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The Global Machine Learning Model Operationalization Management (MLOps) Market size is expected to reach $8.5 billion by 2028, rising at a market growth of 38.9% CAGR during the forecast period



New York, Jan. 25, 2023 (GLOBE NEWSWIRE) — announces the release of the report “Global Machine Learning Model Operationalization Management Market Size, Share & Industry Trends Analysis Report By Component, By Vertical, By Organization size, By Deployment Mode, By Regional Outlook and Forecast, 2022 – 2028” –
In addition, aligning models with business demands and regulatory standards is simpler.

MLOps is gradually becoming a stand-alone method for managing the ML lifecycle. It covers every lifecycle stage, including data collection, model building (using the software development lifecycle and continuous integration/delivery), deployment, orchestration, health, governance, diagnostics, and business metrics.

Machine learning technology solutions are being aggressively adopted by businesses to improve the customer experience and support maximizing profit. Market participants are implementing advanced data processing and integration strategies to gather insights and get a competitive edge over rivals. The use of MLOps in enterprises is still in its infancy.

As people become more aware of the advantages of doing so, there will likely be lucrative chances for market expansion. The demand for cutting-edge solutions for improved data management is fueled by the expanding usage of data science technologies for improvements in computing power, artificial intelligence, and system learning.

The well-known industry verticals, such as retail, healthcare, education, telecommunication, manufacturing, and financial institutions, have a significant demand for machine learning. Standardized models and workflows are made possible with the assistance of ML Ops. Additionally, it facilitates the simple implementation of machine learning technology anywhere, which is the primary factor in enterprises’ high preference for them.

COVID-19 Impact Analysis

The COVID-19 pandemic is anticipated to be aided by artificial intelligence technology. Several nations are using population surveillance techniques made possible by machine learning and artificial intelligence to track and trace COVID-19 cases. For instance, researchers in South Korea use geo-location information and surveillance camera footage to monitor coronavirus cases. In addition, data scientists use machine intelligence algorithms to anticipate the location of the next outbreak and notify the appropriate authorities, allowing for real-time illness tracking. This has permitted technologically advanced nations to put a speed breaker on the spread of the virus. Such active endeavors are projected to increase the demand for machine intelligence solutions during the upcoming period.

Market Growth Factors

ML should be standardized for efficient teamwork.

Manual data collection and reprocessing are inefficient and may yield unacceptable results. MLOps aids in automating the entire workflow of ML models. This comprises data collection, the model creation, testing, retraining, and deployment. MLOps assist businesses in reducing errors and saving time. For the company-wide adoption of ML models, IT and business professionals and data scientists and engineers are involved in cooperation.

Use of Machine Leading Expanded in The Financial Sector

Financial institutions possess a vast amount of client information. They may collect information on purchases, spending habits, platform usage, and geo-locational preferences in addition to standard banking information, such as bank account balances, to create a 360-degree image of the consumer. This enables the bank to offer goods and services that are particularly tailored to the customer’s requirements and preferences. Therefore, the growing use of ML in the financial industry will fuel the expansion of the MLOps market.

Market Restraining Factors

Lack of Expertise

While more SMBs in the machine learning as a service industry use cloud-based services, the time-consuming machine learning integration process will become significantly less time-consuming. It helps to enhance an organization’s efficiency without recruiting human resources by avoiding repetitive work. Organizations need now utilise MLOps in data management to collect and integrate the enormous volumes of data from several internal and external data sources and unite the data silos.

Components Outlook

Based on components, the Machine Learning Model Operationalization Management (MLOps) Market is categorized into Platform and Services. In 2021, the services segment recorded a sizable revenue share. MLOps solutions are being adopted by businesses worldwide to strengthen their customer interaction, brand recognition, and marketing initiatives. Organizations can effortlessly engage consumers, communicate more effectively, and broaden their reach using MLOps marketing tools.

Deployment Mode Outlook

Based on deployment mode, the Machine Learning Model Operationalization Management (MLOps) Market is classified into On-Premises and Cloud. The cloud category had the most revenue share in the market in 2021. To boost employee productivity, the cloud-based system enables worldwide IT task outsourcing. Three other types of cloud computing exist private, public, and hybrid. The public cloud’s rising popularity is primarily due to its numerous organizational advantages, including flexibility and scalability, remote access, simplicity, speedier installation, and many other benefits.

