Product Code: SE 9531
The AI inference PaaS market is projected to reach USD 18.84 billion in 2025 and USD 105.22 billion by 2030, recording a CAGR of 41.1% during the forecast period. The market is witnessing strong growth fueled by the rising need for real-time decision-making and the increasing integration of AI inference with industry-specific SaaS platforms.
Scope of the Report |
Years Considered for the Study | 2021-2030 |
Base Year | 2024 |
Forecast Period | 2025-2030 |
Units Considered | Value (USD Million) |
Segments | By Deployment, Application, Vertical and Region |
Regions covered | North America, Europe, APAC, RoW |
Sectors such as finance, retail, and healthcare leverage real-time insights to improve fraud detection, customer engagement, and clinical decision support, driving adoption of scalable inference services. At the same time, embedding inference capabilities into SaaS offerings allows enterprises to unlock tailored AI solutions without heavy infrastructure investments. These trends are expanding the addressable market and positioning AI inference PaaS as a core enabler of digital transformation.
"Private cloud segment is projected to record the second-highest CAGR between 2025 and 2030"
The private cloud segment is expected to grow at the second-highest CAGR in the AI inference PaaS market during the forecast period, driven by the increasing demand for data security, compliance, and customized infrastructure among enterprises. Sectors such as BFSI, healthcare, and government prioritize private cloud deployments due to strict regulatory frameworks and the data sensitivity involved. AI inference on private clouds allows organizations to retain full control over data, reduce latency, and achieve high performance with dedicated resources. Vendors are responding with hybrid and private cloud offerings that combine scalability with governance, enabling enterprises to deploy large language models (LLMs) and machine learning workloads securely. Moreover, the rising adoption of sovereign AI initiatives in Europe and Asia-Pacific further strengthens demand for private cloud-based inference platforms.
"Machine learning segment is expected to hold a major share of the AI inference PaaS market in 2025"
The machine learning segment is likely to account for a significant share of the AI inference PaaS market in 2025, driven by its widespread adoption across end-use industries, such as finance, healthcare, retail, and manufacturing. Enterprises increasingly leverage machine learning algorithms for predictive analytics, fraud detection, customer personalization, and operational optimization, creating steady demand for scalable inference solutions. The ability of PaaS offerings to support real-time inference, automated model deployment, and cost-efficient scalability makes them a preferred choice for machine learning applications. Furthermore, the availability of pre-trained models, APIs, and managed infrastructure on cloud platforms is lowering entry barriers for SMEs and startups.
"Europe is anticipated to hold a significant market share in 2025"
Europe is projected to hold a strong position in the AI inference PaaS market in 2025, supported by advanced digital infrastructure, rising adoption of AI technologies, and increasing investments in sovereign AI initiatives. Countries such as the UK, Germany, and France are leading in AI adoption across industries, particularly in BFSI, automotive, and healthcare. The emphasis on data privacy and compliance, especially under GDPR, shapes the demand for secure and localized inference platforms, with global players and regional cloud providers expanding offerings tailored to these requirements. Growth in Europe is also driven by significant investments in cloud infrastructure and partnerships between hyperscalers and European institutions. In May 2024, Amazon announced major investments to expand cloud operations and a European sovereign cloud project, directly enhancing local compute capacity and enabling enterprises to access compliant inference services within the region. This move reflects a broader trend of hyperscalers localizing infrastructure to address Europe's sovereignty concerns. Alongside Amazon, Microsoft Azure, and Google Cloud are strengthening their European presence, while local providers, such as OVHcloud and Deutsche Telekom, are capturing enterprises prioritizing domestic hosting and trusted AI deployment.
Extensive primary interviews were conducted with key industry experts in the AI inference PaaS market space to determine and verify the market size for various segments and subsegments gathered through secondary research. The breakdown of primary participants for the report is shown below.
