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Retrieval-augmented Generation (RAG) Market by Offering (Solution (RAG-enabled platforms, data management and indexing layers, retrieval & search models), Services), Type, Application, End User, and Deployment Type - Global Forecast to 2030

出版商 MarketsandMarkets產業別 ICT & Media出版日期 2025-10-10頁數 350報告編號 TC9579

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報告摘要

MarketsandMarkets: The retrieval-augmented generation (RAG) market is estimated to be USD 1.94 billion in 2025 and is projected to reach USD 9.86 billion by 2030 at a CAGR of 38.4%. Major technology companies, including Microsoft, AWS, Google, Anthropic, and Cohere, are heavily investing in RAG-powered solutions, integrations, and partnerships. Cloud hyperscalers are embedding RAG into their enterprise AI offerings, such as Azure OpenAI Service and AWS Bedrock, making it easier for businesses to integrate retrieval capabilities into their generative AI applications. This ecosystem expansion not only raises awareness of RAG but also lowers barriers to adoption by providing enterprises with ready-to-use, scalable solutions. Continued venture funding into RAG startups and partnerships between model providers and retrieval infrastructure vendors further accelerate the market’s growth trajectory. “Data management and indexing layer solution segment to witness significant growth during forecast period.” As enterprises continue to handle massive volumes of structured and unstructured data, robust indexing and efficient data management become critical for optimal RAG performance. Advances in vector databases, embeddings, and real-time data ingestion are driving rapid adoption of these solutions. With increasing demand for high-quality data retrieval, low-latency performance, and scalable architecture, the data management and indexing layer is projected to grow at the fastest rate, particularly in sectors with complex datasets like healthcare, financial services, and life sciences. “By type, foundational and enhanced RAG segment to lead market during forecast period.” Foundational and enhanced RAG is projected to account for the largest market share due to its early adoption across enterprises seeking reliable retrieval-augmented generative capabilities. This type combines large language models with robust retrieval architectures, enabling organizations to integrate structured and unstructured data sources for enhanced decision-making and knowledge generation. Foundational RAG solutions are widely deployed in enterprise search, content summarization, and domain-specific data synthesis, offering high accuracy, scalability, and operational efficiency. Enhanced RAG variants further improve the performance of foundational models by incorporating fine-tuned domain knowledge, relevance ranking, and advanced embedding mechanisms. Enterprises favor this type for its stability, established use cases, and proven ROI, making it the most prominent sub-segment in terms of market size. Additionally, technology vendors continue to enhance foundational RAG platforms with pre-trained models and plug-and-play integration capabilities, further reinforcing their market leadership. “Asia Pacific to record highest growth rate during forecast period.” Asia Pacific is becoming a key growth hub for the RAG market, driven by strong enterprise demand and a rapidly growing developer community. Companies in the region are using RAG to manage complex, data-heavy industries like healthcare, logistics, and energy. The rollout of cloud-based systems and 5G networks is opening up new opportunities for RAG-powered assistants and knowledge tools at the edge. Growth in the Asia Pacific comes from partnerships between governments, global tech giants, and local players, which ensures solutions meet local rules and cultural needs. Making Asia Pacific not just a fast adopter, but also a region that will influence the global future of RAG, especially in areas like multimodal and cross-domain AI. Breakdown of primaries The study contains insights from various industry experts, from solution vendors to Tier 1 companies. The break-up of the primaries is as follows: • By Company Type: Tier 1 – 35%, Tier 2 – 45%, and Tier 3 – 20% • By Designation: C-level –35%, D-level – 30%, and Others – 35% • By Region: North America – 40%, Europe – 20%, Asia Pacific – 25%, Middle East & Africa – 9%, Latin America – 6% The major players in the retrieval-augmented generation (RAG) market include Microsoft (US), Amazon Web Services, Inc. (US), Anthropic (US), Google (US), IBM (US), Cohere (Canada), NVIDIA (US), Pinecone (US), Elastic N.V. (US), Progress Software Corporation (US), Vectra AI, Inc. (US), Ragie.ai (US), Clarifai (US), Chatbees (US), Zilliz (US), Weaviate (Netherlands), Qdrant (Berlin), and MongoDB (US). These players have adopted various growth strategies, such as partnerships, agreements, collaborations, new product launches, enhancements, and acquisitions, to expand their market footprint. Research Coverage The market study covers the retrieval-augmented generation (RAG) market size and growth potential across different segments, including offering, type, application, end user, deployment type, and region. The offerings studied include solutions (RAG-enabled platforms, data management and indexing layers, retrieval & search models, and other solutions), and services (managed and professional). The type segment includes foundational & enhanced RAG, agentic & adaptive RAG, knowledge-structured & memory-based RAG, privacy-preserving & distributed RAG, and other types. The application segment includes enterprise search, domain-specific data synthesis, content summarization & generation, personalized recommendations & insights, code & developer productivity, and other applications. The end user segment includes healthcare & life sciences, retail & e-commerce, financial services, telecommunications, education, media & entertainment, software & technology providers, and other end users. The deployment type segment includes on-premises and cloud. The regional analysis of the retrieval-augmented generation (RAG) market covers North America, Europe, Asia Pacific, the Middle East & Africa, and Latin America. Key Benefits of Buying the Report The report will help market leaders and new entrants with information on the closest approximations of the global retrieval-augmented generation (RAG) market’s revenue numbers and subsegments. It will also help stakeholders understand the competitive landscape, gain insights, and plan suitable go-to-market strategies. Moreover, the report will provide insights for stakeholders to understand the market’s pulse and provide them with information on key market drivers, restraints, challenges, and opportunities. The report provides the following insights. Analysis of key drivers (Enhancing accuracy with context-aware AI responses, accelerating enterprise digitization), restraints (Managing high infrastructure costs, ensuring data privacy and protection), opportunities (Integrating RAG with domain-specific applications, expanding multilingual support), and challenges (Managing vendor fragmentation, mitigating risks of AI hallucinations) that are influencing the growth of the retrieval-augmented generation (RAG) market. Product Development/Innovation: Detailed insights on upcoming technologies, research & development activities, and new product & service launches in the retrieval-augmented generation (RAG) market Market Development: The report provides comprehensive information about lucrative markets, analyzing the retrieval-augmented generation (RAG) market across various regions. Market Diversification: Comprehensive information about new products and services, untapped geographies, recent developments, and investments in the retrieval-augmented generation (RAG) market. Competitive Assessment: In-depth assessment of market shares, growth strategies and service offerings of leading players such as Microsoft (US), Amazon Web Services, Inc. (US), Anthropic (US), Google (US), IBM (US), Cohere (Canada), NVIDIA (US), Pinecone (US), Elastic N.V. (US), Progress Software Corporation (US), Vectra AI, Inc. (US), Ragie.ai (US), Clarifai (US), Chatbees (US), Zilliz (US), Weaviate (Netherlands), Qdrant (Berlin), and MongoDB (US).
