MLOps Market Overview

A collection of procedures known as machine learning operations (MLOps) automates and streamlines machine learning (ML) deployments and processes. You can use machine learning and artificial intelligence (AI) as foundational skills to tackle challenging real-world issues and provide value to your clients.
MLOps is quickly gaining popularity among lovers of AI, ML engineering, and data science. According to this pattern, the Continuous Delivery Foundation SIG MLOps sets the administration of machine learning models apart from conventional software engineering.

The global MLOps market size was valued at USD 1.64 billion in 2023. It is estimated to reach USD 30.65 billion by 2032, growing at a CAGR of 38.45% during the forecast period (2024–2032).

Competitive Landscape

Some of the prominent players operating in the MLOps Market are 

  1. IBM Corp.
  2. Microsoft
  3. Google LLC
  4. DataRobot
  5. Amazon Web Services, Inc.
  6. Neptune Labs, Inc.
  7. Dataiku.
  8. ALTERYX, Inc.
  9. Hewlett Packard Enterprise Development LP
  10. GAVS Technologies N.A., Inc.

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Latest trends in MLOps Market report

  • Democratization of MLOps: A larger range of people, including non-technical stakeholders, can more easily utilize MLOps. More people are being able to contribute to the development of AI and ML thanks to sophisticated tooling, automated pipelines, and user-friendly platforms.
  • Convergence of MLOps and DevOps: A unified, cross-functional approach to software development is being formed by the growing integration of MLOps and DevOps. This convergence enhances teamwork, decreases deployment bottlenecks, and streamlines procedures.
  • Automation powered by AI and AutoML: Automation is transforming deployment, hyperparameter tuning, and model training. Data scientists may now more effectively investigate model architectures and algorithms thanks to the advancements in autoML.
  • The increasing prevalence of AI has led to a focus on creating ML models and MLOps procedures that are clear, comprehensible, and consistent with moral values. This is known as responsible AI and ethical MLOps.
  • Increasing Edge AI and On-Device Deployment: To enhance responsiveness, data privacy, and overall model performance, there is a growing trend toward installing machine learning models at the edge, or in closer proximity to the data source.
  • Combining with DataOps: To further streamline the machine learning lifecycle, MLOps is merging with DataOps, which is focused on guaranteeing data quality and improving data pipelines.
  • MLOps are anticipated to be widely adopted in several areas, including retail, banking, finance, and healthcare, as they develop and become more affordable.
  • Cloud-Based MLOps: Because they provide enterprises with scalability, flexibility, and cost-effectiveness, cloud-based MLOps solutions are becoming more and more popular.

Global MLOps Market: Segmentation

As a result of the MLOps Market segmentation, the market is divided into sub-segments based on product type, application, as well as regional and country-level forecasts.

  1. By Component
    1. Platform
    2. Service
  2. By Deployment
    1. Cloud
    2. On-premises
  3. By Organization Size
    1. SMEs
    2. Large Enterprises
  4. By Vertical
    1. BFSI
    2. Healthcare and Life Sciences
    3. Retail and E-Commerce
    4. IT and Telecom
    5. Energy and Utilities
    6. Government and Public Sector
    7. Media and Entertainment
    8. Others

The report forecasts revenue growth at all the geographic levels and provides an in-depth analysis of the latest industry trends and development patterns from 2022 to 2030 in each of the segments and sub-segments. Some of the major geographies included in the market are given below:

  • North America (U.S., Canada)
  • Europe (U.K., Germany, France, Italy)
  • Asia Pacific (China, India, Japan, Singapore, Malaysia)
  • Latin America (Brazil, Mexico)
  • Middle East & Africa

Regional Analysis

  • North America: Market Size: Over the course of the projection period, the MLOps market in North America is expected to increase at a Compound Annual Growth Rate (CAGR) of 41.0%, from USD 1.1 billion in 2022 to USD 5.9 billion by 2027.
    Key Players: IBM, Microsoft, Google, AWS, and HPE are some of the leading companies in the North American MLOps market.
  • Europe: Market Size: Growth in the European MLOps market is anticipated to be substantial, supporting the expansion of the market as a whole.
    Important Players: Neptune.ai, Comet, SparkCognition, Hopsworks, and ClearML are important players in the European market.
  • Asia-Pacific: Market Size: As a result of the growing use of AI and machine learning technologies, the MLOps market in this region is anticipated to expand significantly.
    Important Players: In the Asia-Pacific market, H2O.ai, Weights & Biases, Katonic.ai, Modzy, and Iguazio are some of the major companies.

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Key Highlights

  • In order to explain MLOps Market the following: introduction, product type and application, market overview, market analysis by countries, market opportunities, market risk, and market driving forces
  • The purpose of this study is to examine the manufacturers of MLOps Market, including profile, primary business, and news, sales and price, revenue, and market share.
  • To provide an overview of the competitive landscape among the leading manufacturers in the world, including sales, revenue, and market share of MLOps Market percent
  • In order to illustrate the market subdivided by kind and application, complete with sales, price, revenue, market share, and growth rate broken down by type and application
  • To conduct an analysis of the main regions by manufacturers, categories, and applications, covering regions such as North America, Europe, Asia Pacific, the Middle East, and South America, with sales, revenue, and market share segmented by manufacturers, types, and applications.
  • To conduct an investigation into the production costs, essential raw materials, and production method, etc.

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