloads.
CoreWeave's platform includes several key software components that enhance its value proposition beyond raw compute capacity. At the foundation is the CoreWeave Kubernetes Service (CKS), which provides fully managed Kubernetes clusters with pre-installed components such as network interfaces, storage interfaces, GPU drivers, and monitoring tools. The platform incorporates software like Tensorizer for efficient model loading and SUNK (Slurm on Kubernetes for Training) that combines high-performance computing job scheduling with containerized workloads. CoreWeave AI Object Storage delivers data transfer speeds of up to 2GB per second per GPU across hundreds of thousands of GPUs, reducing the impact of data transfers on model performance. The company's Mission Control software provides customers with comprehensive visibility into infrastructure health and performance through managed Grafana dashboards that monitor metrics like Infiniband bandwidth, GPU temperature, and power consumption. Competitors in this space include Amazon Web Services, Microsoft Azure, Google Cloud, Lambda, Oracle Cloud, and Crusoe, though CoreWeave maintains competitive advantages through its specialized architecture and Nvidia partnership.
The company's product portfolio has been significantly enhanced through its recent acquisition of Weights & Biases, a leading AI developer platform used by over 1 million AI engineers across 1,400 organizations including OpenAI, Meta, NVIDIA, and AstraZeneca. This strategic $1.7 billion acquisition, completed in May 2025, extends CoreWeave's capabilities beyond pure infrastructure to include comprehensive tools for AI model training, evaluation, and monitoring. The integration creates an end-to-end platform that combines CoreWeave's high-performance infrastructure with Weights & Biases' specialized MLOps and LLMOps capabilities, enabling customers to accelerate their AI development cycles from initial experimentation through production deployment. Notable features from the Weights & Biases platform include advanced experiment tracking, model optimization, workflow automation, and specialized tools for fixing model hallucinations. CoreWeave has emphasized that Weights & Biases customers will maintain deployment flexibility, with no requirement to use CoreWeave's cloud infrastructure, though the integration will enable enhanced capabilities for those who choose the combined solution.
CoreWeave's product development roadmap emphasizes continued enhancement of performance, reliability, and ease of use for AI workloads. The platform's technical architecture is designed to support both the training phase, where models learn from large datasets, and the inference phase, where trained models generate predictions from user inputs. CoreWeave has focused particular attention on maximizing Model FLOPS Utilization (MFU), a key metric for AI workload efficiency, achieving up to 48.5% MFU compared to approximately 40.4% from alternative solutions. This 20% performance advantage translates directly to faster training times and lower costs for customers. The company's expanded product portfolio now addresses a broader range of AI use cases beyond large language models, including computer vision applications, multimodal AI systems, and specialized vertical applications in industries like healthcare, financial services, and manufacturing. This diversification positions CoreWeave to capture value across the evolving AI application landscape as organizations move beyond general-purpose models to more specialized implementations tailored to specific business requirements.
Technical Architecture
CoreWeave's technical architecture is built on a Kubernetes-native foundation that eliminates traditional virtualization overhead, enabling direct access to hardware resources for maximum performance. The company's infrastructure stack starts with high-density bare-metal servers housed in strategically located data centers, connected by high-performance networking using technologies like Infiniband and RDMA (Remote Direct Memory Access). CoreWeave leverages Nvidia's GPUDirect RDMA technology to accelerate data transfers between GPUs, bypassing the host server's operating system and central processing unit to reduce latency. This architecture enables data transfer directly between GPU memory and storage or network devices, significantly improving performance for data-intensive AI workloads. The company maintains 32 data centers across the United States and Europe, housing over 250,000 Nvidia GPUs with access to more than 260MW of active power, making it competitive with established hyperscalers despite its relative youth.
