Global No-Code Machine Learning Platforms Market Research Report 2025

Publication ID:

PB503253184

Publication Date:

March 26, 2025

Pages:

Publisher:

MRRPB5

Countries:

Global [1]

USD 2,900.00

IT Services [2]

Hardware (Computing & Electronics) [3]

Computing & Electronics [4]

Description:

The global market for No-Code Machine Learning Platforms was valued at US$ 923 million in the year 2024 and is projected to reach a revised size of US$ 1640 million by 2031, growing at a CAGR of 8.7% during the forecast period.
No-Code Machine Learning Platforms are user-friendly software tools that enable individuals, even without technical expertise, to build, deploy, and manage machine learning models. These platforms provide intuitive interfaces with drag-and-drop features, pre-built algorithms, and automated data preprocessing, allowing users to easily create models for tasks like prediction and data analysis. By eliminating the need for coding, these platforms make machine learning accessible to a broader audience, empowering businesses to leverage advanced data-driven insights and automation without requiring specialized skills.
North American market for No-Code Machine Learning Platforms 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 No-Code Machine Learning Platforms 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 No-Code Machine Learning Platforms 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 No-Code Machine Learning Platforms include Google, Microsoft, DataRobot, H2O.ai, AWS, RapidMiner, Alteryx, BigML, Levity, MonkeyLearn, 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 No-Code Machine Learning Platforms, 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 No-Code Machine Learning Platforms.
The No-Code Machine Learning Platforms 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 No-Code Machine Learning Platforms 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 No-Code Machine Learning Platforms 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
Google
Microsoft
DataRobot
H2O.ai
AWS
RapidMiner
Alteryx
BigML
Levity
MonkeyLearn
Runway ML
Peltarion
Slyce
TIBCO
Zest AI
Weka.io
Segment by Type
Automated Machine Learning (AutoML)
Data Preparation & Preprocessing
Model Deployment & Management
Others
Segment by Application
Healthcare
BFSI
IT & Telecom
Retail & E-commerce
Energy & Utilities
Media & Entertainment
Education
Others
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 No-Code Machine Learning Platforms 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.

Please Note - This is an on demand report and will be delivered in 2 business days (48 hours) post payment.

Table Of Contents:

1 Report Overview
1.1 Study Scope
1.2 Market Analysis by Type
1.2.1 Global No-Code Machine Learning Platforms Market Size Growth Rate by Type: 2020 VS 2024 VS 2031
1.2.2 Automated Machine Learning (AutoML)
1.2.3 Data Preparation & Preprocessing
1.2.4 Model Deployment & Management
1.2.5 Others
1.3 Market by Application
1.3.1 Global No-Code Machine Learning Platforms Market Growth by Application: 2020 VS 2024 VS 2031
1.3.2 Healthcare
1.3.3 BFSI
1.3.4 IT & Telecom
1.3.5 Retail & E-commerce
1.3.6 Energy & Utilities
1.3.7 Media & Entertainment
1.3.8 Education
1.3.9 Others
1.4 Assumptions and Limitations
1.5 Study Objectives
1.6 Years Considered
2 Global Growth Trends
2.1 Global No-Code Machine Learning Platforms Market Perspective (2020-2031)
2.2 Global No-Code Machine Learning Platforms Growth Trends by Region
2.2.1 Global No-Code Machine Learning Platforms Market Size by Region: 2020 VS 2024 VS 2031
2.2.2 No-Code Machine Learning Platforms Historic Market Size by Region (2020-2025)
2.2.3 No-Code Machine Learning Platforms Forecasted Market Size by Region (2026-2031)
2.3 No-Code Machine Learning Platforms Market Dynamics
2.3.1 No-Code Machine Learning Platforms Industry Trends
2.3.2 No-Code Machine Learning Platforms Market Drivers
2.3.3 No-Code Machine Learning Platforms Market Challenges
2.3.4 No-Code Machine Learning Platforms Market Restraints
3 Competition Landscape by Key Players
3.1 Global Top No-Code Machine Learning Platforms Players by Revenue
3.1.1 Global Top No-Code Machine Learning Platforms Players by Revenue (2020-2025)
3.1.2 Global No-Code Machine Learning Platforms Revenue Market Share by Players (2020-2025)
3.2 Global Top No-Code Machine Learning Platforms Players by Company Type and Market Share by Company Type (Tier 1, Tier 2, and Tier 3)
3.3 Global Key Players Ranking by No-Code Machine Learning Platforms Revenue
3.4 Global No-Code Machine Learning Platforms Market Concentration Ratio
3.4.1 Global No-Code Machine Learning Platforms Market Concentration Ratio (CR5 and HHI)
3.4.2 Global Top 10 and Top 5 Companies by No-Code Machine Learning Platforms Revenue in 2024
3.5 Global Key Players of No-Code Machine Learning Platforms Head office and Area Served
3.6 Global Key Players of No-Code Machine Learning Platforms, Product and Application
3.7 Global Key Players of No-Code Machine Learning Platforms, Date of Enter into This Industry
3.8 Mergers & Acquisitions, Expansion Plans
4 No-Code Machine Learning Platforms Breakdown Data by Type
4.1 Global No-Code Machine Learning Platforms Historic Market Size by Type (2020-2025)
4.2 Global No-Code Machine Learning Platforms Forecasted Market Size by Type (2026-2031)
5 No-Code Machine Learning Platforms Breakdown Data by Application
5.1 Global No-Code Machine Learning Platforms Historic Market Size by Application (2020-2025)
5.2 Global No-Code Machine Learning Platforms Forecasted Market Size by Application (2026-2031)
6 North America
6.1 North America No-Code Machine Learning Platforms Market Size (2020-2031)
6.2 North America No-Code Machine Learning Platforms Market Growth Rate by Country: 2020 VS 2024 VS 2031
6.3 North America No-Code Machine Learning Platforms Market Size by Country (2020-2025)
6.4 North America No-Code Machine Learning Platforms Market Size by Country (2026-2031)
6.5 United States
6.6 Canada
7 Europe
7.1 Europe No-Code Machine Learning Platforms Market Size (2020-2031)
7.2 Europe No-Code Machine Learning Platforms Market Growth Rate by Country: 2020 VS 2024 VS 2031
7.3 Europe No-Code Machine Learning Platforms Market Size by Country (2020-2025)
7.4 Europe No-Code Machine Learning Platforms 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 No-Code Machine Learning Platforms Market Size (2020-2031)
8.2 Asia-Pacific No-Code Machine Learning Platforms Market Growth Rate by Region: 2020 VS 2024 VS 2031
8.3 Asia-Pacific No-Code Machine Learning Platforms Market Size by Region (2020-2025)
8.4 Asia-Pacific No-Code Machine Learning Platforms 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 No-Code Machine Learning Platforms Market Size (2020-2031)
9.2 Latin America No-Code Machine Learning Platforms Market Growth Rate by Country: 2020 VS 2024 VS 2031
9.3 Latin America No-Code Machine Learning Platforms Market Size by Country (2020-2025)
9.4 Latin America No-Code Machine Learning Platforms Market Size by Country (2026-2031)
9.5 Mexico
9.6 Brazil
10 Middle East & Africa
10.1 Middle East & Africa No-Code Machine Learning Platforms Market Size (2020-2031)
10.2 Middle East & Africa No-Code Machine Learning Platforms Market Growth Rate by Country: 2020 VS 2024 VS 2031