目錄 Table of Contents
1 INTRODUCTION 29 1.1 STUDY OBJECTIVES 29 1.2 MARKET DEFINITION 29 1.3 STUDY SCOPE 30 1.3.1 MARKET SEGMENTATION AND REGIONS COVERED 30 1.3.2 INCLUSIONS AND EXCLUSIONS 31 1.4 YEARS CONSIDERED 31 1.5 CURRENCY CONSIDERED 32 1.6 STAKEHOLDERS 32 2 RESEARCH METHODOLOGY 33 2.1 RESEARCH DATA 33 2.1.1 SECONDARY DATA 34 2.1.2 PRIMARY DATA 34 2.1.2.1 Breakdown of primary profiles 35 2.2 MARKET SIZE ESTIMATION 35 2.2.1 TOP-DOWN APPROACH 36 2.2.2 BOTTOM-UP APPROACH 37 2.2.3 RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET ESTIMATION: DEMAND-SIDE ANALYSIS 38 2.3 DATA TRIANGULATION 39 2.4 RISK ASSESSMENT 40 2.5 RESEARCH ASSUMPTIONS 40 2.6 RESEARCH LIMITATIONS 41 3 EXECUTIVE SUMMARY 42 4 PREMIUM INSIGHTS 45 4.1 ATTRACTIVE OPPORTUNITIES FOR PLAYERS IN RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET 45 4.2 RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY OFFERING 45 4.3 RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY SOLUTION 46 4.4 RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY TYPE 46 4.5 RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY APPLICATION 47 4.6 RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY DEPLOYMENT TYPE 47 4.7 RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY END USER 48 4.8 NORTH AMERICA: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY END USER AND REGION 48   5 MARKET OVERVIEW AND INDUSTRY TRENDS 49 5.1 INTRODUCTION 49 5.2 MARKET DYNAMICS 49 5.2.1 DRIVERS 50 5.2.1.1 Enhancing Accuracy with Context-aware AI Responses 50 5.2.1.2 Accelerating Enterprise Digitalization 51 5.2.2 RESTRAINTS 51 5.2.2.1 Managing High Infrastructure Costs 51 5.2.2.2 Ensuring Data Privacy and Protection 51 5.2.3 OPPORTUNITIES 52 5.2.3.1 Integrating RAG with Domain-specific Applications 52 5.2.3.2 Expanding Multilingual Support 52 5.2.4 CHALLENGES 52 5.2.4.1 Mitigating Risks of AI Hallucinations 52 5.2.4.2 Managing Vendor Fragmentation 52 5.3 RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET: BRIEF HISTORY 53 5.4 SUPPLY CHAIN ANALYSIS 54 5.5 ECOSYSTEM 56 5.6 CASE STUDIES 57 5.6.1 FILEVINE AND ZILLIZ CLOUD REVOLUTIONIZED CASE MANAGEMENT WITH VECTOR SEARCH 57 5.6.2 NEOPLE ASSISTANTS TRANSFORMING CUSTOMER SERVICE WITH WEAVIATE 58 5.6.3 DUST ADDRESSED COMPLEXITIES FACED BY QDRANT BY DEPLOYING LLMS 58 5.7 PORTER’S FIVE FORCES MODEL 59 5.7.1 THREAT OF NEW ENTRANTS 60 5.7.2 THREAT OF SUBSTITUTES 60 5.7.3 BARGAINING POWER OF BUYERS 60 5.7.4 BARGAINING POWER OF SUPPLIERS 60 5.7.5 INTENSITY OF COMPETITIVE RIVALRY 60 5.8 PATENT ANALYSIS 60 5.8.1 METHODOLOGY 60 5.8.2 LIST OF PATENTS IN RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, 2020–2024 61 5.9 DISRUPTIONS IMPACTING BUYERS/CLIENTS IN RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET 62 5.10 PRICING ANALYSIS 63 5.10.1 AVERAGE SELLING PRICE OF KEY PLAYERS, 2024 63 5.10.2 INDICATIVE PRICING ANALYSIS OF KEY PLAYERS, BY SOLUTION, 2024 63 5.11 KEY STAKEHOLDERS AND BUYING CRITERIA 65 5.11.1 KEY STAKEHOLDERS IN BUYING PROCESS 65 5.11.2 BUYING CRITERIA 66   5.12 TECHNOLOGY ANALYSIS 66 5.12.1 KEY TECHNOLOGIES 66 5.12.1.1 Large Language Models (LLMs) and Transformer-based Generators 66 5.12.1.2 Embedding Models 67 5.12.1.3 Dense Retrieval Mechanisms 67 5.12.1.4 Vector Databases 67 5.12.2 COMPLEMENTARY TECHNOLOGIES 68 5.12.2.1 Reranking Models 68 5.12.2.2 Knowledge Graphs 68 5.12.2.3 Semantic Search and NLP Techniques 68 5.12.2.4 Reasoning and Memory Modules 68 5.12.3 ADJACENT TECHNOLOGIES 69 5.12.3.1 Multimodal AI Processing 69 5.12.3.2 Data Privacy and Security Tools 69 5.12.3.3 AI/ML Frameworks and Orchestration Tools 69 5.13 REGULATORY LANDSCAPE 70 5.13.1 REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS 70 5.13.2 KEY REGULATIONS 73 5.13.2.1 North America 73 5.13.2.1.1 California Consumer Privacy Act (CCPA) 73 5.13.2.1.2 Canada's Directive on Automated Decision-making 73 5.13.2.1.3 AI and Automated Decision Systems (AADS) Ordinance (New York City) 73 5.13.2.2 Europe 73 5.13.2.2.1 General Data Protection Regulation (GDPR) 73 5.13.2.2.2 European Union's Artificial Intelligence Act (AIA) 73 5.13.2.2.3 Ethical Guidelines for Trustworthy AI by the European Commission 73 5.13.2.3 Asia Pacific 73 5.13.2.3.1 Personal Information Protection Law (PIPL) - China 73 5.13.2.3.2 Artificial Intelligence Ethics Guidelines - Japan 74 5.13.2.3.3 AI Strategy and Governance Framework - Australia 74 5.13.2.4 Middle East & Africa 74 5.13.2.4.1 UAE AI Regulation and Ethics Guidelines 74 5.13.2.4.2 South Africa's Protection of Personal Information Act (POPIA) 74 5.13.2.4.3 Egypt's Data Protection Law 74 5.13.2.5 Latin America 74 5.13.2.5.1 Brazil - General Data Protection Law (LGPD) 74 5.13.2.5.2 Mexico - Federal Law on the Protection of Personal Data Held by Private Parties (LFPDPPP) 75 5.13.2.5.3 Argentina - Personal Data Protection Law (PDPL) 75   5.14 KEY CONFERENCES & EVENTS 75 5.15 TECHNOLOGY ROADMAP FOR RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET 75 5.15.1 SHORT-TERM ROADMAP (2025-2026) 76 5.15.2 MID-TERM ROADMAP (2027–2028) 76 5.15.3 LONG-TERM ROADMAP (2029–2030) 76 5.16 BEST PRACTICES IN RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET 76 5.16.1 ENSURE HIGH-QUALITY KNOWLEDGE BASES 76 5.16.2 IMPLEMENT HYBRID SEARCH TECHNIQUES 76 5.16.3 ADOPT EXPLAINABLE AI PRACTICES 76 5.16.4 HUMAN-IN-THE-LOOP MECHANISMS 77 5.16.5 EMBED SECURITY AND COMPLIANCE FROM THE START 77 5.16.6 OPTIMIZE FOR LATENCY AND SCALE 77 5.16.7 MAINTAIN CONTINUOUS FEEDBACK LOOPS 77 5.17 CURRENT AND EMERGING BUSINESS MODELS 77 5.18 TOOLS, FRAMEWORKS, AND TECHNIQUES USED IN RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET 78 5.19 INVESTMENT AND FUNDING SCENARIO 78 5.20 IMPACT OF AI/GENERATIVE AI ON RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET 78 5.20.1 USE CASES OF GENERATIVE AI IN RETRIEVAL-AUGMENTED GENERATION (RAG) 79 5.21 IMPACT OF 2025 US TARIFF – RAG MARKET 80 5.21.1 INTRODUCTION 80 5.21.2 KEY TARIFF RATES 80 5.21.3 PRICE IMPACT ANALYSIS 81 5.21.3.1 Strategic Shifts and Emerging Trends 81 5.21.4 IMPACT ON COUNTRY/REGION 82 5.21.4.1 US 82 5.21.4.2 Asia Pacific 82 5.21.4.3 Europe 82 5.21.5 IMPACT ON END-USE INDUSTRIES 83 5.21.5.1 Healthcare & Life Sciences 83 5.21.5.2 Retail & E-commerce 83 5.21.5.3 Media & Entertainment 83 5.21.5.4 Financial Services 83 6 RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY OFFERING 84 6.1 INTRODUCTION 85 6.1.1 OFFERING: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET DRIVERS 85 6.2 SOLUTIONS 86 6.2.1 RAG SOLUTIONS TO EVOLVE TOWARD MORE AUTONOMOUS AND ADAPTIVE FRAMEWORKS 86 6.2.2 RAG-ENABLED PLATFORMS 87 6.2.3 DATA MANAGEMENT AND INDEXING LAYER 88 6.2.3.1 Need for scalable and intelligent indexing drives solution growth 88 6.2.4 RETRIEVAL AND SEARCH MODELS 89 6.2.4.1 Growing enterprise needs for contextual intelligence 89 6.2.5 OTHER SOLUTIONS 89 6.3 SERVICES 90 6.3.1 STREAMLINING ACADEMIC AND ADMINISTRATIVE OPERATIONS VIA INTEGRATED DIGITAL SYSTEMS 90 6.3.2 MANAGED SERVICES 91 6.3.2.1 Simplifying RAG Operations and Enhancing Scalability 91 6.3.3 PROFESSIONAL SERVICES 92 6.3.3.1 Driving Tailored Implementation and Performance Optimization 92 6.3.3.2 Support and Maintenance 93 6.3.3.3 Consulting and Customization 94 6.3.3.4 