The CoreWeave Cloud Platform employs a layered architecture that combines cloud flexibility with HPC performance. Virtual private cloud network provisioning provides secure multi-tenancy, while managed Kubernetes enables containerized applications. The platform includes specialized services for AI workloads, such as inference optimization and Tensorizer for efficient model loading. A distinguishing feature is the implementation of Slurm on Kubernetes (SUNK), which allows the popular HPC job scheduler to run atop Kubernetes, enabling multiple AI jobs with different priorities to run side-by-side while maintaining optimal resource utilization. CoreWeave's approach to cluster management includes extensive automated validation, proactive health checking, and intelligent monitoring that identifies and removes problematic nodes before they disrupt workloads. The platform provides exceptional observability through real-time insights into GPU metrics and system performance, complemented by automated recovery processes that minimize downtime.
CoreWeave's architecture incorporates several innovative approaches to overcome common limitations in traditional cloud environments. The company's infrastructure is designed to deliver consistently high performance for AI workloads, achieving up to 96% "goodput" (the proportion of processing power effectively utilized for productive work). This performance consistency is critical for AI workloads where interruptions can invalidate days or weeks of training progress. The company's storage architecture features CoreWeave AI Object Storage that provides up to 2GB per second per GPU data transfer speeds across hundreds of thousands of GPUs, reducing the impact of data transfers on model performance. Network architecture employs dedicated high-speed interconnects between compute nodes, optimized for the massive data movement requirements of distributed AI training workloads. The platform's scale-to-zero capabilities, enabled by Google's Knative Kubernetes extension, allow customers to completely shut down GPU clusters when not in use, eliminating idle resources and reducing costs while maintaining rapid reactivation capabilities.
Strengths
CoreWeave's primary competitive advantage lies in its purpose-built infrastructure optimized specifically for GPU-intensive AI workloads. The company's Kubernetes-native architecture eliminates the virtualization overhead found in traditional cloud environments, delivering up to 20% higher performance for AI workloads compared to general-purpose cloud providers. This performance advantage translates directly to faster training times, more efficient inference, and lower total costs for customers deploying complex AI models. Independent benchmark tests have confirmed these performance gains, with CoreWeave achieving an optimized Model FLOPS Utilization (MFU) of 48.5% for Llama 3.1 training compared to approximately 40.4% from alternative solutions. The company's bare-metal approach and advanced storage and networking infrastructure enable it to deliver consistent performance at scale, with minimal interruptions that could invalidate lengthy AI training runs. These technical advantages are particularly valuable for leading AI labs and enterprises developing cutting-edge models that require maximum computational efficiency.
CoreWeave has secured an enviable position within the AI ecosystem through strategic partnerships with key technology leaders. The company's relationship with Nvidia provides preferential access to the latest GPU technologies, allowing CoreWeave to be among the first cloud providers to offer advancements like the GB200 NVL72 chips. Major customer relationships with AI leaders like Microsoft and OpenAI validate CoreWeave's technology and create a virtuous cycle of continuous improvement as the company addresses the needs of the most demanding AI workloads. The $11.9 billion, five-year agreement with OpenAI announced in March 2025 not only provides substantial contracted revenue but also establishes CoreWeave as a critical infrastructure provider for one of the world's leading AI research organizations. The company's ability to secure these partnerships demonstrates both its technical capabilities and its operational reliability. CoreWeave's recent acquisition of Weights & Biases further strengthens its product offering, expanding from pure infrastructure to include enhanced tools for model management, evaluation, and monitoring.
The acquisition of Weights & Biases creates significant new strengths for CoreWeave by transforming it from a pure infrastructure provider to an end-to-end AI platform company. This strategic move enhances the company's value proposition by integrating software tools for the entire AI development lifecycle with its high-performance infrastructure, creating a more comprehensive solution for AI builders. The acquisition brings CoreWeave closer to AI developers and expands its potential market beyond infrastructure procurement to include the rapidly growing MLOps and LLMOps segments. Weights & Biases' established customer base of over 1,400 organizations, including marquee names like OpenAI, Meta, NVIDIA, and AstraZeneca, provides CoreWeave with relationships across the AI ecosystem and opportunities for cross-selling. The combined platform enables customers to accelerate their AI development cycles with a seamless workflow from initial experimentation through production deployment, addressing key challenges in model training, optimization, and monitoring. This integrated approach positions CoreWeave to capture more value in the AI stack and differentiate itself from pure infrastructure providers.
