The global market for Agentic RAG (Retrieval Augmented Generation) Solution was valued at US$ 79.1 million in the year 2024 and is projected to reach a revised size of US$ 826 million by 2031, growing at a CAGR of 35.1% during the forecast period.
Agentic RAG or agent-based RAG typically refers to a framework that combines the concepts of agents and Retrieval-Augmented Generation (RAG) in AI. It reshapes the approach to question answering through a cutting-edge agent-based framework.Unlike conventional techniques that depend exclusively on large language models (LLMs), agentic RAG utilizes intelligent agents to address complex questions that necessitate detailed planning, multi-step reasoning, and the integration of external tools. These agents function as expert researchers, skillfully navigating numerous documents, comparing information, creating summaries, and providing thorough, accurate responses.Furthermore, agentic RAG is designed for seamless scalability, allowing for the easy addition of new documents. Each set is overseen by its sub-agent.Together, Agentic RAG emphasizes the importance of informed decision-making and active participation in processes, whether in personal contexts or AI applications. It underscores how leveraging external knowledge can empower users or systems to achieve better results.Agentic RAG isn't just an upgrade; it's a paradigm shift. This framework heralds the redefinition of enterprise AI applications by introducing retrieval precision, generative prowess, and decision-making agents into one competent model. Be it operational efficiency or the quest to deliver unparalleled user experience, Agentic RAG presents an intelligent scalable solution.The creation of Agentic RAG marks a significant evolution in AI-assisted information retrieval. By combining the strengths of Retrieval-Augmented Generation with autonomous agent capabilities, Agentic RAG systems can not only access and retrieve information but also proactively address complex queries and tasks. This advancement represents a leap forward in the practical application of AI, enabling more accurate, comprehensive, and contextually relevant responses.Traditional RAG systems rely on pre-existing data to generate responses. While this approach works, it has limitations, especially when it comes to dealing with complex queries or ensuring the accuracy of the retrieved information. Agentic RAG, on the other hand, employs intelligent agents that can cross-reference multiple sources, verify data, and use multi-step reasoning to ensure the output is both precise and contextually relevant.In essence, Agentic RAG takes the concept of RAG to the next level, combining advanced querying capabilities with intelligent tool usage to deliver superior results.
North American market for Agentic RAG (Retrieval Augmented Generation) Solution is estimated to increase from $ million in 2024 to reach $ million by 2031, at a CAGR of % during the forecast period of 2025 through 2031.
Asia-Pacific market for Agentic RAG (Retrieval Augmented Generation) Solution is estimated to increase from $ million in 2024 to reach $ million by 2031, at a CAGR of % during the forecast period of 2025 through 2031.
The global market for Agentic RAG (Retrieval Augmented Generation) Solution in Healthcare is estimated to increase from $ million in 2024 to $ million by 2031, at a CAGR of % during the forecast period of 2025 through 2031.
The major global companies of Agentic RAG (Retrieval Augmented Generation) Solution include Microsoft (SimplAI), MongoDB Atlas, Moveworks, Markovate, Ampcome, Vectorize AI, Inc, Dell Technologies, Primafelicitas, SoluLab, CloudRaft, etc. In 2024, the world's top three vendors accounted for approximately % of the revenue.
This report aims to provide a comprehensive presentation of the global market for Agentic RAG (Retrieval Augmented Generation) Solution, with both quantitative and qualitative analysis, to help readers develop business/growth strategies, assess the market competitive situation, analyze their position in the current marketplace, and make informed business decisions regarding Agentic RAG (Retrieval Augmented Generation) Solution.
The Agentic RAG (Retrieval Augmented Generation) Solution market size, estimations, and forecasts are provided in terms of and revenue ($ millions), considering 2024 as the base year, with history and forecast data for the period from 2020 to 2031. This report segments the global Agentic RAG (Retrieval Augmented Generation) Solution market comprehensively. Regional market sizes, concerning products by Type, by Application, and by players, are also provided.
For a more in-depth understanding of the market, the report provides profiles of the competitive landscape, key competitors, and their respective market ranks. The report also discusses technological trends and new product developments.