The study contains insights from various industry experts, from component suppliers to Tier 1 companies and OEMs. The break-up of the primaries is as follows:
- By Company Type: Tier 1 - 50%, Tier 2 - 30%, and Tier 3 - 20%
- By Designation: C-level Executives - 20%, Directors - 30%, and Others - 50%
- By Region: North America - 40%, Europe - 20%, Asia Pacific- 30%, and RoW - 10%
The AI inference PaaS market is dominated by a few globally established players, such as Microsoft (US), Amazon Web Services, Inc. (US), Google Cloud (US), Oracle (US), IBM (US), Alibaba Cloud (China), Salesforce, Inc. (US), Tencent Cloud (China), Baidu, Inc. (China), Together AI (US), CoreWeave (US), Predibase (US), Vectara (US), Prem AI (US), and Baseten (China), among others. The study includes an in-depth competitive analysis of these key players in the AI inference PaaS market and their company profiles, recent developments, and key market strategies.
Research Coverage:
The report segments the AI inference PaaS market based on deployment (public cloud, private cloud, and hybrid cloud), application (generative AI, machine learning, natural language processing, and computer vision), and vertical (healthcare, BFSI, automotive, retail & e-commerce, media & entertainment, government & defense, IT & telecom, and other verticals). It also discusses the market's drivers, restraints, opportunities, and challenges. It gives a detailed view of the market across four main regions (North America, Europe, Asia Pacific, and RoW). The report includes an ecosystem analysis of key players.
Key Benefits of Buying the Report:
- Analysis of key drivers (surging adoption of generative AI and large language models, increasing preference for cloud-native AI architectures, rising need for real-time decision making), restraints (high cost of AI accelerators and service pricing volatility, vendor lock-in concerns, data privacy and regulatory restrictions), opportunities (availability of on-demand inference for SMEs and startups, rise in sovereign AI and regional cloud partnerships, integration of AI inference platforms with industry-specific SaaS solutions), challenges (latency and bandwidth issues in cloud-only setups, complexities in managing AI models in dynamic production environments)
- Service Development/Innovation: Detailed insights on upcoming technologies, research and development activities, and new launches in the AI inference PaaS market
- Market Development: Comprehensive information about lucrative markets through the analysis of the AI inference PaaS market across varied regions
- Market Diversification: Exhaustive information about new products and services, untapped geographies, recent developments, and investments in the AI inference PaaS market
- Competitive Assessment: In-depth assessment of market shares, growth strategies, and product offerings of leading players, such as Microsoft (US), Amazon Web Services, Inc. (US), Google Cloud (US), Oracle (US), IBM (US), Alibaba Cloud (China), Salesforce, Inc. (US), Tencent Cloud (China), Baidu, Inc. (China), and Together AI (US)