10.3 Middle East & Africa No-Code Machine Learning Platforms Market Size by Country (2020-2025)
10.4 Middle East & Africa No-Code Machine Learning Platforms Market Size by Country (2026-2031)
10.5 Turkey
10.6 Saudi Arabia
10.7 UAE
11 Key Players Profiles
11.1 Google
11.1.1 Google Company Details
11.1.2 Google Business Overview
11.1.3 Google No-Code Machine Learning Platforms Introduction
11.1.4 Google Revenue in No-Code Machine Learning Platforms Business (2020-2025)
11.1.5 Google Recent Development
11.2 Microsoft
11.2.1 Microsoft Company Details
11.2.2 Microsoft Business Overview
11.2.3 Microsoft No-Code Machine Learning Platforms Introduction
11.2.4 Microsoft Revenue in No-Code Machine Learning Platforms Business (2020-2025)
11.2.5 Microsoft Recent Development
11.3 DataRobot
11.3.1 DataRobot Company Details
11.3.2 DataRobot Business Overview
11.3.3 DataRobot No-Code Machine Learning Platforms Introduction
11.3.4 DataRobot Revenue in No-Code Machine Learning Platforms Business (2020-2025)
11.3.5 DataRobot Recent Development
11.4 H2O.ai
11.4.1 H2O.ai Company Details
11.4.2 H2O.ai Business Overview
11.4.3 H2O.ai No-Code Machine Learning Platforms Introduction
11.4.4 H2O.ai Revenue in No-Code Machine Learning Platforms Business (2020-2025)
11.4.5 H2O.ai Recent Development
11.5 AWS
11.5.1 AWS Company Details
11.5.2 AWS Business Overview
11.5.3 AWS No-Code Machine Learning Platforms Introduction
11.5.4 AWS Revenue in No-Code Machine Learning Platforms Business (2020-2025)
11.5.5 AWS Recent Development
11.6 RapidMiner
11.6.1 RapidMiner Company Details
11.6.2 RapidMiner Business Overview
11.6.3 RapidMiner No-Code Machine Learning Platforms Introduction
11.6.4 RapidMiner Revenue in No-Code Machine Learning Platforms Business (2020-2025)
11.6.5 RapidMiner Recent Development
11.7 Alteryx
11.7.1 Alteryx Company Details
11.7.2 Alteryx Business Overview
11.7.3 Alteryx No-Code Machine Learning Platforms Introduction
11.7.4 Alteryx Revenue in No-Code Machine Learning Platforms Business (2020-2025)
11.7.5 Alteryx Recent Development
11.8 BigML
11.8.1 BigML Company Details
11.8.2 BigML Business Overview
11.8.3 BigML No-Code Machine Learning Platforms Introduction
11.8.4 BigML Revenue in No-Code Machine Learning Platforms Business (2020-2025)
11.8.5 BigML Recent Development
11.9 Levity
11.9.1 Levity Company Details
11.9.2 Levity Business Overview
11.9.3 Levity No-Code Machine Learning Platforms Introduction
11.9.4 Levity Revenue in No-Code Machine Learning Platforms Business (2020-2025)
11.9.5 Levity Recent Development
11.10 MonkeyLearn
11.10.1 MonkeyLearn Company Details
11.10.2 MonkeyLearn Business Overview
11.10.3 MonkeyLearn No-Code Machine Learning Platforms Introduction
11.10.4 MonkeyLearn Revenue in No-Code Machine Learning Platforms Business (2020-2025)
11.10.5 MonkeyLearn Recent Development
11.11 Runway ML
11.11.1 Runway ML Company Details
11.11.2 Runway ML Business Overview
11.11.3 Runway ML No-Code Machine Learning Platforms Introduction
11.11.4 Runway ML Revenue in No-Code Machine Learning Platforms Business (2020-2025)
11.11.5 Runway ML Recent Development
11.12 Peltarion
11.12.1 Peltarion Company Details
11.12.2 Peltarion Business Overview
11.12.3 Peltarion No-Code Machine Learning Platforms Introduction
11.12.4 Peltarion Revenue in No-Code Machine Learning Platforms Business (2020-2025)
11.12.5 Peltarion Recent Development
11.13 Slyce
11.13.1 Slyce Company Details
11.13.2 Slyce Business Overview
11.13.3 Slyce No-Code Machine Learning Platforms Introduction
11.13.4 Slyce Revenue in No-Code Machine Learning Platforms Business (2020-2025)
11.13.5 Slyce Recent Development
11.14 TIBCO
11.14.1 TIBCO Company Details
11.14.2 TIBCO Business Overview
11.14.3 TIBCO No-Code Machine Learning Platforms Introduction
11.14.4 TIBCO Revenue in No-Code Machine Learning Platforms Business (2020-2025)
11.14.5 TIBCO Recent Development
11.15 Zest AI
11.15.1 Zest AI Company Details
11.15.2 Zest AI Business Overview
11.15.3 Zest AI No-Code Machine Learning Platforms Introduction
11.15.4 Zest AI Revenue in No-Code Machine Learning Platforms Business (2020-2025)
11.15.5 Zest AI Recent Development
11.16 Weka.io
11.16.1 Weka.io Company Details
11.16.2 Weka.io Business Overview
11.16.3 Weka.io No-Code Machine Learning Platforms Introduction
11.16.4 Weka.io Revenue in No-Code Machine Learning Platforms Business (2020-2025)
11.16.5 Weka.io 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

Companies Mentioned:

Google
Microsoft
DataRobot
H2O.ai
AWS
RapidMiner
Alteryx
BigML
Levity
MonkeyLearn
Runway ML
Peltarion
Slyce
TIBCO
Zest AI
Weka.io

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