The report will help the Agentic RAG (Retrieval Augmented Generation) Solution companies, new entrants, and industry chain related companies in this market with information on the revenues for the overall market and the sub-segments across the different segments, by company, by Type, by Application, and by regions.
Market Segmentation
By Company
Microsoft (SimplAI)
MongoDB Atlas
Moveworks
Markovate
Ampcome
Vectorize AI, Inc
Dell Technologies
Primafelicitas
SoluLab
CloudRaft
Softtik Technologies
Hackett Group (LeewayHertz)
Fluid AI
Markovate
Segment by Type
Routing Agent
One-Shot Query Planning Agent
Tool Use Agent
ReAct (Reason + Action) Agents
Dynamic Planning Agent
Segment by Application
Healthcare
Finance and E-commerce
Telecommunications
Law
Education
Other
By Region
North America
United States
Canada
Asia-Pacific
China
Japan
South Korea
Southeast Asia
India
Australia
Rest of Asia
Europe
Germany
France
U.K.
Italy
Russia
Nordic Countries
Rest of Europe
Latin America
Mexico
Brazil
Rest of Latin America
Middle East & Africa
Turkey
Saudi Arabia
UAE
Rest of MEA
Chapter Outline
Chapter 1: Introduces the report scope of the report, executive summary of different market segments (by Type, by Application, etc), including the market size of each market segment, future development potential, and so on. It offers a high-level view of the current state of the market and its likely evolution in the short to mid-term, and long term.
Chapter 2: Introduces executive summary of global market size, regional market size, this section also introduces the market dynamics, latest developments of the market, the driving factors and restrictive factors of the market, the challenges and risks faced by companies in the industry, and the analysis of relevant policies in the industry.
Chapter 3: Detailed analysis of Agentic RAG (Retrieval Augmented Generation) Solution company competitive landscape, revenue market share, latest development plan, merger, and acquisition information, etc.
Chapter 4: Provides the analysis of various market segments by Type, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different market segments.
Chapter 5: Provides the analysis of various market segments by Application, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different downstream markets.
Chapter 6, 7, 8, 9, 10: North America, Europe, Asia Pacific, Latin America, Middle East and Africa segment by country. It provides a quantitative analysis of the market size and development potential of each region and its main countries and introduces the market development, future development prospects, market space, and capacity of each country in the world.
Chapter 11: Provides profiles of key players, introducing the basic situation of the main companies in the market in detail, including product sales, revenue, price, gross margin, product introduction, recent development, etc.
Chapter 12: The main points and conclusions of the report.
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1 Report Overview
1.1 Study Scope
1.2 Market Analysis by Type
1.2.1 Global Agentic RAG (Retrieval Augmented Generation) Solution Market Size Growth Rate by Type: 2020 VS 2024 VS 2031
1.2.2 Routing Agent
1.2.3 One-Shot Query Planning Agent
1.2.4 Tool Use Agent
1.2.5 ReAct (Reason + Action) Agents
1.2.6 Dynamic Planning Agent
