Retrieval-augmented Generation (RAG) Market worth $9.86 billion by 2030 | MarketsandMarkets™

DELRAY BEACH, Fla., Oct. 10, 2025 /PRNewswire/ -- According to 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, registering a CAGR of 38.4% during 2025–2030.

Browse 230 market data Tables and 50 Figures spread through 350 Pages and in-depth TOC on "Retrieval-augmented Generation (RAG) Market - Global Forecast to 2030"

Scope of the Report

• Market Size Available for Years: 2024–2030
• 2025 Market Size: USD 1.94 billion
• 2030 Projected Market Size: USD 9.86 billion
• CAGR (2025–2030): 38.4%
• Segments covered: Offering, Type, Application, End User, Deployment Type, and Region
• Region Highlight: Asia Pacific to register fastest growth rate during forecast period.

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Enterprises are increasingly adopting hybrid AI models that combine generative AI with retrieval, reasoning, and memory modules for specific use cases. RAG fits perfectly into this architecture by bridging the gap between static LLMs and dynamic, real-time knowledge sources. This approach supports critical enterprise use cases such as customer support automation, regulatory compliance monitoring, research assistance, and knowledge management. As organizations seek scalable, secure, and explainable AI deployments, the adoption of hybrid architectures with RAG at the core becomes a key market driver.

The rapid development of vector databases, embedding models, and semantic search technologies is another critical driver of the RAG market. Vendors like Pinecone, Weaviate, Zilliz, and Qdrant have made vector search scalable and enterprise-ready, enabling fast retrieval of large, complex datasets for integration with LLMs. These complementary technologies reduce latency, improve relevance, and make RAG architectures deployable at scale. As retrieval infrastructure matures, more organizations can implement robust RAG pipelines, broadening the market's reach beyond early adopters to mainstream enterprises.

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By end user, healthcare and life sciences segment to witness fastest growth rate during forecast period.

The healthcare and life sciences segment is expected to witness the highest CAGR due to the increasing demand for AI-driven clinical decision support, personalized treatment recommendations, drug discovery, and research data synthesis. Privacy-preserving and distributed RAG solutions are particularly important in this sector to ensure compliance with regulations such as HIPAA and GDPR while enabling secure, real-time data access. Rising investments in AI, coupled with the critical need for improved patient outcomes and operational efficiency, make healthcare the fastest-growing end-user segment over the forecast period.

By application, enterprise search segment to lead market during forecast period.

Organizations need to efficiently manage, access, and synthesize vast volumes of structured and unstructured data. RAG solutions enhance traditional enterprise search capabilities by combining retrieval mechanisms with generative AI, enabling users to obtain precise answers, summaries, and insights in real-time. Large enterprises, particularly in BFSI, healthcare, and IT services, are investing heavily in RAG-enabled search platforms to improve operational efficiency, customer service, and decision-making processes. The ability to index large datasets, integrate multiple data sources, and provide context-aware responses contributes to the widespread adoption of RAG for enterprise search.

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Asia Pacific to register fastest growth rate during forecast period.

The RAG market in Asia Pacific is witnessing exponential momentum, driven by its diverse linguistic landscape and rising enterprise demand for multilingual AI capabilities. Countries such as India, Japan, and South Korea are piloting RAG-based solutions in banking, telecom, and e-commerce, where contextual search and conversational AI can directly boost customer engagement and loyalty. China's significant investments in AI infrastructure and sovereign AI models are accelerating the adoption of localized RAG solutions for industries like education and manufacturing. With governments actively promoting digital economy initiatives, the region is emerging as a hotbed for AI-native startups that integrate RAG into verticalized applications, paving the way for the next wave of global innovation.

Top Key Companies in Retrieval-augmented Generation (RAG) Market:

The report profiles key 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).

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