Training and Development 94 7 RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY TYPE 96 7.1 INTRODUCTION 97 7.1.1 TYPE: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET DRIVERS 97 7.2 FOUNDATIONAL AND ENHANCED RAG 98 7.2.1 FOUNDATIONAL AND ENHANCED RAG BUILDING BLOCK FOR ADVANCED AI SYSTEMS 98 7.3 AGENTIC AND ADAPTIVE RAG 99 7.3.1 ENABLING DYNAMIC AND AUTONOMOUS INTELLIGENCE 99 7.4 KNOWLEDGE-STRUCTURED AND MEMORY-BASED RAG 99 7.4.1 KNOWLEDGE-STRUCTURED & MEMORY-BASED RAG ENHANCING CONTEXTUAL REASONING AND LONG-TERM RECALL 99 7.5 PRIVACY-PRESERVING AND DISTRIBUTED RAG 100 7.5.1 PRIVACY-PRESERVING & DISTRIBUTED RAG SECURING KNOWLEDGE RETRIEVAL IN ERA OF DATA COMPLIANCE 100 7.6 OTHER TYPES 101 8 RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY APPLICATION 102 8.1 INTRODUCTION 103 8.1.1 APPLICATION: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET DRIVERS 103 8.2 ENTERPRISE SEARCH 104 8.2.1 ENTERPRISE SEARCH FUELED BY EXPONENTIAL GROWTH OF INTERNAL DATA 104 8.3 DOMAIN-SPECIFIC DATA SYNTHESIS 105 8.3.1 GROWING COMPLEXITY OF DOMAIN DATA DRIVES ADOPTION 105 8.4 CONTENT SUMMARIZATION AND GENERATION 105 8.4.1 AUTOMATE NARRATIVE CREATION TO BOOST KNOWLEDGE THROUGHPUT 105 8.5 PERSONALIZED RECOMMENDATIONS AND INSIGHTS 106 8.5.1 FOCUS ON USER-CENTRIC EXPERIENCES DRIVES ITS GROWTH 106 8.6 CODE AND DEVELOPER PRODUCTIVITY 107 8.6.1 AI-DRIVEN DEVELOPMENT TOOLS FUEL ADOPTION 107 8.7 OTHER APPLICATIONS 107 9 RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY DEPLOYMENT TYPE 109 9.1 INTRODUCTION 110 9.1.1 DEPLOYMENT TYPE: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET DRIVERS 110 9.2 ON-PREMISES 111 9.2.1 LOCALIZED AI-DRIVEN RETRIEVAL AND REASONING TO INCREASE AS REGULATORY SCRUTINY AROUND DATA USAGE INTENSIFIES 111 9.3 CLOUD 111 9.3.1 ACCELERATING SCALABILITY AND REAL-TIME INTELLIGENCE 111 10 RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY END USER 113 10.1 INTRODUCTION 114 10.1.1 END USER: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET DRIVERS 114 10.2 HEALTHCARE AND LIFE SCIENCES 115 10.2.1 ENHANCING CLINICAL INTELLIGENCE AND PATIENT OUTCOMES 115 10.3 RETAIL & E-COMMERCE 116 10.3.1 DRIVING PERSONALIZED AND CONTEXTUAL SHOPPING EXPERIENCES 116 10.4 FINANCIAL SERVICES 116 10.4.1 FINANCIAL SERVICES REINFORCING COMPLIANCE AND KNOWLEDGE AUTOMATION 116 10.5 TELECOMMUNICATIONS 117 10.5.1 POWERING INTELLIGENT NETWORK AND SERVICE AUTOMATION 117 10.6 EDUCATION 118 10.6.1 ADVANCING ADAPTIVE AND KNOWLEDGE-RICH LEARNING 118 10.7 MEDIA & ENTERTAINMENT 118 10.7.1 ACCELERATING CREATIVE AND CONTEXTUAL CONTENT GENERATION 118 10.8 OTHER END USERS 119 11 RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY REGION 120 11.1 INTRODUCTION 121 11.2 NORTH AMERICA 121 11.2.1 NORTH AMERICA: MACROECONOMIC OUTLOOK 121 11.2.2 US 125 11.2.2.1 Supportive regulatory environment and ecosystem-led commercialization of RAG 125 11.2.3 CANADA 128 11.2.3.1 Leveraging RAG technologies to enhance transparency and sectoral innovation 128 11.3 EUROPE 131 11.3.1 EUROPE: MACROECONOMIC OUTLOOK 131 11.3.2 UK 134 11.3.2.1 Driving enterprise adoption of RAG under strong regulatory frameworks 134 11.3.3 GERMANY 137 11.3.3.1 Industrial applications and compliance-driven RAG adoption 137 11.3.4 FRANCE 140 11.3.4.1 Strengthening multilingual RAG solutions through public–private collaboration 140 11.3.5 ITALY 143 11.3.5.1 Adoption of RAG to modernize knowledge-intensive industries 143 11.3.6 REST OF EUROPE 146 11.4 ASIA PACIFIC 146 11.4.1 ASIA PACIFIC: MACROECONOMIC OUTLOOK 147 11.4.2 CHINA 150 11.4.2.1 Domestic Vector & Knowledge-enhanced Models Power Large-scale RAG 150 11.4.3 INDIA 153 11.4.3.1 Public Pilots and SI Packages Convert RAG Trials into Production 153 11.4.4 JAPAN 156 11.4.4.1 SI-led, Language-aware RAG for Manufacturing and Service Sectors 156 11.4.5 AUSTRALIA & NEW ZEALAND 159 11.4.5.1 Government Pilots Driving Trusted RAG Use Cases 159 11.4.6 SOUTH KOREA 162 11.4.6.1 Telcos and Domestic Clouds Anchoring Sovereign RAG 162 11.4.7 REST OF ASIA PACIFIC 165 11.5 MIDDLE EAST & AFRICA 165 11.5.1 MIDDLE EAST & AFRICA: MACROECONOMIC OUTLOOK 166 11.5.2 UNITED ARAB EMIRATES 169 11.5.2.1 National AI Programs Anchoring RAG Commercialization 169 11.5.3 KINGDOM OF SAUDI ARABIA 172 11.5.3.1 Vision 2030 Investments Scaling Knowledge-centric AI 172 11.5.4 SOUTH AFRICA 174 11.5.4.1 Academic and Startup Ecosystem Piloting RAG 174 11.5.5 REST OF MIDDLE EAST & AFRICA 177 11.6 LATIN AMERICA 177 11.6.1 LATIN AMERICA: MACROECONOMIC OUTLOOK 178 11.6.2 BRAZIL 181 11.6.2.1 Legislative Pilots Driving Public-Sector RAG 181 11.6.3 MEXICO 184 11.6.3.1 SI adaptation of Spanish-language RAG for enterprise support 184 11.6.4 REST OF LATIN AMERICA 186 12 COMPETITIVE LANDSCAPE 187 12.1 INTRODUCTION 187 12.2 KEY PLAYER STRATEGIES/RIGHT TO WIN, 2022–2025 187 12.3 REVENUE ANALYSIS, 2024 188 12.4 MARKET SHARE ANALYSIS, 2024 188 12.5 BRAND/PRODUCT COMPARISON 191 12.6 COMPANY VALUATION AND FINANCIAL METRICS 192 12.7 COMPANY EVALUATION MATRIX: KEY PLAYERS, 2024 193 12.7.1 STARS 193 12.7.2 EMERGING LEADERS 193 12.7.3 PERVASIVE PLAYERS 193 12.7.4 PARTICIPANTS 194 12.7.5 COMPANY FOOTPRINT: KEY PLAYERS, 2024 195 12.7.5.1 Company footprint 195 12.7.5.2 Region footprint 195 12.7.5.3 Deployment type footprint 196 12.7.5.4 End user footprint 196 12.8 COMPANY EVALUATION MATRIX: STARTUPS/SMES, 2024 197 12.8.1 PROGRESSIVE COMPANIES 197 12.8.2 RESPONSIVE COMPANIES 197 12.8.3 DYNAMIC COMPANIES 197 12.8.4 STARTING BLOCKS 197 12.8.5 COMPETITIVE BENCHMARKING: STARTUPS/SMES, 2024 199 12.8.5.1 Detailed list of key startups/SMEs 199 12.8.5.2 Competitive benchmarking of key startups/SMEs 199 12.9 COMPETITIVE SCENARIO 200 12.9.1 PRODUCT LAUNCHES 200 12.9.2 DEALS 201 13 COMPANY PROFILES 203 13.1 INTRODUCTION 203 13.2 KEY PLAYERS 203 13.2.1 MICROSOFT 203 13.2.1.1 Business overview 203 13.2.1.2 Products/Solutions/Services offered 204 13.2.1.3 Recent developments 205 13.2.1.3.1 Product launches 205 13.2.1.3.2 Deals 205 13.2.1.4 MnM view 206 13.2.1.4.1 Key strengths 206 13.2.1.4.2 Strategic choices 206 13.2.1.4.3 Weaknesses and competitive threats 206 13.2.2 AWS 207 13.2.2.1 Business overview 207 13.2.2.2 Products/Solutions/Services offered 208 13.2.2.3 Recent developments 208 13.2.2.3.1 Deals 208 13.2.2.4 MnM view 209 13.2.2.4.1 Key strengths 209 13.2.2.4.2 Strategic choices 209 13.2.2.4.3 Weaknesses and competitive threats 209 13.2.3 GOOGLE 210 13.2.3.1 Business overview 210 13.2.3.2 Products/Solutions/Services offered 211 13.2.3.3 Recent developments 212 13.2.3.3.1 Deals 212 13.2.3.4 MnM view 212 13.2.3.4.1 Key strengths 212 13.2.3.4.2 Strategic choices 212 13.2.3.4.3 Weaknesses and competitive threats 213 13.2.4 ANTHROPIC 214 13.2.4.1 Business overview 214 13.2.4.2 Products/Solutions/Services offered 214 13.2.4.3 Recent developments 214 13.2.4.3.1 Deals 214 13.2.5 IBM 215 13.2.5.1 Business overview 215 13.2.5.2 Products/Solutions/Services offered 216 13.2.5.3 Recent developments 217 13.2.5.3.1 Deals 217 13.2.6 NVIDIA 218 13.2.6.1 Business overview 218 13.2.6.2 Products/Solutions/Services offered 219 13.2.6.3 Recent developments 220 13.2.6.3.1 Deals 220 13.2.7 COHERE 221 13.2.7.1 Business overview 221 13.2.7.2 Products/Solutions/Services offered 