Global ML Ops market is expected to witness a growth of significant CAGR for the forecast period, 2022-2026. Organizations are actively adopting machine learning technology solutions to increase the customer experience and help to achieve maximum profit. To stay ahead in the market and gain a competitive edge against the competitors, market players are adopting advanced data processing and integration techniques to attain insights to make smart decisions. The adoption of ML Ops in organizations is still at a nascent stage, and the growing awareness about the benefits of using ML Ops in organizations is expected to create lucrative opportunities for market growth. The growing use of data science technology for the advancements in artificial intelligence and computing power and the autonomous learning of systems is fueling the demand for advanced solutions for better data management. Machine learning is in high demand by the prominent industry verticals, including healthcare, retail, education, manufacturing, telecommunication, and financial institutions. The use of ML Ops helps in the creation of reproducible models and workflows. Also, it helps in the easy deployment of machine learning technology at any location, which is the major reason for their high preference among the organizations. ML Ops analyzes the performance of models over time and looks at the specific needs for model security, governance, and transparency.

Global ML Ops market is segmented into solutions, product focus, task, component, type, organization size, end use, regional distribution, and company. Based on the regional analysis, Asia-pacific is expected to register the fastest incremental growth over the forecast period, 2022-2026. The rise in the number of enterprises owing to improving economic conditions and the adoption of advanced technologies for increasing the efficiency and performance of the organization is contributing to the market growth.

Based on the organization size, the market is divided into large enterprises and small & medium sized enterprises. The large enterprises segment is expected to account for major market share for the next five years due to the growing use of technologies such as artificial intelligence, machine learning, and investing amounts to manage and analyze the data generated.

The major players operating in the global ML Ops market are Microsoft Corporation, Amazon Web Services, Inc., Google, LLC, IBM Corporation, Dataiku SAS, Iguazio Ltd, Databricks Inc., DataRobot, Inc., Cloudera, Inc., Modzy, Algorithmia, Inc., HP Enterprises Co., Valohai, Allegro AI Ltd., Comet ML Inc., among others. Major companies are developing advanced technologies and launching new services to stay competitive in the market.

Years considered for this report:

Historical Years: 2016-2019

Base Year: 2020

Estimated Year: 2021

Forecast Period: 2022–2026

Objective of the Study:

  • To analyze the historical growth of the market size of global ML Ops market from 2016 to 2019.
  • To estimate and forecast the market size of global ML Ops market from 2020 to 2026 and growth rate until 2026.
  • To classify and forecast global ML Ops market based on solutions, product focus, task, component, type, organization size, end use, regional distribution, and company.
  • To identify dominant region or segment in the global ML Ops market.
  • To identify drivers and challenges for global ML Ops market.
  • To examine competitive developments such as expansions, new product launches, mergers & acquisitions, etc., in global ML Ops market.
  • To identify and analyze the profile of leading players operating in global ML Ops market.
  • To identify key sustainable strategies adopted by market players in global ML Ops market.


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TechSci Research performed both primary as well as exhaustive secondary research for this study. Initially, TechSci Research sourced a list of service providers across the globe. Subsequently, TechSci Research conducted primary research surveys with the identified companies. While interviewing, the respondents were also enquired about their competitors. Through this technique, TechSci Research could include the service providers who could not be identified due to the limitations of secondary research. TechSci Research analyzed the service providers, distribution channels and presence of all major players across the globe.

TechSci Research calculated the market size of global ML Ops market using a bottom-up approach, wherein data for various end-user segments was recorded and forecast for the future years. TechSci Research sourced these values from the industry experts and company representatives and externally validated through analyzing historical data of these product types and applications for getting an appropriate, overall market size. Various secondary sources such as company websites, news articles, press releases, company annual reports, investor presentations and financial reports were also studied by TechSci Research.

Key Target Audience:

  • ML Ops service provider companies
  • Market research and consulting firms
  • Government bodies such as regulating authorities and policy makers
  • Organizations, forums, and alliances related to ML Ops market

The study is useful in providing answers to several critical questions that are important for the industry stakeholders such as service providers, suppliers and partners, end users, etc., besides allowing them in strategizing investments and capitalizing on market opportunities.