Organization Size Outlook

Based on organization size, the Machine Learning Model Operationalization Management (MLOps) Market is categorized into Large Enterprises and SMEs based on Organization Size. In 2021, the small and medium-sized business segment obtained a sizeable revenue share. This is because machine learning adoption enables SMEs to optimize their processes on a limited budget. Shortly, it is anticipated that AI and machine learning will be the key technologies that let SMEs access digital resources and save money on ICT.

Vertical Outlook

Based on vertical, the Machine Learning Model Operationalization Management (MLOps) Market is categorized into BFSI, Retail and eCommerce, Government and Defense, Healthcare and Life Sciences, Manufacturing, Telecom, IT and ITeS, Energy, and Utilities, Transportation and Logistics, and Others. The BFSI sector produced the highest revenue share in the market in 2021. However, most banks also experience considerable difficulties managing inert models, particularly in settings where application deployments could be more active and influential. MLOps, which essentially applies DevOps techniques and methods to machine learning, can assist banks in swiftly and effectively addressing some of these issues.

Regional Outlook

Based on geography, the Machine Learning Model Operationalization Management (MLOps) Market is classified into North America, Europe, Asia Pacific, and LAMEA. North America is anticipated to hold the most significant market share during the projection period. By market share, North America is one of the top regions for MLOps. MLOps in this region are expanding due to the use of ML technology by nations like the US and Canada in various application fields. The US is regarded as one of the key contributors to North American MLOps market.

The major strategies followed by the market participants are Product Launches. Based on the Analysis presented in the Cardinal matrix; Microsoft Corporation and Google LLC are the forerunners in the Machine Learning Model Operationalization Management (MLOps). Companies such as Amazon Web Services, Inc. (, Inc.), IBM Corporation, Hewlett-Packard enterprise Company are some of the key innovators in Machine Learning Model Operationalization Management (MLOps).

The market research report covers the analysis of key stake holders of the market. Key companies profiled in the report include Microsoft Corporation, Amazon Web Services, Inc. (, Inc.), Google LLC, IBM Corporation, Hewlett-Packard enterprise Company, Alteryx, Inc., Cloudera, Inc., DataRobot, Inc., Domino Data Lab, Inc., and, Inc.

Recent Strategies Deployed in Machine Learning Model Operationalization Management (MLOps)

Partnerships, Collaborations & Agreements

Sep-2022: Domino Data Lab has collaborated with Nvidia, a Chipmaker company, and NetApp, a data management and storage system provider. This collaboration is aimed to advance the latest solutions and reference architecture that would help data science and machine learning workloads that are operating in muli cloud and hybrid systems.

Mar-2022: Amazon collaborated with Virginia Tech, a public land-grant research university, and launched an initiative for ML and AI research. This collaboration would allow doctoral students who have applied for Amazon fellowships and are performing ML and AI research. Additionally, this would help the efforts of faculty members engaged in the field of research.

Feb-2022: Microsoft entered into a partnership with Tata Consultancy Services, an Indian company focusing on providing information technology services and consulting. Under the partnership, Tata Consultancy Services leveraged its software, TCS Intelligent Urban Exchange (IUX) and TCS Customer Intelligence & Insights (CI&I), to enable businesses in providing hyper-personalized customer experiences. CI&I and IUX are supported by artificial intelligence (AI), and machine learning, and assist in real-time data analytics. The CI&I software empowered retailers, banks, insurers, and other businesses to gather insights, predictions, and recommended actions in real-time to enhance the satisfaction of customers.

Mar-2021: Amazon partnered with Hugging Face, a company that develops tools for building applications using machine learning. Through this Partnership, the company would ease the use of Machine Learning models for organizations and provide advanced NLP features in comparatively lesser time.

Feb-2021: Amazon Web Services entered into a partnership with Salesforce, a cloud-based software company. The partnership enabled us to utilize a complete set of Salesforce and AWS capabilities simultaneously to rapidly develop and deploy new business applications that facilitate digital transformation. Salesforce also embedded AWS services for voice, video, artificial intelligence (AI), and machine learning (ML) directly in new applications for sales, service, and industry vertical use cases.