221 13.2.7.3 Recent developments 222 13.2.7.3.1 Deals 222 13.2.8 PINECONE 223 13.2.8.1 Business overview 223 13.2.8.2 Products/Solutions/Services offered 223 13.2.8.3 Recent developments 223 13.2.8.3.1 Deals 223 13.2.9 ELASTIC 225 13.2.9.1 Business overview 225 13.2.9.2 Products/Solutions/Services offered 226 13.2.9.3 Recent developments 227 13.2.9.3.1 Deals 227 13.2.10 MONGODB 228 13.2.10.1 Business overview 228 13.2.10.2 Products/Solutions/Services offered 229 13.2.10.3 Recent developments 229 13.2.10.3.1 Product launches 229 13.2.10.3.2 Deals 229 13.3 OTHER PLAYERS 230 13.3.1 PROGRESS SOFTWARE 230 13.3.2 RAGIE.AI 230 13.3.3 CLARIFAI 231 13.3.4 VECTARA 231 13.3.5 WEAVIATE 232 13.3.6 CHATBEES 232 13.3.7 ZILLIZ 233 13.3.8 QDRANT 234 14 ADJACENT/RELATED MARKETS 235 14.1 INTRODUCTION 235 14.2 GENERATIVE AI MARKET 235 14.2.1 MARKET DEFINITION 235 14.2.2 MARKET OVERVIEW 235 14.2.3 GENERATIVE AI MARKET, BY OFFERING 235 14.2.4 GENERATIVE AI MARKET, BY DATA MODALITY 236 14.2.5 GENERATIVE AI MARKET, BY APPLICATION 237 14.2.6 GENERATIVE AI MARKET, BY END USER 238 14.2.7 GENERATIVE AI MARKET, BY REGION 239 14.3 LARGE LANGUAGE MODEL (LLM) MARKET 240 14.3.1 MARKET DEFINITION 240 14.3.2 MARKET OVERVIEW 240 14.3.3 LARGE LANGUAGE MODEL (LLM) MARKET, BY OFFERING 241 14.3.4 LARGE LANGUAGE MODEL (LLM) MARKET, BY ARCHITECTURE 242 14.3.5 LARGE LANGUAGE MODEL (LLM) MARKET, BY MODALITY 243 14.3.6 LARGE LANGUAGE MODEL (LLM) MARKET, BY MODEL SIZE 244 14.3.7 LARGE LANGUAGE MODEL (LLM) MARKET, BY APPLICATION 245 14.3.8 LARGE LANGUAGE MODEL (LLM) MARKET, BY END USER 247 14.3.9 LARGE LANGUAGE MODEL (LLM) MARKET, BY REGION 248 15 APPENDIX 250 15.1 DISCUSSION GUIDE 250 15.2 KNOWLEDGESTORE: MARKETSANDMARKETS’ SUBSCRIPTION PORTAL 254 15.3 CUSTOMIZATION OPTIONS 256 15.4 RELATED REPORTS 256 15.5 AUTHOR DETAILS 257
圖表清單 List of Tables & Figures
TABLE 1 USD EXCHANGE RATES, 2020–2024 32 TABLE 2 RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET: ECOSYSTEM 56 TABLE 3 IMPACT OF PORTER’S FORCES ON RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET 59 TABLE 4 INDICATIVE PRICING ANALYSIS OF KEY RETRIEVAL-AUGMENTED GENERATION (RAG), BY SOLUTION, 2024 64 TABLE 5 INFLUENCE OF STAKEHOLDERS ON BUYING PROCESS FOR KEY END USERS (%) 65 TABLE 6 KEY BUYING CRITERIA FOR TOP THREE END USERS 66 TABLE 7 NORTH AMERICA: REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS 70 TABLE 8 EUROPE: REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS 71 TABLE 9 ASIA PACIFIC: REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS 71 TABLE 10 MIDDLE EAST & AFRICA: REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS 72 TABLE 11 LATIN AMERICA: REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS 72 TABLE 12 RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET: KEY CONFERENCES & EVENTS, 2025–2026 75 TABLE 13 US ADJUSTED RECIPROCAL TARIFF RATES 80 TABLE 14 RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY OFFERING, 2024–2030 (USD MILLION) 86 TABLE 15 RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY SOLUTION, 2024–2030 (USD MILLION) 87 TABLE 16 SOLUTION: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY REGION, 2024–2030 (USD MILLION) 87 TABLE 17 RAG-ENABLED PLATFORMS: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY REGION, 2024–2030 (USD MILLION) 88 TABLE 18 DATA MANAGEMENT AND INDEXING LAYER: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY REGION, 2024–2030 (USD MILLION) 88 TABLE 19 RETRIEVAL AND SEARCH MODELS: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY REGION, 2024–2030 (USD MILLION) 89 TABLE 20 OTHER SOLUTIONS: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY REGION, 2024–2030 (USD MILLION) 90 TABLE 21 RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY SERVICE, 2024–2030 (USD MILLION) 91 TABLE 22 SERVICES: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY REGION, 2024–2030 (USD MILLION) 91 TABLE 23 MANAGED SERVICES: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY REGION, 2024–2030 (USD MILLION) 92 TABLE 24 PROFESSIONAL SERVICES: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY REGION, 2024–2030 (USD MILLION) 93 TABLE 25 RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY PROFESSIONAL SERVICE, 2024–2030 (USD MILLION) 93 TABLE 26 SUPPORT AND MAINTENANCE: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY REGION, 2024–2030 (USD MILLION) 94 TABLE 27 CONSULTING AND CUSTOMIZATION: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY REGION, 2024–2030 (USD MILLION) 94 TABLE 28 TRAINING AND DEVELOPMENT: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY REGION, 2024–2030 (USD MILLION) 95 TABLE 29 RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY TYPE, 2024–2030 (USD MILLION) 98 TABLE 30 FOUNDATIONAL AND ENHANCED RAG: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY REGION, 2024–2030 (USD MILLION) 98 TABLE 31 AGENTIC AND ADAPTIVE RAG: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY REGION, 2024–2030 (USD MILLION) 99 TABLE 32 KNOWLEDGE-STRUCTURE AND MEMORY-BASED RAG: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY REGION, 2024–2030 (USD MILLION) 100 TABLE 33 PRIVACY-PRESERVING AND DISTRIBUTED RAG: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY REGION, 2024–2030 (USD MILLION) 100 TABLE 34 OTHER TYPES: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY REGION, 2024–2030 (USD MILLION) 101 TABLE 35 RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY APPLICATION, 2024–2030 (USD MILLION) 104 TABLE 36 ENTERPRISE SEARCH: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY REGION, 2024–2030 (USD MILLION) 104 TABLE 37 DOMAIN-SPECIFIC DATA SYNTHESIS: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY REGION, 2024–2030 (USD MILLION) 105 TABLE 38 CONTENT SUMMARIZATION AND GENERATION: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY REGION, 2024–2030 (USD MILLION) 106 TABLE 39 PERSONALIZED RECOMMENDATIONS AND INSIGHTS: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY REGION, 2024–2030 (USD MILLION) 106 TABLE 40 CODE AND DEVELOPER PRODUCTIVITY: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY REGION, 2024–2030 (USD MILLION) 107 TABLE 41 OTHER APPLICATIONS: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY REGION, 2024–2030 (USD MILLION) 108 TABLE 42 RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY DEPLOYMENT TYPE, 2024–2030 (USD MILLION) 110 TABLE 43 ON-PREMISES: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY REGION, 2024–2030 (USD MILLION) 111 TABLE 44 CLOUD: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY REGION, 2024–2030 (USD MILLION) 112 TABLE 45 RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY END USER, 2024–2030 (USD MILLION) 115 TABLE 46 HEALTHCARE & LIFE SCIENCES: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY REGION, 2024–2030 (USD MILLION) 115 TABLE 47 RETAIL & E-COMMERCE: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY REGION, 2024–2030 (USD MILLION) 116 TABLE 48 FINANCIAL SERVICES: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY REGION, 2024–2030 (USD MILLION) 117 TABLE 49 TELECOMMUNICATIONS: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY REGION, 2024–2030 (USD MILLION) 117 TABLE 50 EDUCATION: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY REGION, 2024–2030 (USD MILLION) 118 TABLE 51 MEDIA & ENTERTAINMENT: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY REGION, 2024–2030 (USD MILLION) 119 TABLE 52 OTHER END USERS: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY REGION, 2024–2030 (USD MILLION) 119 TABLE 53 RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY REGION, 2024–2030 (USD MILLION) 121 TABLE 54 NORTH AMERICA: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY 0FFERING, 2024–2030 (USD MILLION) 122 TABLE 55 NORTH AMERICA: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY SOLUTION, 2024–2030 (USD MILLION) 122 TABLE 56 NORTH AMERICA: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY SERVICE, 2024–2030 (USD MILLION) 123 TABLE 57 NORTH AMERICA: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY PROFESSIONAL SERVICE, 2024–2030 (USD MILLION) 123 TABLE 58 NORTH AMERICA: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY TYPE, 2024–2030 (USD MILLION) 123 TABLE 59 NORTH AMERICA: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY APPLICATION, 2024–2030 (USD MILLION) 124 TABLE 60 NORTH AMERICA: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY DEPLOYMENT TYPE, 2024–2030 (USD MILLION) 124 TABLE 61 NORTH AMERICA: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY END USER, 2024–2030 (USD MILLION) 124 TABLE 62 NORTH AMERICA: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY COUNTRY, 2024–2030 (USD MILLION) 125 TABLE 63 US: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY OFFERING, 2024–2030 (USD MILLION) 125 TABLE 64 US: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY SOLUTION, 2024–2030 (USD MILLION) 126 TABLE 65 US: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY SERVICE, 2024–2030 (USD MILLION) 126 TABLE 66 US: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY PROFESSIONAL SERVICE, 2024–2030 (USD MILLION) 126 TABLE 67 US: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY TYPE, 2024–2030 (USD MILLION) 127 TABLE 68 US: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY APPLICATION, 2024–2030 (USD MILLION) 127 TABLE 69 US: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY DEPLOYMENT TYPE, 2024–2030 (USD MILLION) 127 TABLE 70 US: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY END USER, 2024–2030 (USD MILLION) 128 TABLE 71 CANADA: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY OFFERING, 2024–2030 (USD MILLION) 128 TABLE 72 CANADA: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY SOLUTION, 2024–2030 (USD MILLION) 129 TABLE 73 CANADA: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY SERVICE, 2024–2030 (USD MILLION) 129 TABLE 74 CANADA: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY PROFESSIONAL SERVICE, 2024–2030 (USD MILLION) 129 TABLE 75 CANADA: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY TYPE, 2024–2030 (USD MILLION) 130 TABLE 76 CANADA: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY APPLICATION, 2024–2030 (USD MILLION) 130 TABLE 77 CANADA: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY DEPLOYMENT TYPE, 2024–2030 (USD MILLION) 130 TABLE 78 CANADA: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY END USER, 2024–2030 (USD MILLION) 131 TABLE 79 EUROPE: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY OFFERING, 2024–2030 (USD MILLION) 132 TABLE 80 EUROPE: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY SOLUTION, 2024–2030 (USD MILLION) 132 TABLE 81 EUROPE: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY SERVICE, 2024–2030 (USD MILLION) 132 TABLE 82 EUROPE: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY PROFESSIONAL SERVICE, 2024–2030 (USD MILLION) 132 TABLE 83 EUROPE: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY TYPE, 2024–2030 (USD MILLION) 133 TABLE 84 EUROPE: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY APPLICATION, 2024–2030 (USD MILLION) 133 TABLE 85 EUROPE: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY DEPLOYMENT TYPE, 2024–2030 (USD MILLION) 133 TABLE 86 EUROPE: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY END USER, 2024–2030 (USD MILLION) 134 TABLE 87 EUROPE: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY COUNTRY, 2024–2030 (USD MILLION) 134 TABLE 88 UK: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY OFFERING, 2024–2030 (USD MILLION) 135 TABLE 89 UK: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY SOLUTION, 2024–2030 (USD MILLION) 135 TABLE 90 UK: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY SERVICE, 2024–2030 (USD MILLION) 135 TABLE 91 UK: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY PROFESSIONAL SERVICE, 2024–2030 (USD MILLION) 135 TABLE 92 UK: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY TYPE, 2024–2030 (USD MILLION) 136 TABLE 93 UK: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY APPLICATION, 2024–2030 (USD MILLION) 136 TABLE 94 UK: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY DEPLOYMENT TYPE, 2024–2030 (USD MILLION) 136 TABLE 95 UK: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY END USER, 2024–2030 (USD MILLION) 137 TABLE 96 GERMANY: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY OFFERING, 2024–2030 (USD MILLION) 137 TABLE 97 GERMANY: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY SOLUTION, 2024–2030 (USD MILLION) 138 TABLE 98 GERMANY: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY SERVICE, 2024–2030 (USD MILLION) 138 TABLE 99 GERMANY: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY PROFESSIONAL SERVICE, 2024–2030 (USD MILLION) 138 TABLE 100 GERMANY: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY TYPE, 2024–2030 (USD MILLION) 139 TABLE 101 GERMANY: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY APPLICATION, 2024–2030 (USD MILLION) 139 TABLE 102 GERMANY: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY DEPLOYMENT TYPE, 2024–2030 (USD MILLION) 139 TABLE 103 GERMANY: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY END USER, 2024–2030 (USD MILLION) 140 TABLE 104 FRANCE: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY OFFERING, 2024–2030 (USD MILLION) 140 TABLE 105 FRANCE: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY SOLUTION, 2024–2030 (USD MILLION) 141 TABLE 106 FRANCE: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY SERVICE, 2024–2030 (USD MILLION) 141 TABLE 107 FRANCE: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY PROFESSIONAL SERVICE, 2024–2030 (USD MILLION) 141 TABLE 108 FRANCE: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY TYPE, 2024–2030 (USD MILLION) 142 TABLE 109 FRANCE: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY APPLICATION, 2024–2030 (USD MILLION) 142 TABLE 110 FRANCE: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY DEPLOYMENT TYPE, 2024–2030 (USD MILLION) 142 TABLE 111 FRANCE: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY END USER, 2024–2030 (USD MILLION) 143 TABLE 112 ITALY: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY OFFERING, 2024–2030 (USD MILLION) 143 TABLE 113 ITALY: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY SOLUTION, 2024–2030 (USD MILLION) 144 TABLE 114 ITALY: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY SERVICE, 2024–2030 (USD MILLION) 144 TABLE 115 ITALY: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY PROFESSIONAL SERVICE, 2024–2030 (USD MILLION) 144 TABLE 116 ITALY: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY TYPE, 2024–2030 (USD MILLION) 145 TABLE 117 ITALY: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY APPLICATION, 2024–2030 (USD MILLION) 145 TABLE 118 ITALY: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY DEPLOYMENT TYPE, 2024–2030 (USD MILLION) 145 TABLE 119 ITALY: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY END USER, 2024–2030 (USD MILLION) 146 TABLE 120 ASIA PACIFIC: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY 0FFERING, 2024–2030 (USD MILLION) 148 TABLE 121 ASIA PACIFIC: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY SOLUTION, 2024–2030 (USD MILLION) 148 TABLE 122 ASIA PACIFIC: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY SERVICE, 2024–2030 (USD MILLION) 148 TABLE 123 ASIA PACIFIC: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY PROFESSIONAL SERVICE, 2024–2030 (USD MILLION) 148 TABLE 124 ASIA PACIFIC: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY TYPE, 2024–2030 (USD MILLION) 149 TABLE 125 ASIA PACIFIC: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY APPLICATION, 2024–2030 (USD MILLION) 149 TABLE 126 ASIA PACIFIC: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY DEPLOYMENT TYPE, 2024–2030 (USD MILLION) 149 TABLE 127 ASIA PACIFIC: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY END USER, 2024–2030 (USD MILLION) 150 TABLE 128 ASIA PACIFIC: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY COUNTRY, 2024–2030 (USD MILLION) 150 TABLE 129 CHINA: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY OFFERING, 2024–2030 (USD MILLION) 151 TABLE 130 CHINA: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY SOLUTION, 2024–2030 (USD MILLION) 151 TABLE 131 CHINA: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY SERVICE, 2024–2030 (USD MILLION) 151 TABLE 132 CHINA: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY PROFESSIONAL SERVICE, 2024–2030 (USD MILLION) 151 TABLE 133 CHINA: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY TYPE, 2024–2030 (USD MILLION) 152 TABLE 134 CHINA: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY APPLICATION, 2024–2030 (USD MILLION) 152 TABLE 135 CHINA: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY DEPLOYMENT TYPE, 2024–2030 (USD MILLION) 152 TABLE 136 CHINA: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY END USER, 2024–2030 (USD MILLION) 153 TABLE 137 INDIA: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY OFFERING, 2024–2030 (USD MILLION) 153 TABLE 138 INDIA: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY SOLUTION, 2024–2030 (USD MILLION) 154 TABLE 139 INDIA: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY SERVICE, 2024–2030 (USD MILLION) 154 TABLE 140 INDIA: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY PROFESSIONAL SERVICE, 2024–2030 (USD MILLION) 154 TABLE 141 INDIA: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY TYPE, 2024–2030 (USD MILLION) 155 TABLE 142 INDIA: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY APPLICATION, 2024–2030 (USD MILLION) 155 TABLE 143 INDIA: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY DEPLOYMENT TYPE, 2024–2030 (USD MILLION) 155 TABLE 144 INDIA: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY END USER, 2024–2030 (USD MILLION) 156 TABLE 145 JAPAN: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY OFFERING, 2024–2030 (USD MILLION) 156 TABLE 146 JAPAN: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY SOLUTION, 2024–2030 (USD MILLION) 157 TABLE 147 JAPAN: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY SERVICE, 2024–2030 (USD MILLION) 157 TABLE 148 JAPAN: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY PROFESSIONAL SERVICE, 2024–2030 (USD MILLION) 157 TABLE 149 JAPAN: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY TYPE, 2024–2030 (USD MILLION) 158 TABLE 150 JAPAN: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY APPLICATION, 2024–2030 (USD MILLION) 158 TABLE 151 JAPAN: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY DEPLOYMENT TYPE, 2024–2030 (USD MILLION) 158 TABLE 152 JAPAN: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY END USER, 2024–2030 (USD MILLION) 159 TABLE 153 AUSTRALIA AND NEW ZEALAND: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY OFFERING, 2024–2030 (USD MILLION) 159 TABLE 154 AUSTRALIA AND NEW ZEALAND: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY SOLUTION, 2024–2030 (USD MILLION) 160 TABLE 155 AUSTRALIA AND NEW ZEALAND: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY SERVICE, 2024–2030 (USD MILLION) 160 TABLE 156 AUSTRALIA AND NEW ZEALAND: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY PROFESSIONAL SERVICE, 2024–2030 (USD MILLION) 160 TABLE 157 AUSTRALIA AND NEW ZEALAND: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY TYPE, 2024–2030 (USD MILLION) 161 TABLE 158 AUSTRALIA AND NEW ZEALAND: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY APPLICATION, 2024–2030 (USD MILLION) 161 TABLE 159 AUSTRALIA AND NEW ZEALAND: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY DEPLOYMENT TYPE, 2024–2030 (USD MILLION) 161 TABLE 160 AUSTRALIA AND NEW ZEALAND: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY END USER, 2024–2030 (USD MILLION) 162 TABLE 161 SOUTH KOREA: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY OFFERING, 2024–2030 (USD MILLION) 162 TABLE 162 SOUTH KOREA: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY SOLUTION, 2024–2030 (USD MILLION) 163 TABLE 163 SOUTH KOREA: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY SERVICE, 2024–2030 (USD MILLION) 163 TABLE 164 SOUTH KOREA: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY PROFESSIONAL SERVICE, 2024–2030 (USD MILLION) 163 TABLE 165 SOUTH KOREA: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY TYPE, 2024–2030 (USD MILLION) 164 TABLE 166 SOUTH KOREA: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY APPLICATION, 2024–2030 (USD MILLION) 164 TABLE 167 SOUTH KOREA: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY DEPLOYMENT TYPE, 2024–2030 (USD MILLION) 164 TABLE 168 SOUTH KOREA: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY END USER, 2024–2030 (USD MILLION) 165 TABLE 169 MIDDLE EAST & AFRICA: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY OFFERING, 2024–2030 (USD MILLION) 166 TABLE 170 MIDDLE EAST & AFRICA: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY SOLUTION, 2024–2030 (USD MILLION) 166 TABLE 171 MIDDLE EAST & AFRICA: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY SERVICE, 2024–2030 (USD MILLION) 167 TABLE 172 MIDDLE EAST & AFRICA: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY PROFESSIONAL SERVICE, 2024–2030 (USD MILLION) 167 TABLE 173 MIDDLE EAST & AFRICA: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY TYPE, 2024–2030 (USD MILLION) 167 TABLE 174 MIDDLE EAST & AFRICA: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY APPLICATION, 2024–2030 (USD MILLION) 168 TABLE 175 MIDDLE EAST & AFRICA: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY DEPLOYMENT TYPE, 2024–2030 (USD MILLION) 168 TABLE 176 MIDDLE EAST & AFRICA: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY END USER, 2024–2030 (USD