Report Scope:

In this report, global ML Ops market has been segmented into following categories, in addition to the industry trends which have also been detailed below:

·         Global ML Ops Market, By Solutions:

    • Data Management
    • Modelling
    • Continuous Deployment
    • Computing and Resource
  • Global ML Ops Market, By Product Focus:
    • Data-Centric
    • Model Centric
  • Global ML Ops Market, By Task:
    • Model Lifecycle Management
    • Model Versioning & Iteration
    • Model Monitoring & Management
    • Model Governance
    • Model Security
  • Global ML Ops Market, By Component:
    • Platform
    • Services
      • Professional
      • Managed
  • Global ML Ops Market, By Type:
    • Public Cloud
    • Private Cloud
    • Hybrid Cloud
  • Global ML Ops Market, By Organization Size:
    • Large Enterprise
    • Small & Medium Sized Enterprises
  • Global ML Ops Market, By End Use:
    • BFSI
    • IT & Telecom
    • Retail
    • Manufacturing
    • Public Sector
    • Others
  • Global ML Ops Market, By Region:
    • Asia-Pacific
      • China
      • Japan
      • South Korea
      • India
      • Singapore
      • Australia
      • Vietnam
    • Europe & CIS
      • France
      • Germany
      • United Kingdom
      • Italy
      • Russia
    • North America
      • United States
      • Mexico
      • Canada
    • South America

§  Brazil

§  Argentina

§  Colombia

§  Chile

o   Middle East & Africa

§  South Africa

§  Saudi Arabia

§  UAE

§  Nigeria

§  Egypt

§  Turkey

Competitive Landscape

Company Profiles: Detailed analysis of the major companies present in global ML Ops market.

Available Customizations:

With the given market data, TechSci Research offers customizations according to a company’s specific needs. The following customization options are available for the report:

Company Information

  • Detailed analysis and profiling of additional market players (up to five).
Global ML Ops market is an upcoming report to be released soon. If you wish an early delivery of this report or want to confirm the date of release, please contact us at sales@techsciresearch.com

1.    Product Overview

2.    Research Methodology

3.    Impact of COVID-19 on Global ML Ops Market

4.    Executive Summary

5.    Global ML Ops Market Outlook

5.1.  Market Size & Forecast

5.1.1.     By Value

5.2.  Market Share & Forecast

5.2.1.     By Solutions (Data Management, Modelling, Continuous Deployment, Computing and Resource)

5.2.2.     By Product Focus (Data-Centric, Model Centric)

5.2.3.     By Task (Model Lifecycle Management, Model Versioning & Iteration, Model Monitoring & Management, Model Governance, Model Security)