CoreWeave has demonstrated exceptional execution capabilities in a capital-intensive and technically complex industry. The company's expansion from three data centers in 2022 to 32 data centers with over 250,000 GPUs by early 2025 represents an unprecedented pace of infrastructure deployment. This rapid scaling has been supported by innovative financing approaches, including using GPUs as collateral for debt financing, that have enabled CoreWeave to build infrastructure ahead of competition. The company's revenue growth from $228.9 million in 2023 to $1.92 billion in 2024 reflects both market demand and CoreWeave's ability to convert that demand into contracted business. The management team has shown strategic foresight in pivoting from cryptocurrency mining to AI infrastructure, positioning the company at the forefront of one of technology's fastest-growing markets. CoreWeave's successful IPO in March 2025, raising $1.5 billion despite challenging market conditions, provides additional capital to fund continued growth and demonstrates investor confidence in the company's business model and market opportunity.
Weaknesses
CoreWeave's most significant vulnerability lies in its customer concentration, with Microsoft accounting for approximately 62% of the company's revenue in 2024. While the recent $11.9 billion agreement with OpenAI will help diversify this concentration, the company remains heavily dependent on a small number of large customers. This concentration creates substantial risk if any major customer were to shift spending to alternative providers or develop their own infrastructure. The competitive landscape is intensifying as traditional cloud providers like AWS, Google Cloud, and Microsoft Azure continue to expand their specialized GPU offerings, potentially eroding CoreWeave's performance advantages over time. These larger competitors have significantly greater financial resources, established enterprise relationships, and broader service portfolios that could challenge CoreWeave's position as the GPU market matures. Additionally, new specialized providers continue to enter the market, including well-funded startups like Lambda and Crusoe that employ similar business models targeting AI infrastructure.
CoreWeave's financial position presents potential concerns despite its impressive revenue growth. The company reported a net loss of $863.4 million in 2024, wider than its $593.7 million loss in 2023, reflecting the significant capital investments required to build and operate data centers at scale. CoreWeave carries substantial debt, with approximately $7.9 billion on its balance sheet according to its IPO filing, creating financial leverage that could become problematic if market conditions deteriorate. The company's business model requires continuous capital investment to maintain technological leadership and expand capacity, creating ongoing funding requirements that must be balanced against profitability goals. While CoreWeave's contracted revenue provides visibility into future cash flows, the company faces the challenge of managing depreciation schedules for its GPU assets against potential technological obsolescence as newer, more powerful chips are introduced at an accelerating pace. If GPU pricing declines faster than anticipated or customer demand shifts, CoreWeave could face challenges in achieving positive returns on its infrastructure investments.
CoreWeave's rapid growth presents operational challenges that could impact its ability to maintain service quality and customer satisfaction. The company's expansion from a small cryptocurrency mining operation to a major cloud infrastructure provider has required significant organizational scaling in a short timeframe. Maintaining operational excellence across 32 data centers while continuing to add new facilities requires sophisticated management systems and experienced technical personnel, both of which are in high demand across the industry. The company faces execution risks in its international expansion plans, including regulatory complexities, power availability constraints, and hiring challenges in new markets. CoreWeave's specialized focus on GPU infrastructure creates potential vulnerability to shifts in AI development approaches, such as the emergence of alternative acceleration technologies or more efficient software approaches that reduce computational requirements. While the company has successfully navigated its growth to date, maintaining the same execution quality at an ever-larger scale will require continuous improvement in operational processes and organizational capabilities.