MILLION) 168 TABLE 177 MIDDLE EAST & AFRICA: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY COUNTRY, 2024–2030 (USD MILLION) 169 TABLE 178 UAE: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY OFFERING, 2024–2030 (USD MILLION) 169 TABLE 179 UAE: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY SOLUTION, 2024–2030 (USD MILLION) 169 TABLE 180 UAE: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY SERVICE, 2024–2030 (USD MILLION) 170 TABLE 181 UAE: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY PROFESSIONAL SERVICE, 2024–2030 (USD MILLION) 170 TABLE 182 UAE: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY TYPE, 2024–2030 (USD MILLION) 170 TABLE 183 UAE: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY APPLICATION, 2024–2030 (USD MILLION) 171 TABLE 184 UAE: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY DEPLOYMENT TYPE, 2024–2030 (USD MILLION) 171 TABLE 185 UAE: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY END USER, 2024–2030 (USD MILLION) 171 TABLE 186 KSA: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY OFFERING, 2024–2030 (USD MILLION) 172 TABLE 187 KSA: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY SOLUTION, 2024–2030 (USD MILLION) 172 TABLE 188 KSA: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY SERVICE, 2024–2030 (USD MILLION) 172 TABLE 189 KSA: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY PROFESSIONAL SERVICE, 2024–2030 (USD MILLION) 173 TABLE 190 KSA: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY TYPE, 2024–2030 (USD MILLION) 173 TABLE 191 KSA: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY APPLICATION, 2024–2030 (USD MILLION) 173 TABLE 192 KSA: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY DEPLOYMENT TYPE, 2024–2030 (USD MILLION) 174 TABLE 193 KSA: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY END USER, 2024–2030 (USD MILLION) 174 TABLE 194 SOUTH AFRICA: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY OFFERING, 2024–2030 (USD MILLION) 174 TABLE 195 SOUTH AFRICA: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY SOLUTION, 2024–2030 (USD MILLION) 175 TABLE 196 SOUTH AFRICA: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY SERVICE, 2024–2030 (USD MILLION) 175 TABLE 197 SOUTH AFRICA: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY PROFESSIONAL SERVICE, 2024–2030 (USD MILLION) 175 TABLE 198 SOUTH AFRICA: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY TYPE, 2024–2030 (USD MILLION) 176 TABLE 199 SOUTH AFRICA: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY APPLICATION, 2024–2030 (USD MILLION) 176 TABLE 200 SOUTH AFRICA: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY DEPLOYMENT TYPE, 2024–2030 (USD MILLION) 176 TABLE 201 SOUTH AFRICA: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY END USER, 2024–2030 (USD MILLION) 177 TABLE 202 LATIN AMERICA: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY OFFERING, 2024–2030 (USD MILLION) 178 TABLE 203 LATIN AMERICA: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY SOLUTION, 2024–2030 (USD MILLION) 178 TABLE 204 LATIN AMERICA: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY SERVICE, 2024–2030 (USD MILLION) 179 TABLE 205 LATIN AMERICA: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY PROFESSIONAL SERVICE, 2024–2030 (USD MILLION) 179 TABLE 206 LATIN AMERICA: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY TYPE, 2024–2030 (USD MILLION) 179 TABLE 207 LATIN AMERICA: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY APPLICATION, 2024–2030 (USD MILLION) 180 TABLE 208 LATIN AMERICA: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY DEPLOYMENT TYPE, 2024–2030 (USD MILLION) 180 TABLE 209 LATIN AMERICA: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY END USER, 2024–2030 (USD MILLION) 180 TABLE 210 LATIN AMERICA: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY COUNTRY, 2024–2030 (USD MILLION) 181 TABLE 211 BRAZIL: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY OFFERING, 2024–2030 (USD MILLION) 181 TABLE 212 BRAZIL: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY SOLUTION, 2024–2030 (USD MILLION) 181 TABLE 213 BRAZIL: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY SERVICE, 2024–2030 (USD MILLION) 182 TABLE 214 BRAZIL: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY PROFESSIONAL SERVICE, 2024–2030 (USD MILLION) 182 TABLE 215 BRAZIL: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY TYPE, 2024–2030 (USD MILLION) 182 TABLE 216 BRAZIL: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY APPLICATION, 2024–2030 (USD MILLION) 183 TABLE 217 BRAZIL: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY DEPLOYMENT TYPE, 2024–2030 (USD MILLION) 183 TABLE 218 BRAZIL: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY END USER, 2024–2030 (USD MILLION) 183 TABLE 219 MEXICO: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY OFFERING, 2024–2030 (USD MILLION) 184 TABLE 220 MEXICO: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY SOLUTION, 2024–2030 (USD MILLION) 184 TABLE 221 MEXICO: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY SERVICE, 2024–2030 (USD MILLION) 184 TABLE 222 MEXICO: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY PROFESSIONAL SERVICE, 2024–2030 (USD MILLION) 185 TABLE 223 MEXICO: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY TYPE, 2024–2030 (USD MILLION) 185 TABLE 224 MEXICO: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY APPLICATION, 2024–2030 (USD MILLION) 185 TABLE 225 MEXICO: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY DEPLOYMENT TYPE, 2024–2030 (USD MILLION) 186 TABLE 226 MEXICO: RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, BY END USER, 2024–2030 (USD MILLION) 186 TABLE 227 OVERVIEW OF STRATEGIES ADOPTED BY KEY RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET PLAYERS, 2022–2025 187 TABLE 228 RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET: DEGREE OF COMPETITION 189 TABLE 229 RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET: REGION FOOTPRINT 195 TABLE 230 RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET: DEPLOYMENT TYPE FOOTPRINT 196 TABLE 231 RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET: END USER FOOTPRINT 196 TABLE 232 RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET: LIST OF KEY STARTUPS/SMES 199 TABLE 233 RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET: COMPETITIVE BENCHMARKING OF KEY STARTUPS/SMES 199 TABLE 234 RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET: PRODUCT LAUNCHES, JANUARY 2022–APRIL 2025 200 TABLE 235 RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET: DEALS, JANUARY 2022–APRIL 2025 201 TABLE 236 MICROSOFT: COMPANY OVERVIEW 203 TABLE 237 MICROSOFT: PRODUCTS/SOLUTIONS/SERVICES OFFERED 204 TABLE 238 MICROSOFT: PRODUCT LAUNCHES 205 TABLE 239 MICROSOFT: DEALS 205 TABLE 240 AWS: COMPANY OVERVIEW 207 TABLE 241 AWS: PRODUCTS/SOLUTIONS/SERVICES OFFERED 208 TABLE 242 AWS: DEALS 208 TABLE 243 GOOGLE: COMPANY OVERVIEW 210 TABLE 244 GOOGLE: PRODUCTS/SOLUTIONS/SERVICES OFFERED 211 TABLE 245 GOOGLE: DEALS 212 TABLE 246 ANTHROPIC: COMPANY OVERVIEW 214 TABLE 247 ANTHROPIC: PRODUCTS/SOLUTIONS/SERVICES OFFERED 214 TABLE 248 ANTHROPIC: DEALS 214 TABLE 249 IBM: COMPANY OVERVIEW 215 