5.2.4.     By Component (Platform, Services (Professional, Managed))

5.2.5.     By Type (Public Cloud, Private Cloud, Hybrid Cloud)

5.2.6.     By Organization Size (Large Enterprises, Small & Medium Sized Enterprises)

5.2.7.     By End Use (BFSI, IT & Telecom, Retail, Manufacturing, Public Sector, Others)

5.2.8.     By Company (2020)

5.2.9.     By Region

5.3.  Product Market Map

6.    Asia-Pacific ML Ops Market Outlook

6.1.  Market Size & Forecast          

6.1.1.     By Value

6.2.  Market Share & Forecast

6.2.1.     By Solutions

6.2.2.     By Product Focus

6.2.3.     By Task

6.2.4.     By Component

6.2.5.     By Type

6.2.6.     By Organization Size

6.2.7.     By End Use

6.2.8.     By Country

6.3.  Asia-Pacific: Country Analysis

6.3.1.     China ML Ops Market Outlook

6.3.1.1.         Market Size & Forecast

6.3.1.1.1.             By Value

6.3.1.2.         Market Share & Forecast

6.3.1.2.1.             By Solutions

6.3.1.2.2.             By Product Focus

6.3.1.2.3.             By Task

6.3.1.2.4.             By Component

6.3.1.2.5.             By Type

6.3.1.2.6.             By Organization Size

6.3.1.2.7.             By End Use

6.3.2.     India ML Ops Market Outlook

6.3.2.1.         Market Size & Forecast

6.3.2.1.1.             By Value

6.3.2.2.         Market Share & Forecast

6.3.2.2.1.             By Solutions

6.3.2.2.2.             By Product Focus

6.3.2.2.3.             By Task

6.3.2.2.4.             By Component

6.3.2.2.5.             By Type

6.3.2.2.6.             By Organization Size

6.3.2.2.7.             By End Use

6.3.3.     Japan ML Ops Market Outlook

6.3.3.1.         Market Size & Forecast

6.3.3.1.1.             By Value 

6.3.3.2.         Market Share & Forecast

6.3.3.2.1.             By Solutions

6.3.3.2.2.             By Product Focus

6.3.3.2.3.             By Task

6.3.3.2.4.             By Component

6.3.3.2.5.             By Type

6.3.3.2.6.             By Organization Size

6.3.3.2.7.             By End Use

6.3.4.     South Korea ML Ops Market Outlook

6.3.4.1.         Market Size & Forecast

6.3.4.1.1.             By Value

6.3.4.2.         Market Share & Forecast

6.3.4.2.1.             By Solutions

6.3.4.2.2.             By Product Focus

6.3.4.2.3.             By Task

6.3.4.2.4.             By Component

6.3.4.2.5.             By Type

6.3.4.2.6.             By Organization Size

6.3.4.2.7.             By End Use

6.3.5.     Australia ML Ops Market Outlook

6.3.5.1.         Market Size & Forecast

6.3.5.1.1.             By Value

6.3.5.2.         Market Share & Forecast

6.3.5.2.1.             By Solutions

6.3.5.2.2.             By Product Focus

6.3.5.2.3.             By Task

6.3.5.2.4.             By Component

6.3.5.2.5.             By Type

6.3.5.2.6.             By Organization Size

6.3.5.2.7.             By End Use

6.3.6.     Singapore ML Ops Market Outlook

6.3.6.1.         Market Size & Forecast

6.3.6.1.1.             By Value

6.3.6.2.         Market Share & Forecast

6.3.6.2.1.             By Solutions

6.3.6.2.2.             By Product Focus

6.3.6.2.3.             By Task

6.3.6.2.4.             By Component

6.3.6.2.5.             By Type

6.3.6.2.6.             By Organization Size

6.3.6.2.7.             By End Use

6.3.7.     Vietnam ML Ops Market Outlook

6.3.7.1.         Market Size & Forecast

6.3.7.1.1.             By Value

6.3.7.2.         Market Share & Forecast

6.3.7.2.1.             By Solutions

6.3.7.2.2.             By Product Focus

6.3.7.2.3.             By Task

6.3.7.2.4.             By Component

6.3.7.2.5.             By Type

6.3.7.2.6.             By Organization Size

6.3.7.2.7.             By End Use

7.    Europe & CIS ML Ops Market Outlook

7.1.  Market Size & Forecast          

7.1.1.     By Value

7.2.  Market Share & Forecast

7.2.1.     By Solutions

7.2.2.     By Product Focus

7.2.3.     By Task

7.2.4.     By Component

7.2.5.     By Type

7.2.6.     By Organization Size

7.2.7.     By End Use

7.2.8.     By Country

7.3.  Europe & CIS: Country Analysis

7.3.1.     France ML Ops Market Outlook

7.3.1.1.         Market Size & Forecast

7.3.1.1.1.             By Value

7.3.1.2.         Market Share & Forecast

7.3.1.2.1.             By Solutions

7.3.1.2.2.             By Product Focus

7.3.1.2.3.             By Task

7.3.1.2.4.             By Component

7.3.1.2.5.             By Type

7.3.1.2.6.             By Organization Size

7.3.1.2.7.             By End Use

7.3.2.     Germany ML Ops Market Outlook

7.3.2.1.         Market Size & Forecast

7.3.2.1.1.             By Value

7.3.2.2.         Market Share & Forecast

7.3.2.2.1.             By Solutions

7.3.2.2.2.             By Product Focus

7.3.2.2.3.             By Task

7.3.2.2.4.             By Component

7.3.2.2.5.             By Type

7.3.2.2.6.             By Organization Size

7.3.2.2.7.             By End Use

7.3.3.     United Kingdom ML Ops Market Outlook

7.3.3.1.         Market Size & Forecast

7.3.3.1.1.             By Value

7.3.3.2.         Market Share & Forecast

7.3.3.2.1.             By Solutions

7.3.3.2.2.             By Product Focus

7.3.3.2.3.             By Task

7.3.3.2.4.             By Component

7.3.3.2.5.             By Type

7.3.3.2.6.             By Organization Size

7.3.3.2.7.             By End Use

7.3.4.     Italy ML Ops Market Outlook

7.3.4.1.         Market Size & Forecast

7.3.4.1.1.             By Value

7.3.4.2.         Market Share & Forecast

7.3.4.2.1.             By Solutions

7.3.4.2.2.             By Product Focus

7.3.4.2.3.             By Task

7.3.4.2.4.             By Component

7.3.4.2.5.             By Type

7.3.4.2.6.             By Organization Size

7.3.4.2.7.             By End Use

7.3.5.     Russia ML Ops Market Outlook

7.3.5.1.         Market Size & Forecast

7.3.5.1.1.             By Value

7.3.5.2.         Market Share & Forecast

7.3.5.2.1.             By Solutions

7.3.5.2.2.             By Product Focus

7.3.5.2.3.             By Task

7.3.5.2.4.             By Component

7.3.5.2.5.             By Type

7.3.5.2.6.             By Organization Size

7.3.5.2.7.             By End Use

8.    North America ML Ops Market Outlook

8.1.  Market Size & Forecast          

8.1.1.     By Value

8.2.  Market Share & Forecast

8.2.1.     By Solutions

8.2.2.     By Product Focus

8.2.3.     By Task

8.2.4.     By Component

8.2.5.     By Type

8.2.6.     By Organization Size

8.2.7.     By End Use

8.2.8.     By Country

8.3.  North America: Country Analysis

8.3.1.     United States ML Ops Market Outlook

8.3.1.1.         Market Size & Forecast

8.3.1.1.1.             By Value

8.3.1.2.         Market Share & Forecast

8.3.1.2.1.             By Solutions

8.3.1.2.2.             By Product Focus