Product Launches and Product Expansions:

Dec-2022: Alteryx, Inc. launched Alteryx Machine Learning. This newly launched product consists of Time Series enhancements which would broaden the predictive power of the company’s machine learning product. The product also includes a user interface (UI) update with new model evaluation abilities creating the process of model development highly simple and intuitive.

Apr-2022: Hewlett Packard released Machine Learning Development System (MLDS) and Swarm Learning, their new machine learning solutions. The two solutions are focused on simplifying the burdens of AI development in a development environment that progressively consists of large amounts of protected data and specialized hardware. The MLDS provides a full software and services stack, including a training platform (the HPE Machine Learning Development Environment), container management (Docker), cluster management (HPE Cluster Manager), and Red Hat Enterprise Linux

May-2022: Hewlett Packard launched HPE Swarm Learning and the new Machine Learning (ML) Development System, two AI and ML-based solutions. These new solutions increase the accuracy of models, solve AI infrastructure burdens, and improve data privacy standards. The company declared the new tool a “breakthrough AI solution” that focuses on fast-tracking insights at the edge, with attributes ranging from identifying card fraud to diagnosing diseases.

Jan-2022: Domino Data Lab unveiled Domino 5.0, the first Enterprise MLOps solution, an end-to-end software suite optimized to run AI workloads with VMWare. This newly launched platform would help the end-to-end data science lifecycle and offer data scientists in using the tools of their choice.

May-2021: Google released Vertex AI, a novel managed machine learning platform that enables developers to more easily deploy and maintain their AI models. Engineers can use Vertex AI to manage video, image, text, and tabular datasets, and develop machine learning pipelines to train and analyze models utilizing Google Cloud algorithms or custom training code. After that, the engineers can install models for online or batch use cases all on scalable managed infrastructure.

Mar-2021: Microsoft released updates to Azure Arc, its service that brought Azure products and management to multiple clouds, edge devices, and data centers with auditing, compliance, and role-based access. Microsoft also made Azure Arc-enabled Kubernetes available. Azure Arc-enabled Machine Learning and Azure Arc-enabled Kubernetes are developed to aid companies to find a balance between enjoying the advantages of the cloud and maintaining apps and maintaining apps and workloads on-premises for regulatory and operational reasons. The new services enable companies to implement Kubernetes clusters and create machine learning models where data lives, as well as handle applications and models from a single dashboard.

Acquisitions and Mergers

Jul-2021: DataRobot took over Algorithmia, a machine learning operations platform. The acquisition of Algorithmia would strengthen DataRobot’s position as the preeminent provider of complete solutions in the MLOps space, focused on offering machine learning models into production.

Jun-2021: Hewlett Packard completed the acquisition of Determined AI, a San Francisco-based startup that offers a strong and solid software stack to train AI models faster, at any scale, utilizing its open-source machine learning (ML) platform. Hewlett Packard integrated Determined AI’s unique software solution with its world-leading AI and high-performance computing (HPC) products to empower ML engineers to conveniently deploy and train machine learning models to offer faster and more precise analysis from their data in almost every industry.

May-2021: IBM acquired Waeg, a Salesforce Consulting Partner in Europe. Through this acquisition, IBM would broaden IBM’s suite of Salesforce services and develop IBM’s AI and hybrid cloud strategy. Additionally, this acquisition is based on IBM’s continued investment in Salesforce consulting services to address the growing client requirements for experience-led business transformation and the latest customer engagement strategies supported by machine learning, data, and AI.

Scope of the Study

Market Segments covered in the Report:

By Component

• Platform

• Services

By Vertical


• IT & ITeS

• Manufacturing

• Retail & Ecommerce

• Government & Defense

• Healthcare & Life Sciences

• Telecom

• Energy & Utilities

• Travel & Tourism

• Others

By Organization size

• Large Enterprises

• SMEs

By Deployment Mode

• Cloud

• On-premise

By Geography

• North America

o US

o Canada

o Mexico

o Rest of North America

• Europe

o Germany

o UK

o France

o Russia

o Spain

o Italy

o Rest of Europe

• Asia Pacific

o China

o Japan

o India

o South Korea

o Singapore

o Malaysia

o Rest of Asia Pacific


o Brazil

o Argentina


o Saudi Arabia

o South Africa

o Nigeria

o Rest of LAMEA

Companies Profiled

• Microsoft Corporation

• Amazon Web Services, Inc. (, Inc.)