TABLE OF CONTENTS
1 INTRODUCTION
- 1.1 STUDY OBJECTIVES
- 1.2 MARKET DEFINITION
- 1.3 STUDY SCOPE
- 1.3.1 MARKETS COVERED AND REGIONAL SCOPE
- 1.3.2 INCLUSIONS AND EXCLUSIONS
- 1.3.3 YEARS CONSIDERED
- 1.4 CURRENCY CONSIDERED
- 1.5 LIMITATIONS
- 1.6 STAKEHOLDERS
2 RESEARCH METHODOLOGY
- 2.1 RESEARCH DATA
- 2.1.1 SECONDARY DATA
- 2.1.1.1 List of key secondary sources
- 2.1.1.2 Key data from secondary sources
- 2.1.2 PRIMARY DATA
- 2.1.2.1 List of primary interview participants
- 2.1.2.2 Breakdown of primaries
- 2.1.2.3 Key data from primary sources
- 2.1.2.4 Key industry insights
- 2.1.3 SECONDARY AND PRIMARY RESEARCH
- 2.2 MARKET SIZE ESTIMATION
- 2.2.1 BOTTOM-UP APPROACH
- 2.2.1.1 Approach to arrive at market size using bottom-up analysis (demand side)
- 2.2.2 TOP-DOWN APPROACH
- 2.2.2.1 Approach to arrive at market size using top-down analysis (supply side)
- 2.3 MARKET BREAKDOWN AND DATA TRIANGULATION
- 2.4 RESEARCH ASSUMPTIONS
- 2.5 RESEARCH LIMITATIONS
- 2.6 RISK ANALYSIS
3 EXECUTIVE SUMMARY
4 PREMIUM INSIGHTS
- 4.1 ATTRACTIVE OPPORTUNITIES FOR PLAYERS IN AI INFERENCE PAAS MARKET
- 4.2 AI INFERENCE PAAS MARKET, BY DEPLOYMENT AND APPLICATION
- 4.3 AI INFERENCE PAAS MARKET, BY VERTICAL
- 4.4 AI INFERENCE PAAS MARKET, BY GEOGRAPHY
5 MARKET OVERVIEW
- 5.1 INTRODUCTION
- 5.2 MARKET DYNAMICS
- 5.2.1 DRIVERS
- 5.2.1.1 Surging adoption of generative AI and large language models
- 5.2.1.2 Increasing preference for cloud-native AI architectures
- 5.2.1.3 Rising need for real-time decision making
- 5.2.2 RESTRAINTS
- 5.2.2.1 High cost of AI accelerators and service pricing volatility
- 5.2.2.2 Vendor lock-in concerns
- 5.2.2.3 Data privacy and regulatory restrictions
- 5.2.3 OPPORTUNITIES
- 5.2.3.1 Availability of on-demand inference for SMEs and startups
- 5.2.3.2 Rise in sovereign AI and regional cloud partnerships
- 5.2.3.3 Integration of AI inference platforms with industry-specific SaaS solutions
- 5.2.4 CHALLENGES
- 5.2.4.1 Latency and bandwidth issues in cloud-only setups
- 5.2.4.2 Complexities in managing AI models in dynamic production environments
- 5.3 TRENDS/DISRUPTIONS IMPACTING CUSTOMER BUSINESS
- 5.4 VALUE CHAIN ANALYSIS
- 5.5 ECOSYSTEM ANALYSIS
- 5.6 INVESTMENT AND FUNDING SCENARIO
- 5.7 PORTER'S FIVE FORCES ANALYSIS
- 5.7.1 INTENSITY OF COMPETITIVE RIVALRY
- 5.7.2 BARGAINING POWER OF SUPPLIERS
- 5.7.3 BARGAINING POWER OF BUYERS
- 5.7.4 THREAT OF SUBSTITUTES
- 5.7.5 THREAT OF NEW ENTRANTS
- 5.8 KEY STAKEHOLDERS AND BUYING CRITERIA
- 5.8.1 KEY STAKEHOLDERS IN BUYING PROCESS
- 5.8.2 BUYING CRITERIA
- 5.9 PATENT ANALYSIS
- 5.10 REGULATORY LANDSCAPE
- 5.10.1 REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
- 5.10.2 REGULATIONS
- 5.10.3 STANDARDS
- 5.11 PRICING ANALYSIS
- 5.11.1 PRICING RANGE OF AI INFERENCE PAAS OFFERED BY KEY PLAYERS, BY DEPLOYMENT, 2024
- 5.11.2 AVERAGE SELLING PRICE OF AI INFERENCE PAAS, BY APPLICATION, 2024