1.3 Market by Application
1.3.1 Global Agentic RAG (Retrieval Augmented Generation) Solution Market Growth by Application: 2020 VS 2024 VS 2031
1.3.2 Healthcare
1.3.3 Finance and E-commerce
1.3.4 Telecommunications
1.3.5 Law
1.3.6 Education
1.3.7 Other
1.4 Assumptions and Limitations
1.5 Study Objectives
1.6 Years Considered
2 Global Growth Trends
2.1 Global Agentic RAG (Retrieval Augmented Generation) Solution Market Perspective (2020-2031)
2.2 Global Agentic RAG (Retrieval Augmented Generation) Solution Growth Trends by Region
2.2.1 Global Agentic RAG (Retrieval Augmented Generation) Solution Market Size by Region: 2020 VS 2024 VS 2031
2.2.2 Agentic RAG (Retrieval Augmented Generation) Solution Historic Market Size by Region (2020-2025)
2.2.3 Agentic RAG (Retrieval Augmented Generation) Solution Forecasted Market Size by Region (2026-2031)
2.3 Agentic RAG (Retrieval Augmented Generation) Solution Market Dynamics
2.3.1 Agentic RAG (Retrieval Augmented Generation) Solution Industry Trends
2.3.2 Agentic RAG (Retrieval Augmented Generation) Solution Market Drivers
2.3.3 Agentic RAG (Retrieval Augmented Generation) Solution Market Challenges
2.3.4 Agentic RAG (Retrieval Augmented Generation) Solution Market Restraints
3 Competition Landscape by Key Players
3.1 Global Top Agentic RAG (Retrieval Augmented Generation) Solution Players by Revenue
3.1.1 Global Top Agentic RAG (Retrieval Augmented Generation) Solution Players by Revenue (2020-2025)
3.1.2 Global Agentic RAG (Retrieval Augmented Generation) Solution Revenue Market Share by Players (2020-2025)
3.2 Global Top Agentic RAG (Retrieval Augmented Generation) Solution Players by Company Type and Market Share by Company Type (Tier 1, Tier 2, and Tier 3)
3.3 Global Key Players Ranking by Agentic RAG (Retrieval Augmented Generation) Solution Revenue
3.4 Global Agentic RAG (Retrieval Augmented Generation) Solution Market Concentration Ratio
3.4.1 Global Agentic RAG (Retrieval Augmented Generation) Solution Market Concentration Ratio (CR5 and HHI)
3.4.2 Global Top 10 and Top 5 Companies by Agentic RAG (Retrieval Augmented Generation) Solution Revenue in 2024
3.5 Global Key Players of Agentic RAG (Retrieval Augmented Generation) Solution Head office and Area Served
3.6 Global Key Players of Agentic RAG (Retrieval Augmented Generation) Solution, Product and Application
3.7 Global Key Players of Agentic RAG (Retrieval Augmented Generation) Solution, Date of Enter into This Industry
3.8 Mergers & Acquisitions, Expansion Plans
4 Agentic RAG (Retrieval Augmented Generation) Solution Breakdown Data by Type
4.1 Global Agentic RAG (Retrieval Augmented Generation) Solution Historic Market Size by Type (2020-2025)
4.2 Global Agentic RAG (Retrieval Augmented Generation) Solution Forecasted Market Size by Type (2026-2031)
5 Agentic RAG (Retrieval Augmented Generation) Solution Breakdown Data by Application
5.1 Global Agentic RAG (Retrieval Augmented Generation) Solution Historic Market Size by Application (2020-2025)
5.2 Global Agentic RAG (Retrieval Augmented Generation) Solution Forecasted Market Size by Application (2026-2031)
6 North America
6.1 North America Agentic RAG (Retrieval Augmented Generation) Solution Market Size (2020-2031)
6.2 North America Agentic RAG (Retrieval Augmented Generation) Solution Market Growth Rate by Country: 2020 VS 2024 VS 2031
