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CoreWeave Product

To democratize high-performance computing by building the world's most powerful and accessible GPU cloud infrastructure for AI innovation

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To democratize high-performance computing by building the world's most powerful and accessible GPU cloud infrastructure for AI innovation

Strengths

  • INFRASTRUCTURE: Industry-leading GPU cloud architecture with 10K+ NVIDIA H100s deployed
  • SCALABILITY: Vertical integration enables 5x faster deployment than competitors
  • EFFICIENCY: 35% lower TCO through proprietary cooling and power optimization
  • PARTNERSHIPS: Strategic NVIDIA preferred partner status with priority allocations
  • EXPERTISE: Deep technical bench with specialists in AI infrastructure optimization

Weaknesses

  • GEOGRAPHIC: Limited data center footprint outside North America region
  • BRAND: Lower market awareness compared to hyperscaler cloud providers
  • ENTERPRISE: Underdeveloped enterprise sales motion and support infrastructure
  • PRODUCT: Limited software layer differentiation beyond raw infrastructure
  • TALENT: Challenges attracting AI/ML product experts in competitive market

Opportunities

  • DEMAND: AI computing demand exceeding supply by 3x through 2026
  • SPECIALIZED: Growing need for domain-specific GPU infrastructure solutions
  • EXPANSION: International market entry opportunities, particularly in EMEA/APAC
  • SOFTWARE: Development of proprietary middleware for AI deployment efficiency
  • STARTUPS: Dedicated program to capture emerging AI startup market share

Threats

  • COMPETITION: Hyperscalers expanding dedicated AI infrastructure offerings
  • SUPPLY: Ongoing industry-wide GPU supply constraints through 2026
  • TECHNOLOGY: Potential emergence of alternative AI acceleration technologies
  • REGULATION: Growing data sovereignty and AI regulatory requirements
  • ECONOMIC: Enterprise AI spending sensitivity to macroeconomic conditions

Key Priorities

  • PRODUCT: Develop differentiated software/middleware layers beyond hardware
  • EXPANSION: Accelerate international data center footprint development
  • ENTERPRISE: Build robust enterprise GTM motion and support systems
  • SPECIALIZATION: Create industry-specific AI infrastructure solutions
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To democratize high-performance computing by building the world's most powerful and accessible GPU cloud infrastructure for AI innovation

BUILD THE PLATFORM

Create a comprehensive AI development ecosystem

  • FOUNDATION: Launch CoreWeave AI Platform beta with unified deployment tools for 250+ early users
  • OPTIMIZATION: Develop proprietary GPU utilization enhancement middleware with 15%+ performance gains
  • INTEGRATION: Establish seamless integration with 5 leading MLOps and AI development frameworks
  • EXPERIENCE: Achieve 85%+ positive feedback rating from platform beta users on core functionality
GLOBAL REACH

Expand international infrastructure footprint

  • EMEA: Complete Frankfurt data center with 2000+ H100 GPUs and achieve 60% pre-launch commitment
  • APAC: Finalize Singapore facility construction and begin equipment installation for Q3 launch
  • LATENCY: Establish global network backbone with <80ms latency between all regional data centers
  • COMPLIANCE: Implement comprehensive data sovereignty framework meeting requirements in 12 regions
ENTERPRISE GROWTH

Build robust enterprise acquisition capability

  • TEAM: Expand enterprise sales organization to 45 professionals with industry-specific expertise
  • PROCESS: Implement structured enterprise sales methodology with 35% improvement in close rates
  • SUPPORT: Launch 24/7 enterprise support operations with guaranteed 15-minute response SLA
  • SECURITY: Complete SOC 2 Type II certification and achieve FedRAMP Ready status for public sector
INDUSTRY FOCUS

Develop vertical-specific AI solutions

  • FINANCIAL: Launch financial services AI reference architecture with 2 tier-1 bank pilot customers
  • HEALTHCARE: Develop HIPAA-compliant medical imaging AI infrastructure solution with research partner
  • MANUFACTURING: Create industrial AI blueprint achieving 30% training efficiency for vision systems
  • MEDIA: Establish specialized rendering and generative content creation infrastructure for studios
METRICS
  • GPU Utilization Rate: 87% by Q4 2025 (from current 81%)
  • Net Revenue Retention: 135% across all customer segments
  • Enterprise Customer Count: 75 Fortune 1000 companies (from current 42)
VALUES
  • Performance Excellence - We relentlessly pursue technological superiority
  • Customer Obsession - We build for real customer needs and measure success by their achievements
  • Sustainable Innovation - We develop solutions that maximize computational efficiency while minimizing environmental impact
  • Agility & Adaptability - We embrace change and rapidly evolve our offerings to meet emerging market demands
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Align the learnings