- 5.12 TECHNOLOGY ANALYSIS
- 5.12.1 KEY TECHNOLOGIES
- 5.12.1.1 Machine learning
- 5.12.1.2 Cloud computing
- 5.12.2 COMPLEMENTARY TECHNOLOGIES
- 5.12.2.1 Big data analytics
- 5.12.3 ADJACENT TECHNOLOGIES
- 5.12.3.1 High-performance computing (HPC)
- 5.13 CASE STUDY ANALYSIS
- 5.13.1 FORETHOUGHT OPTIMIZES AI INFERENCE AND SCALABILITY USING AWS SAGEMAKER
- 5.13.2 DOCUSIGN BOOSTS PRODUCTIVITY USING NVIDIA TRITON INFERENCE SERVER ON AZURE
- 5.13.3 SMEG UK LTD DELIVERS SMARTER CUSTOMER SERVICE THROUGH ORACLE GENERATIVE AI SOLUTIONS
- 5.13.4 CERN BUILDS LARGE-SCALE AI MODELS FOR SCIENTIFIC DISCOVERY USING OCI DATA SCIENCE
- 5.13.5 FIREWORKS AI BOOSTS AI MODEL PERFORMANCE WITH OCI AI INFRASTRUCTURE
- 5.14 KEY CONFERENCES AND EVENTS, 2025-2026
- 5.15 IMPACT OF 2025 US TARIFF ON AI INFERENCE PAAS MARKET
- 5.15.1 INTRODUCTION
- 5.15.2 PRICE IMPACT ANALYSIS
- 5.15.3 KEY TARIFF RATES
- 5.15.4 IMPACT ON COUNTRIES/REGIONS
- 5.15.4.1 US
- 5.15.4.2 Europe
- 5.15.4.3 Asia Pacific
- 5.15.5 IMPACT ON VERTICALS
6 AI INFERENCE PAAS MARKET, BY DEPLOYMENT
- 6.1 INTRODUCTION
- 6.2 PUBLIC CLOUD
- 6.2.1 RISING ADOPTION OF GEN AI AND LARGE LANGUAGE MODELS ACROSS INDUSTRIES TO ACCELERATE SEGMENTAL GROWTH
- 6.3 PRIVATE CLOUD
- 6.3.1 GROWING FOCUS ON ENTERPRISE CONTROL AND INTELLECTUAL PROPERTY PROTECTION TO FUEL SEGMENTAL GROWTH
- 6.4 HYBRID CLOUD
- 6.4.1 INCREASING COMPLEXITY OF AI WORKLOADS TO CONTRIBUTE TO SEGMENTAL GROWTH
7 AI INFERENCE PAAS MARKET, BY APPLICATION
- 7.1 INTRODUCTION
- 7.2 GENERATIVE AI
- 7.2.1 RULE-BASED MODELS
- 7.2.1.1 Strong focus on operational efficiency, governance, and regulatory compliance to bolster segmental growth
- 7.2.2 STATISTICAL MODELS
- 7.2.2.1 Increasing need for low-latency, real-time predictions to foster segmental growth
- 7.2.3 DEEP LEARNING
- 7.2.3.1 Rapid advances in hardware, optimized serving frameworks, and access to pre-trained models and repositories to drive market
- 7.2.4 GENERATIVE ADVERSARIAL NETWORKS (GANS)
- 7.2.4.1 Mounting demand for synthetic content, creative AI applications, and high-fidelity simulation environments to fuel segmental growth
- 7.2.5 AUTOENCODERS
- 7.2.5.1 Rise in fraud detection and cybersecurity use cases to boost segmental growth
- 7.2.6 CONVOLUTIONAL NEURAL NETWORKS (CNNS)
- 7.2.6.1 Increasing adoption of visual AI across industries to contribute to segmental growth
- 7.2.7 TRANSFORMER MODELS
- 7.2.7.1 Growing demand for contextual AI and LLM-based productivity tools to augment segmental growth
- 7.3 MACHINE LEARNING
- 7.3.1 INCREASING AVAILABILITY OF STRUCTURED AND UNSTRUCTURED DATA TO ACCELERATE SEGMENTAL GROWTH
- 7.4 NATURAL LANGUAGE PROCESSING
- 7.4.1 RISING ADOPTION OF CHATBOTS, VOICE ASSISTANTS, AND TEXT ANALYTICS TO BOLSTER SEGMENTAL GROWTH
- 7.5 COMPUTER VISION
- 7.5.1 MOUNTING DEMAND FOR AUTOMATION OF SURVEILLANCE, MANUFACTURING, AND HEALTHCARE TO FUEL SEGMENTAL GROWTH
8 AI INFERENCE PAAS MARKET, BY VERTICAL
- 8.1 INTRODUCTION
- 8.2 HEALTHCARE