• Google LLC

• IBM Corporation

• Hewlett-Packard enterprise Company

• Alteryx, Inc.

• Cloudera, Inc.

• DataRobot, Inc.

• Domino Data Lab, Inc.

•, Inc.

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• Exhaustive coverage

• Highest number of market tables and figures

• Subscription based model available

• Guaranteed best price

• Assured post sales research support with 10% customization free
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Artificial Intelligence

Tata Elxsi and Telefónica Collaborate to Achieve True Cloud-Native Infrastructure Management, Revolutionising Telecommunications Landscape




BENGALURU, India and BARCELONA, Spain, Feb. 27, 2024 /PRNewswire/ — Tata Elxsi and Telefónica proudly announce a groundbreaking achievement in the realm of the automation of cloud infrastructure for telecommunications, with the successful implementation of true cloud-native infrastructure management powered by ETSI Open-Source MANO (ETSI OSM). This milestone represents a significant evolution in network management, enabling operators to build intent-driven network systems with unprecedented efficiency and agility.

Through this collaboration, Tata Elxsi and Telefónica have enhanced the capabilities of OSM, introducing innovative features such as infrastructure automation, serverless operations execution environments, and the deployment of multi-cloud Platform-as-a-Service (PaaS) solutions. These advancements mark a new phase in the evolution of Telco Cloud technologies and signify a commitment to driving digital transformation across the telecommunications industry.
The integration of OSM with Tata Elxsi’s award-winning NEURON platform represents a pivotal moment in multi-domain transformation towards autonomous network systems. NEURON’s business intent-driven functionalities, coupled with OSM’s platform, provide operators with unparalleled control and flexibility in managing complex infrastructures.
“In our collaboration with Tata Elxsi, our objective is to advance the boundaries of technology and standardization, propelling operators towards cloud-native agility,” emphasised Francisco-Javier Ramón, Multicloud Tools Manager in gCTIO Unit at Telefónica.
“We are thrilled to partner with Telefónica to revolutionize the orchestration landscape,” commented B. Ramesh Ramanathan, Principal Architect, CTO Office at Tata Elxsi. “This collaboration enhances our presence within the open-source community and propels NEURON towards the realm of 5G and beyond and autonomous networks.”
The strategic collaboration between Tata Elxsi and Telefónica sets the stage for future advancements in Telco Cloud technology, paving the way for cutting-edge solutions that address the evolving needs of the telecommunications industry.  Powered by OSM, NEURON now possesses the capability to seamlessly integrate infrastructure, services, security, networking, and configuration into a unified, intent-driven deployment.
Please visit MWC Hall 2 – 2A53MR to see the joint demonstration by Telefónica and Tata Elxsi.
About Tata Elxsi
Tata Elxsi is a global design and technology services company that blends technology, creativity, and engineering to help customers transform ideas into world-class products and solutions. With expertise in industries such as automotive, broadcast, communications, healthcare, and more, Tata Elxsi is committed to driving innovation and delivering value to its clients worldwide. For more information, visit
About Telefónica:
Telefónica is a leading telecommunications company operating in Europe and Latin America. With a presence in over 15 countries and a customer base exceeding 350 million, Telefónica is committed to providing cutting-edge solutions and services that enable individuals, businesses, and communities to connect and thrive in the digital world.

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Artificial Intelligence

Netcore Unbxd’s Strategic Expansion in Europe Fuels 150% Revenue Growth, Redefining Ecommerce in Europe




LONDON, Feb. 27, 2024 /PRNewswire/ — Netcore Unbxd, a leading AI-powered Commerce Search and Product Discovery landscape player, proudly announces exceptional growth in the UK and European markets. This growth which has tripled in the last year, is marked by the successful onboarding of market-leading retailers, including Waitrose, Unilever Europe, Camper Footwear, Dobbies, Alohas, OceansApart, Goodform, and ResMed Europe. What sets this accomplishment apart is its tangible impact on the retailer’s bottom line, as they leverage the advanced capabilities of Netcore Unbxd’s platform, resulting in an impressive 40% surge in revenue and a substantial 25% increase in conversions.