6.3 North America Agentic RAG (Retrieval Augmented Generation) Solution Market Size by Country (2020-2025)
6.4 North America Agentic RAG (Retrieval Augmented Generation) Solution Market Size by Country (2026-2031)
6.5 United States
6.6 Canada
7 Europe
7.1 Europe Agentic RAG (Retrieval Augmented Generation) Solution Market Size (2020-2031)
7.2 Europe Agentic RAG (Retrieval Augmented Generation) Solution Market Growth Rate by Country: 2020 VS 2024 VS 2031
7.3 Europe Agentic RAG (Retrieval Augmented Generation) Solution Market Size by Country (2020-2025)
7.4 Europe Agentic RAG (Retrieval Augmented Generation) Solution Market Size by Country (2026-2031)
7.5 Germany
7.6 France
7.7 U.K.
7.8 Italy
7.9 Russia
7.10 Nordic Countries
8 Asia-Pacific
8.1 Asia-Pacific Agentic RAG (Retrieval Augmented Generation) Solution Market Size (2020-2031)
8.2 Asia-Pacific Agentic RAG (Retrieval Augmented Generation) Solution Market Growth Rate by Region: 2020 VS 2024 VS 2031
8.3 Asia-Pacific Agentic RAG (Retrieval Augmented Generation) Solution Market Size by Region (2020-2025)
8.4 Asia-Pacific Agentic RAG (Retrieval Augmented Generation) Solution Market Size by Region (2026-2031)
8.5 China
8.6 Japan
8.7 South Korea
8.8 Southeast Asia
8.9 India
8.10 Australia
9 Latin America
9.1 Latin America Agentic RAG (Retrieval Augmented Generation) Solution Market Size (2020-2031)
9.2 Latin America Agentic RAG (Retrieval Augmented Generation) Solution Market Growth Rate by Country: 2020 VS 2024 VS 2031
9.3 Latin America Agentic RAG (Retrieval Augmented Generation) Solution Market Size by Country (2020-2025)
9.4 Latin America Agentic RAG (Retrieval Augmented Generation) Solution Market Size by Country (2026-2031)
9.5 Mexico
9.6 Brazil
10 Middle East & Africa
10.1 Middle East & Africa Agentic RAG (Retrieval Augmented Generation) Solution Market Size (2020-2031)
10.2 Middle East & Africa Agentic RAG (Retrieval Augmented Generation) Solution Market Growth Rate by Country: 2020 VS 2024 VS 2031
10.3 Middle East & Africa Agentic RAG (Retrieval Augmented Generation) Solution Market Size by Country (2020-2025)
10.4 Middle East & Africa Agentic RAG (Retrieval Augmented Generation) Solution Market Size by Country (2026-2031)
10.5 Turkey
10.6 Saudi Arabia
10.7 UAE
11 Key Players Profiles
11.1 Microsoft (SimplAI)
11.1.1 Microsoft (SimplAI) Company Details
11.1.2 Microsoft (SimplAI) Business Overview
11.1.3 Microsoft (SimplAI) Agentic RAG (Retrieval Augmented Generation) Solution Introduction
11.1.4 Microsoft (SimplAI) Revenue in Agentic RAG (Retrieval Augmented Generation) Solution Business (2020-2025)
11.1.5 Microsoft (SimplAI) Recent Development
11.2 MongoDB Atlas
11.2.1 MongoDB Atlas Company Details
11.2.2 MongoDB Atlas Business Overview
11.2.3 MongoDB Atlas Agentic RAG (Retrieval Augmented Generation) Solution Introduction
11.2.4 MongoDB Atlas Revenue in Agentic RAG (Retrieval Augmented Generation) Solution Business (2020-2025)
11.2.5 MongoDB Atlas Recent Development
11.3 Moveworks
11.3.1 Moveworks Company Details
11.3.2 Moveworks Business Overview
11.3.3 Moveworks Agentic RAG (Retrieval Augmented Generation) Solution Introduction
11.3.4 Moveworks Revenue in Agentic RAG (Retrieval Augmented Generation) Solution Business (2020-2025)
11.3.5 Moveworks Recent Development
11.4 Markovate
11.4.1 Markovate Company Details
11.4.2 Markovate Business Overview
11.4.3 Markovate Agentic RAG (Retrieval Augmented Generation) Solution Introduction
11.4.4 Markovate Revenue in Agentic RAG (Retrieval Augmented Generation) Solution Business (2020-2025)
11.4.5 Markovate Recent Development
11.5 Ampcome
11.5.1 Ampcome Company Details
11.5.2 Ampcome Business Overview
11.5.3 Ampcome Agentic RAG (Retrieval Augmented Generation) Solution Introduction