- 8.2.1 GROWING FOCUS ON COST-EFFICIENT CLINICAL WORKFLOWS AND DIGITAL HEALTH TO BOOST SEGMENTAL GROWTH
- 8.3 BFSI
- 8.3.1 RISING EMPHASIS ON REAL-TIME FRAUD DETECTION AND RISK ASSESSMENT TO FUEL SEGMENTAL GROWTH
- 8.4 AUTOMOTIVE
- 8.4.1 MOUNTING DEMAND FOR CONNECTED, AUTONOMOUS, AND ELECTRIC VEHICLE TECHNOLOGIES TO DRIVE MARKET
- 8.5 RETAIL & E-COMMERCE
- 8.5.1 INCREASING ADOPTION OF AI-DRIVEN MARKETING AND SALES ANALYTICS TO CONTRIBUTE TO SEGMENTAL GROWTH
- 8.6 MEDIA & ENTERTAINMENT
- 8.6.1 ESCALATING DIGITAL CONTENT CONSUMPTION TO ACCELERATE SEGMENTAL GROWTH
- 8.7 GOVERNMENT & DEFENSE
- 8.7.1 INCREASING INVESTMENT IN MODERNIZATION AND SOVEREIGN AI INITIATIVES TO FOSTER SEGMENTAL GROWTH
- 8.8 IT & TELECOM
- 8.8.1 RISING NEED TO OPTIMIZE INTERNAL OPERATIONS AND DELIVER INTELLIGENT SERVICES TO BOLSTER SEGMENTAL GROWTH
- 8.9 OTHER VERTICALS
9 AI INFERENCE PAAS MARKET, BY REGION
- 9.1 INTRODUCTION
- 9.2 NORTH AMERICA
- 9.2.1 MACROECONOMIC OUTLOOK FOR NORTH AMERICA
- 9.2.2 US
- 9.2.2.1 Rising deployment of AI-powered applications in industries to boost market growth
- 9.2.3 CANADA
- 9.2.3.1 Increasing government investment in compute infrastructure to accelerate market growth
- 9.2.4 MEXICO
- 9.2.4.1 Strong focus on building data center cluster to meet surging demand for enterprise cloud services to drive market
- 9.3 EUROPE
- 9.3.1 MACROECONOMIC OUTLOOK FOR EUROPE
- 9.3.2 GERMANY
- 9.3.2.1 Mounting demand for intelligent, scalable, and locally compliant platforms in manufacturing sectors to augment market growth
- 9.3.3 UK
- 9.3.3.1 Rising implementation of policies to strengthen compute capacity and enhance digital sovereignty to fuel market growth
- 9.3.4 FRANCE
- 9.3.4.1 Growing emphasis on scaling compute resources and strengthening data sovereignty to bolster market growth
- 9.3.5 ITALY
- 9.3.5.1 Increasing investment in sovereign compute infrastructure to contribute to market growth
- 9.3.6 SPAIN
- 9.3.6.1 Government-backed digital transformation initiatives to accelerate market growth
- 9.3.7 POLAND
- 9.3.7.1 Strategic investments in compute infrastructure and government-led digitalization to support market growth
- 9.3.8 NORDICS
- 9.3.8.1 High commitment to sustainable digital infrastructure and advanced connectivity to boost market growth
- 9.3.9 REST OF EUROPE
- 9.4 ASIA PACIFIC
- 9.4.1 MACROECONOMIC OUTLOOK FOR ASIA PACIFIC
- 9.4.2 CHINA
- 9.4.2.1 Large-scale AI adoption and strategic investments in computing infrastructure to contribute to market growth
- 9.4.3 SOUTH KOREA
- 9.4.3.1 Rapid digital transformation and rise of industry-leading technology firms to foster market growth
- 9.4.4 JAPAN
- 9.4.4.1 Large-scale investments in AI platforms to accelerate market growth
- 9.4.5 INDIA
- 9.4.5.1 Booming startup ecosystem and government-led digital initiatives to fuel market growth
- 9.4.6 AUSTRALIA
- 9.4.6.1 Robust cloud infrastructure and growing ecosystem of AI adopters to bolster market growth
- 9.4.7 INDONESIA
- 9.4.7.1 Increasing digital-first population and integration of AI into core industries to augment market growth