TABLE 250 IBM: PRODUCTS/SOLUTIONS/SERVICES OFFERED 216 TABLE 251 IBM: DEALS 217 TABLE 252 NVIDIA: COMPANY OVERVIEW 218 TABLE 253 NVIDIA: PRODUCTS/SOLUTIONS/SERVICES OFFERED 219 TABLE 254 NVIDIA: DEALS 220 TABLE 255 COHERE: COMPANY OVERVIEW 221 TABLE 256 COHERE: PRODUCTS/SOLUTIONS/SERVICES OFFERED 221 TABLE 257 COHERE: DEALS 222 TABLE 258 PINECONE: COMPANY OVERVIEW 223 TABLE 259 PINECONE: PRODUCTS/SOLUTIONS/SERVICES OFFERED 223 TABLE 260 PINECONE: DEALS 223 TABLE 261 ELASTIC: COMPANY OVERVIEW 225 TABLE 262 ELASTIC: PRODUCTS/SOLUTIONS/SERVICES OFFERED 226 TABLE 263 ELASTIC: DEALS 227 TABLE 264 MONGODB: COMPANY OVERVIEW 228 TABLE 265 MONGODB: PRODUCTS/SOLUTIONS/SERVICES OFFERED 229 TABLE 266 MONGODB: PRODUCT LAUNCHES 229 TABLE 267 MONGODB: DEALS 229 TABLE 268 GENERATIVE AI MARKET, BY OFFERING, 2020–2024 (USD MILLION) 236 TABLE 269 GENERATIVE AI MARKET, BY OFFERING, 2025–2032 (USD MILLION) 236 TABLE 270 GENERATIVE AI MARKET, BY DATA MODALITY, 2020–2024 (USD MILLION) 237 TABLE 271 GENERATIVE AI MARKET, BY DATA MODALITY, 2025–2032 (USD MILLION) 237 TABLE 272 GENERATIVE AI MARKET, BY APPLICATION, 2020–2024 (USD MILLION) 238 TABLE 273 GENERATIVE AI MARKET, BY APPLICATION, 2025–2032 (USD MILLION) 238 TABLE 274 GENERATIVE AI MARKET, BY END USER, 2020–2024 (USD MILLION) 239 TABLE 275 GENERATIVE AI MARKET, BY END USER, 2025–2032 (USD MILLION) 239 TABLE 276 GENERATIVE AI MARKET, BY REGION, 2020–2024 (USD MILLION) 240 TABLE 277 GENERATIVE AI MARKET, BY REGION, 2025–2032 (USD MILLION) 240 TABLE 278 LARGE LANGUAGE MODEL MARKET, BY OFFERING, 2020–2023 (USD MILLION) 241 TABLE 279 LARGE LANGUAGE MODEL MARKET, BY OFFERING, 2024–2030 (USD MILLION) 241 TABLE 280 LARGE LANGUAGE MODEL MARKET, BY ARCHITECTURE, 2020–2023 (USD MILLION) 242 TABLE 281 LARGE LANGUAGE MODEL MARKET, BY ARCHITECTURE, 2024–2030 (USD MILLION) 243 TABLE 282 LARGE LANGUAGE MODEL MARKET, BY MODALITY, 2020–2023 (USD MILLION) 243 TABLE 283 LARGE LANGUAGE MODEL MARKET, BY MODALITY, 2024–2030 (USD MILLION) 244 TABLE 284 LARGE LANGUAGE MODEL MARKET, BY MODEL SIZE, 2020–2023 (USD MILLION) 245 TABLE 285 LARGE LANGUAGE MODEL MARKET, BY MODEL SIZE, 2024–2030 (USD MILLION) 245 TABLE 286 LARGE LANGUAGE MODEL MARKET, BY APPLICATION, 2020–2023 (USD MILLION) 246 TABLE 287 LARGE LANGUAGE MODEL MARKET, BY APPLICATION, 2024–2030 (USD MILLION) 246 TABLE 288 LARGE LANGUAGE MODEL MARKET, BY END USER, 2020–2023 (USD MILLION) 247 TABLE 289 LARGE LANGUAGE MODEL MARKET, BY END USER, 2024–2030 (USD MILLION) 248 TABLE 290 LARGE LANGUAGE MODEL MARKET, BY REGION, 2020–2023 (USD MILLION) 249 TABLE 291 LARGE LANGUAGE MODEL MARKET, BY REGION, 2024–2030 (USD MILLION) 249 FIGURE 1 RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET: RESEARCH DESIGN 33 FIGURE 2 BREAKDOWN OF PRIMARY INTERVIEWS, BY COMPANY TYPE, DESIGNATION, AND REGION 35 FIGURE 3 RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET: TOP-DOWN AND BOTTOM-UP APPROACHES 36 FIGURE 4 MARKET SIZE ESTIMATION METHODOLOGY—APPROACH 1 (SUPPLY SIDE): REVENUE OF VENDORS IN RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET 37 FIGURE 5 MARKET SIZE ESTIMATION METHODOLOGY—APPROACH 2 (DEMAND SIDE): RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET 37 FIGURE 6 MARKET SIZE ESTIMATION METHODOLOGY: DEMAND-SIDE ANALYSIS 38 FIGURE 7 MARKET SIZE ESTIMATION USING BOTTOM-UP APPROACH 38 FIGURE 8 RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET: DATA TRIANGULATION 39 FIGURE 9 RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, 2024–2030 (USD MILLION) 43 FIGURE 10 RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET: REGIONAL AND COUNTRY-WISE SHARE, 2025 44 FIGURE 11 RAPID DIGITAL TRANSFORMATION AND GROWING ENTERPRISE AI ADOPTION TO DRIVE MARKET 45 FIGURE 12 SOLUTIONS SEGMENT TO HOLD LARGER MARKET SHARE IN 2025 45 FIGURE 13 RAG-ENABLED PLATFORMS SEGMENT TO HOLD LARGEST MARKET SHARE IN 2025 46 FIGURE 14 FOUNDATIONAL & ENHANCED RAG SEGMENT TO HOLD LARGEST MARKET SHARE IN 2025 46 FIGURE 15 ENTERPRISE SEARCH SEGMENT TO HOLD LARGEST MARKET SHARE IN 2025 47 FIGURE 16 CLOUD SEGMENT TO HOLD LARGER MARKET SHARE IN 2025 47 FIGURE 17 HEALTHCARE & LIFE SCIENCES SEGMENT TO LEAD MARKET IN 2025 48 FIGURE 18 HEALTHCARE & LIFE SCIENCES SEGMENT AND US TO ACCOUNT FOR SIGNIFICANT MARKET SHARES IN 2025 48 FIGURE 19 RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET: DRIVERS, RESTRAINTS, OPPORTUNITIES, AND CHALLENGES 50 FIGURE 20 BRIEF HISTORY OF RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET 53 FIGURE 21 RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET: SUPPLY CHAIN ANALYSIS 54 FIGURE 22 KEY PLAYERS IN RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET ECOSYSTEM 56 FIGURE 23 PORTER’S FIVE FORCES ANALYSIS 59 FIGURE 24 MAJOR PATENTS FOR RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET 61 FIGURE 25 RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET: DISRUPTIONS IMPACTING BUYERS/CLIENTS 62 FIGURE 26 AVERAGE SELLING PRICE OF KEY PLAYERS, USD PER MONTH, 2024 63 FIGURE 27 INFLUENCE OF STAKEHOLDERS ON BUYING PROCESS FOR KEY END USERS 65 FIGURE 28 KEY BUYING CRITERIA FOR TOP THREE END USERS 66 FIGURE 29 TOOLS, FRAMEWORKS, AND TECHNIQUES USED IN RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET 78 FIGURE 30 INVESTMENT AND FUNDING SCENARIO 78 FIGURE 31 USE CASES OF GENERATIVE AI IN RETRIEVAL-AUGMENTED GENERATION (RAG) 79 FIGURE 32 SERVICES SEGMENT TO GROW AT HIGHER CAGR DURING FORECAST PERIOD 85 FIGURE 33 DATA MANAGEMENT & INDEXING LAYER SEGMENT TO GROW AT HIGHEST CAGR DURING FORECAST PERIOD 86 FIGURE 34 MANAGED SERVICES SEGMENT TO GROW AT HIGHER CAGR DURING FORECAST PERIOD 90 FIGURE 35 TRAINING AND DEVELOPMENT TO GROW AT HIGHEST CAGR DURING FORECAST PERIOD 92 FIGURE 36 FOUNDATIONAL & ENHANCED RAG SEGMENT TO HOLD THE LARGEST MARKET SHARE DURING FORECAST PERIOD 97 FIGURE 37 ENTERPRISE SEARCH SEGMENT TO HOLD THE LARGEST MARKET SHARE DURING FORECAST PERIOD 103 FIGURE 38 CLOUD SEGMENT TO GROW AT HIGHER CAGR DURING FORECAST PERIOD 110 FIGURE 39 HEALTHCARE & LIFE SCIENCES SEGMENT TO HOLD LARGEST MARKET SHARE DURING FORECAST PERIOD 114 FIGURE 40 NORTH AMERICA: MARKET SNAPSHOT 122 FIGURE 41 ASIA PACIFIC: MARKET SNAPSHOT 147 FIGURE 42 REVENUE ANALYSIS OF KEY PLAYERS IN RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, 2022 TO 2024 (USD BILLION) 188 FIGURE 43 SHARES OF LEADING COMPANIES IN RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET, 2024 189 FIGURE 44 RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET: BRAND/PRODUCT COMPARISON 191 FIGURE 45 COMPANY VALUATION OF KEY VENDORS, 2025 192 FIGURE 46 FINANCIAL METRICS OF KEY VENDORS, 2025 193 FIGURE 47 RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET: COMPANY EVALUATION MATRIX (KEY PLAYERS), 2024 194 FIGURE 48 RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET: COMPANY FOOTPRINT 195 FIGURE 49 RETRIEVAL-AUGMENTED GENERATION (RAG) MARKET: COMPANY EVALUATION MATRIX (STARTUPS/SMES), 2024 198 FIGURE 50 MICROSOFT: COMPANY SNAPSHOT 204 FIGURE 51 AWS: COMPANY SNAPSHOT 207 FIGURE 52 GOOGLE: COMPANY SNAPSHOT 211 FIGURE 53 IBM: COMPANY SNAPSHOT 216 FIGURE 54 NVIDIA: COMPANY SNAPSHOT 219 FIGURE 55 ELASTIC: COMPANY SNAPSHOT 226 FIGURE 56 MONGODB: COMPANY SNAPSHOT 228

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