Client Voice
CoreWeave's customers consistently highlight the platform's performance advantages for demanding AI workloads as a primary driver of adoption. Leading AI research organizations report that CoreWeave's architecture delivers measurably faster training times and more consistent performance compared to traditional cloud providers, with documented improvements of up to 20% in Model FLOPS Utilization (MFU). Mistral AI, a prominent customer, noted that the performance and reliability they've experienced from CoreWeave clusters have been exceptional, enabling them to deliver cutting-edge models quickly. The company emphasized the close partnership with CoreWeave's technical team, describing it as "like having an extension of our own team on the infrastructure side." This collaborative approach to customer relationships emerges as a consistent theme, with clients valuing CoreWeave's willingness to work directly with their technical teams to optimize infrastructure for specific workloads. Customers appreciate the company's deep understanding of AI workload requirements and its expertise in designing and operating high-performance GPU clusters at scale.
Performance improvements translate directly to business benefits for CoreWeave's customers, with several reporting significant cost savings alongside capability enhancements. One client in the generative AI space reported being able to serve requests three times faster after migrating to CoreWeave while simultaneously reducing cloud costs by 75%. These efficiency gains enable AI companies to improve user experience through faster response times while managing the substantial computational costs associated with serving AI models. Enterprise customers value CoreWeave's ability to rapidly scale infrastructure in response to demand spikes, with one reporting the ability to "scale up extremely fast when there is more demand." This elasticity is particularly valuable in the rapidly evolving AI market, where new model releases or application launches can create sudden increases in resource requirements. Customers also note CoreWeave's early access to the latest GPU technologies as a competitive advantage, allowing them to leverage advancements like NVIDIA's Blackwell architecture before they become widely available on other cloud platforms.
Implementation experiences vary based on customer requirements, but clients generally report smooth onboarding processes supported by CoreWeave's technical expertise. Organizations migrating from traditional cloud providers value CoreWeave's assistance in optimizing their workloads for the new infrastructure environment, though some note initial challenges in adapting their deployment pipelines. Customers with experience using both CoreWeave and traditional cloud providers consistently cite CoreWeave's superior price-performance ratio for GPU-intensive workloads, with several reporting 30-50% lower total costs for equivalent computational tasks. Clients also appreciate the platform's observability features, which provide detailed insights into GPU utilization, power consumption, and other performance metrics through pre-built dashboards and monitoring tools. While some customers note that CoreWeave's specialized focus means they still need to maintain relationships with general-purpose cloud providers for non-GPU workloads, they value the platform's interoperability with these environments and its ability to integrate into multi-cloud architectures.
Bottom Line
Organizations developing and deploying compute-intensive AI applications should consider CoreWeave as their primary infrastructure provider for GPU-intensive workloads, particularly those requiring maximum performance efficiency and cost optimization. Companies actively involved in AI model training and inference, especially those working with large language models, computer vision systems, or multimodal AI applications, will benefit most significantly from CoreWeave's architecture advantages and specialized expertise. Chief Information Officers and AI leaders should evaluate CoreWeave when current cloud providers cannot deliver sufficient GPU capacity, consistent performance, or cost efficiency for expanding AI initiatives. The company is particularly well-suited for organizations that require early access to cutting-edge GPU technologies and can benefit from close collaboration with infrastructure experts who understand the unique requirements of AI workloads. With the addition of Weights & Biases' MLOps and LLMOps capabilities, CoreWeave now offers an attractive end-to-end platform for organizations seeking to accelerate their AI development cycles from initial experimentation through production deployment.
Successful implementation of CoreWeave's platform requires thoughtful integration into broader cloud strategies, with attention to workload placement optimization across traditional cloud providers and specialized infrastructure. Organizations should plan for dedicated technical resources to manage the transition and ongoing operations, though these requirements are typically lighter than building equivalent on-premises GPU infrastructure. Potential customers should also conduct thorough performance benchmarking of their specific workloads to quantify the advantages CoreWeave can deliver, using these metrics to build compelling business cases based on both cost savings and capability enhancements. Chief Technology Officers should prepare for potential organizational resistance by educating teams on the benefits of specialized infrastructure and addressing concerns about vendor lock-in through clear architectural guidelines. By strategically leveraging CoreWeave's performance advantages for appropriate workloads while maintaining relationships with general-purpose cloud providers for other needs, organizations can optimize their infrastructure for the AI era while maintaining flexibility for future evolution.