- 9.4.8 MALAYSIA
- 9.4.8.1 Expanding data center footprint to expedite market growth
- 9.4.9 THAILAND
- 9.4.9.1 Growing focus on digital sovereignty and data localization to bolster market growth
- 9.4.10 VIETNAM
- 9.4.10.1 Proliferating infrastructure investment and strong ecosystem of digital infrastructure to foster market growth
- 9.4.11 REST OF ASIA PACIFIC
- 9.5 ROW
- 9.5.1 MACROECONOMIC OUTLOOK FOR ROW
- 9.5.2 SOUTH AMERICA
- 9.5.2.1 Growing demand for scalable and cost-effective solutions to support digital transformation to drive market
- 9.5.3 AFRICA
- 9.5.3.1 South Africa
- 9.5.3.1.1 AI-driven transformation in healthcare and e-commerce sectors to accelerate market growth
- 9.5.3.2 Other African countries
- 9.5.4 MIDDLE EAST
- 9.5.4.1 Bahrain
- 9.5.4.1.1 Robust digital infrastructure and progressive regulatory environment to augment market growth
- 9.5.4.2 Kuwait
- 9.5.4.2.1 Increasing investment in digital infrastructure and government support for technological innovation to drive market
- 9.5.4.3 Oman
- 9.5.4.3.1 Strong commitment to diversifying the economy and enhancing technological capabilities to foster market growth
- 9.5.4.4 Qatar
- 9.5.4.4.1 Innovative smart city initiatives and commitment to digital transformation to accelerate market growth
- 9.5.4.5 Saudi Arabia
- 9.5.4.5.1 Increasing investment in AI infrastructure and focus on digital transformation to expedite market growth
- 9.5.4.6 UAE
- 9.5.4.6.1 Rising deployment of AI to enhance operational efficiency to contribute to market growth
- 9.5.4.7 Rest of Middle East
10 COMPETITIVE LANDSCAPE
- 10.1 OVERVIEW
- 10.2 KEY PLAYER STRATEGIES/RIGHT TO WIN, 2021-2025
- 10.3 REVENUE ANALYSIS, 2021-2024
- 10.4 MARKET SHARE ANALYSIS, 2024
- 10.5 COMPANY VALUATION AND FINANCIAL METRICS
- 10.6 BRAND COMPARISON
- 10.7 COMPANY EVALUATION MATRIX: KEY PLAYERS, 2024
- 10.7.1 STARS
- 10.7.2 EMERGING LEADERS
- 10.7.3 PERVASIVE PLAYERS
- 10.7.4 PARTICIPANTS
- 10.7.5 COMPANY FOOTPRINT: KEY PLAYERS, 2024
- 10.7.5.1 Company footprint
- 10.7.5.2 Region footprint
- 10.7.5.3 Deployment footprint
- 10.7.5.4 Application footprint
- 10.7.5.5 Vertical footprint
- 10.8 COMPANY EVALUATION MATRIX: STARTUPS/SMES, 2024
- 10.8.1 PROGRESSIVE COMPANIES
- 10.8.2 RESPONSIVE COMPANIES
- 10.8.3 DYNAMIC COMPANIES
- 10.8.4 STARTING BLOCKS
- 10.8.5 COMPETITIVE BENCHMARKING: STARTUPS/SMES, 2024
- 10.8.5.1 Detailed list of key startups/SMEs
- 10.8.5.2 Competitive benchmarking of key startups/SMEs
- 10.9 COMPETITIVE SCENARIO
- 10.9.1 PRODUCT LAUNCHES/ENHANCEMENTS
- 10.9.2 DEALS
11 COMPANY PROFILES
- 11.1 KEY PLAYERS
- 11.1.1 MICROSOFT
- 11.1.1.1 Business overview
- 11.1.1.2 Products/Solutions/Services offered
- 11.1.1.3 Recent developments
- 11.1.1.3.1 Product launches/enhancements
- 11.1.1.3.2 Deals
- 11.1.1.4 MnM view
- 11.1.1.4.1 Key strengths/Right to win
- 11.1.1.4.2 Strategic choices
- 11.1.1.4.3 Weaknesses/Competitive threats
- 11.1.2 AMAZON WEB SERVICES, INC.