CoreWeave Product Retrospective

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To democratize high-performance computing by building the world's most powerful and accessible GPU cloud infrastructure for AI innovation

What Went Well

  • GROWTH: Revenue increased 112% YoY, exceeding analyst expectations by 18%
  • DEPLOYMENT: Successfully installed 2,800+ H100 GPUs ahead of projected timeline
  • PARTNERSHIPS: Secured 3 major strategic agreements with leading AI startups
  • EFFICIENCY: Improved power usage effectiveness (PUE) from 1.12 to 1.08 across
  • RETENTION: Achieved 96% customer retention rate while expanding service scope

Not So Well

  • MARGINS: Gross margin declined 2.3 percentage points due to expansion costs
  • INTERNATIONAL: EMEA data center launch delayed by 47 days due to permit issues
  • ENTERPRISE: Large enterprise deal closure rate at 28% vs. 35% target benchmark
  • TALENT: Engineering team growth at 68% of target due to competitive market
  • SOFTWARE: AI platform product roadmap execution behind schedule by 6+ weeks

Learnings

  • INTEGRATION: Vertical integration strategy providing 32% deployment advantage
  • SEGMENTATION: Mid-market AI companies showing 2.1x higher growth than expected
  • OPTIMIZATION: Customer-specific infrastructure configurations yielding 38% ROI
  • EFFICIENCY: Cooling optimization initiatives delivering 14% power cost savings
  • FORECASTING: Improved demand prediction model accuracy from 72% to 89% precise

Action Items

  • PLATFORM: Accelerate AI software platform development with 15 new engineers
  • EXPANSION: Finalize EMEA and APAC data center locations with 5000+ GPU capacity
  • ENTERPRISE: Implement structured enterprise sales methodology with new hires
  • SPECIALIZATION: Develop 4 industry-specific AI solution reference architectures
  • AUTOMATION: Launch self-service GPU infrastructure provisioning portal by Q3
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To democratize high-performance computing by building the world's most powerful and accessible GPU cloud infrastructure for AI innovation

Strengths

  • ARCHITECTURE: Purpose-built infrastructure optimized for LLM training/inference
  • EXPERTISE: Deep technical knowledge in NVIDIA GPU optimization techniques
  • FLEXIBILITY: Ability to support diverse AI workloads from MLOps to rendering
  • PERFORMANCE: Demonstrated 30%+ improvement in LLM inference latency
  • ALLOCATION: Proprietary orchestration system for AI workload management

Weaknesses

  • TOOLS: Limited proprietary AI developer tooling and middleware offerings
  • SERVICES: Underdeveloped AI consulting and implementation services
  • SPECIALIZATION: Lack of industry-specific AI solution templates/frameworks
  • TALENT: Insufficient AI research partnerships to drive innovation agenda
  • BENCHMARKING: Inadequate standardized performance metrics for customers

Opportunities

  • PLATFORM: Develop comprehensive AI development/deployment platform
  • VERTICAL: Create industry-specific AI solution blueprints for key sectors
  • ECOSYSTEM: Build partner network for complementary AI software solutions
  • OPTIMIZATION: Proprietary software for maximizing GPU utilization for AI
  • AUTOMATION: AI-powered infrastructure self-optimization capabilities

Threats

  • DIFFERENTIATION: Commoditization of base GPU infrastructure services
  • PLATFORMS: Adoption of end-to-end AI platforms reducing infrastructure focus
  • EVOLUTION: Rapid changes in AI model architectures requiring adaptability
  • ALTERNATIVES: Growth of specialized AI chips beyond NVIDIA ecosystem
  • RETENTION: Customer migration to self-hosted solutions after prototyping

Key Priorities

  • PLATFORM: Develop comprehensive AI development/deployment platform
  • OPTIMIZATION: Create proprietary AI workload optimization software layer
  • VERTICAL: Build industry-specific AI solution templates and frameworks
  • ECOSYSTEM: Establish strategic AI software and services partner network