11.5.4 Ampcome Revenue in Agentic RAG (Retrieval Augmented Generation) Solution Business (2020-2025)
11.5.5 Ampcome Recent Development
11.6 Vectorize AI, Inc
11.6.1 Vectorize AI, Inc Company Details
11.6.2 Vectorize AI, Inc Business Overview
11.6.3 Vectorize AI, Inc Agentic RAG (Retrieval Augmented Generation) Solution Introduction
11.6.4 Vectorize AI, Inc Revenue in Agentic RAG (Retrieval Augmented Generation) Solution Business (2020-2025)
11.6.5 Vectorize AI, Inc Recent Development
11.7 Dell Technologies
11.7.1 Dell Technologies Company Details
11.7.2 Dell Technologies Business Overview
11.7.3 Dell Technologies Agentic RAG (Retrieval Augmented Generation) Solution Introduction
11.7.4 Dell Technologies Revenue in Agentic RAG (Retrieval Augmented Generation) Solution Business (2020-2025)
11.7.5 Dell Technologies Recent Development
11.8 Primafelicitas
11.8.1 Primafelicitas Company Details
11.8.2 Primafelicitas Business Overview
11.8.3 Primafelicitas Agentic RAG (Retrieval Augmented Generation) Solution Introduction
11.8.4 Primafelicitas Revenue in Agentic RAG (Retrieval Augmented Generation) Solution Business (2020-2025)
11.8.5 Primafelicitas Recent Development
11.9 SoluLab
11.9.1 SoluLab Company Details
11.9.2 SoluLab Business Overview
11.9.3 SoluLab Agentic RAG (Retrieval Augmented Generation) Solution Introduction
11.9.4 SoluLab Revenue in Agentic RAG (Retrieval Augmented Generation) Solution Business (2020-2025)
11.9.5 SoluLab Recent Development
11.10 CloudRaft
11.10.1 CloudRaft Company Details
11.10.2 CloudRaft Business Overview
11.10.3 CloudRaft Agentic RAG (Retrieval Augmented Generation) Solution Introduction
11.10.4 CloudRaft Revenue in Agentic RAG (Retrieval Augmented Generation) Solution Business (2020-2025)
11.10.5 CloudRaft Recent Development
11.11 Softtik Technologies
11.11.1 Softtik Technologies Company Details
11.11.2 Softtik Technologies Business Overview
11.11.3 Softtik Technologies Agentic RAG (Retrieval Augmented Generation) Solution Introduction
11.11.4 Softtik Technologies Revenue in Agentic RAG (Retrieval Augmented Generation) Solution Business (2020-2025)
11.11.5 Softtik Technologies Recent Development
11.12 Hackett Group (LeewayHertz)
11.12.1 Hackett Group (LeewayHertz) Company Details
11.12.2 Hackett Group (LeewayHertz) Business Overview
11.12.3 Hackett Group (LeewayHertz) Agentic RAG (Retrieval Augmented Generation) Solution Introduction
11.12.4 Hackett Group (LeewayHertz) Revenue in Agentic RAG (Retrieval Augmented Generation) Solution Business (2020-2025)
11.12.5 Hackett Group (LeewayHertz) Recent Development
11.13 Fluid AI
11.13.1 Fluid AI Company Details
11.13.2 Fluid AI Business Overview
11.13.3 Fluid AI Agentic RAG (Retrieval Augmented Generation) Solution Introduction
11.13.4 Fluid AI Revenue in Agentic RAG (Retrieval Augmented Generation) Solution Business (2020-2025)
11.13.5 Fluid AI Recent Development
11.14 Markovate
11.14.1 Markovate Company Details
11.14.2 Markovate Business Overview
11.14.3 Markovate Agentic RAG (Retrieval Augmented Generation) Solution Introduction
11.14.4 Markovate Revenue in Agentic RAG (Retrieval Augmented Generation) Solution Business (2020-2025)
11.14.5 Markovate Recent Development
12 Analyst's Viewpoints/Conclusions
13 Appendix
13.1 Research Methodology
13.1.1 Methodology/Research Approach
13.1.1.1 Research Programs/Design
13.1.1.2 Market Size Estimation
13.1.1.3 Market Breakdown and Data Triangulation
13.1.2 Data Source
13.1.2.1 Secondary Sources
13.1.2.2 Primary Sources
13.2 Author Details
13.3 Disclaimer
Microsoft (SimplAI)
MongoDB Atlas
Moveworks
Markovate
Ampcome
Vectorize AI, Inc
Dell Technologies
Primafelicitas
SoluLab
CloudRaft
Softtik Technologies
Hackett Group (LeewayHertz)
Fluid AI
Markovate
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*If Applicable.