- 11.1.2.1 Business overview
- 11.1.2.2 Products/Solutions/Services offered
- 11.1.2.3 Recent developments
- 11.1.2.3.1 Product launches/enhancements
- 11.1.2.3.2 Deals
- 11.1.2.4 MnM view
- 11.1.2.4.1 Key strengths/Right to win
- 11.1.2.4.2 Strategic choices
- 11.1.2.4.3 Weaknesses/Competitive threats
- 11.1.3 GOOGLE CLOUD
- 11.1.3.1 Business overview
- 11.1.3.2 Products/Solutions/Services offered
- 11.1.3.3 Recent developments
- 11.1.3.3.1 Product launches/enhancements
- 11.1.3.3.2 Deals
- 11.1.3.4 MnM view
- 11.1.3.4.1 Key strengths/Right to win
- 11.1.3.4.2 Strategic choices
- 11.1.3.4.3 Weaknesses/Competitive threats
- 11.1.4 ORACLE
- 11.1.4.1 Business overview
- 11.1.4.2 Products/Solutions/Services offered
- 11.1.4.3 Recent developments
- 11.1.4.3.1 Product launches/enhancements
- 11.1.4.3.2 Deals
- 11.1.4.4 MnM view
- 11.1.4.4.1 Key strengths/Right to win
- 11.1.4.4.2 Strategic choices
- 11.1.4.4.3 Weaknesses/Competitive threats
- 11.1.5 IBM
- 11.1.5.1 Business overview
- 11.1.5.2 Products/Solutions/Services offered
- 11.1.5.3 Recent developments
- 11.1.5.3.1 Product launches/enhancements
- 11.1.5.3.2 Deals
- 11.1.5.4 MnM view
- 11.1.5.4.1 Key strengths/Right to win
- 11.1.5.4.2 Strategic choices
- 11.1.5.4.3 Weaknesses/Competitive threats
- 11.1.6 ALIBABA CLOUD
- 11.1.6.1 Business overview
- 11.1.6.2 Products/Solutions/Services offered
- 11.1.6.3 Recent developments
- 11.1.6.3.1 Product launches/enhancements
- 11.1.6.3.2 Deals
- 11.1.6.3.3 Other developments
- 11.1.7 SALESFORCE, INC.
- 11.1.7.1 Business overview
- 11.1.7.2 Products/Solutions/Services offered
- 11.1.7.3 Recent developments
- 11.1.7.3.1 Product launches/enhancements
- 11.1.7.3.2 Deals
- 11.1.8 TENCENT CLOUD
- 11.1.8.1 Business overview
- 11.1.8.2 Products/Solutions/Services offered
- 11.1.9 BAIDU, INC.
- 11.1.9.1 Business overview
- 11.1.9.2 Products/Solutions/Services offered
- 11.1.9.3 Recent developments
- 11.1.10 TOGETHER AI
- 11.1.10.1 Business overview
- 11.1.10.2 Products/Solutions/Services offered
- 11.1.10.3 Recent developments
- 11.1.10.3.1 Product launches/enhancements
- 11.1.10.3.2 Deals
- 11.2 OTHER PLAYERS
- 11.2.1 COREWEAVE
- 11.2.2 PREDIBASE
- 11.2.3 VECTARA
- 11.2.4 PREM AI
- 11.2.5 BASETEN
- 11.2.6 C3.AI, INC.
- 11.2.7 CLOUDFLARE, INC.
- 11.2.8 XFERENCE SRL
- 11.2.9 H2O.AI
- 11.2.10 DATAROBOT, INC
- 11.2.11 CEREBRAS
- 11.2.12 CLOUDERA, INC.
- 11.2.13 GROQ, INC.
- 11.2.14 SAMBANOVA, INC.
- 11.2.15 LATENT AI
- 11.2.16 MODULAR INC
- 11.2.17 FIREWORKS AI, INC.
- 11.2.18 DEEP INFRA
- 11.2.19 REPLICATE
- 11.2.20 ANYSCALE, INC
- 11.2.21 FEATHERLESS.AI
- 11.2.22 RAFAY SYSTEMS, INC.
12 APPENDIX
- 12.1 INSIGHTS FROM INDUSTRY EXPERTS
- 12.2 DISCUSSION GUIDE
- 12.3 KNOWLEDGESTORE: MARKETSANDMARKETS' SUBSCRIPTION PORTAL
- 12.4 CUSTOMIZATION OPTIONS
- 12.5 RELATED REPORTS
- 12.6 AUTHOR DETAILS