As a wholly owned subsidiary of Netcore Cloud Pvt Ltd, Netcore Unbxd has strategically scaled its teams across key markets in the UK, France, Spain, and Portugal. Unbxd’s data infrastructure spans five regions, including one in the EU. Additionally, the region has established a comprehensive Go-To-Market (GTM) team comprising skilled professionals in customer success, account management, and sales to reinforce its commitment to providing exceptional services and support to its expanding clientele.
Netcore Unbxd’s success lies in the compelling stories of its customers, which include:
Fishpools, a significant player in the UK furniture industry, experienced a 51% increase in Average Order Value (AOV) and a 20% surge in search-related revenue within 12 months of implementing the Unbxd platform.Wex Photo Video, a leading electronics retailer, saw a remarkable 35% reduction in bounce rates within the same period.The company’s recognition as a leader in the Forrester Wave report in the Commerce Search and Product Discovery category in Q3 of 2023 further solidifies its position in the market. This is in addition to Netcore’s previous recognition as a top vendor in Email Marketing Services (Q1 2022) and Cross-Channel Marketing (Q1 2023).
Netcore Unbxd’s advanced AI technology empowers retailers to deliver highly personalised shopping experiences, optimising product discovery and ensuring a seamless shopper journey. The region’s platform has been highly successful, offering enterprise features such as omnichannel search, natural language processing (NLP) models, and multi-language understanding. Recent collaborations with industry leaders such as Unilever and Waitrose highlight the platform’s effectiveness across diverse UK and European sectors.
Nishant Jain, COO of Netcore Unbxd, stated, “Our vision is to revolutionise the ecommerce landscape by leveraging AI technologies like large language models (LLMs) and vector models to enhance product discovery. Netcore Unbxd, a platform designed for enterprise retailers, has observed a significant 150% growth in revenue within the region over the past year.”
Laura Burbedge, Director of Online at Waitrose, said, “We know that our customers are busy and have lots of demands on their time – they need to be able to fill their online shopping trolley quickly and easily with minimal effort. Through working with Unbxd we have already seen a significant improvement in customer satisfaction with our search feature, with more personalised results.”
As AI continues to evolve in ecommerce, Netcore Unbxd remains well-positioned to leverage innovative solutions that empower businesses to stay ahead of the curve.
About Unbxd
Netcore Unbxd is a cutting-edge AI-powered product discovery platform that elevates the ecommerce experience with personalised interactions. By providing a range of solutions, including contextually relevant Search, Personalisation, and Product Recommendations, alongside an intelligent Product Information Management (PIM) platform and an intuitive merchandising console, Unbxd offers brands the tools to optimise their ecommerce objectives. Noteworthy global brands such as Unilever, MattressFirm, Waitrose, Advance Auto Parts, Dillard’s, The Children’s Place, HSN, and Wex have trusted Unbxd. Across the world, Unbxd consistently delivers exceptional shopping journeys to countless online visitors at scale.
Media Contact:Mekhala [email protected] 

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ZwickRoell selects IFS Cloud to drive operational efficiency and support growth




IFS Cloud ERP will streamline ZwickRoell’s processes to reduce complexity and improve efficiencies to build business resilience.
LONDON, Feb. 27, 2024 /PRNewswire/ — IFS, the global cloud enterprise software company, today announced that ZwickRoell Gmbh & Co.KG, a leading worldwide manufacturer of materials testing equipment, has selected IFS Cloud in a strategic move to harmonize its business processes and deliver enhanced visibility across its operations.

The move to IFS Cloud was driven by the need to modernize its current Enterprise Resource Planning (ERP) and Customer Relationship Management (CRM) solution, which could no longer meet the business’ requirements needed to support its strategic growth plans.  Amid industry challenges, including global supply chain disruption, meeting sustainability goals and readiness for increased automation, ZwickRoell sought a new solution that would simplify its daily operations and eliminate existing IT operating risks.
IFS Cloud will enable the company to harmonize its disparate systems and simplify processes across its operations, driving continuous improvements and efficiency. With IFS Cloud, ZwickRoell will benefit from a single, composable digital platform that is designed to fit the needs of its complex manufacturing cycle today, from product development through to service and maintenance, and scale in future.
A key advantage of IFS Cloud is its evergreen model, which allows ZwickRoell to seamlessly integrate composable business applications across ERP, Enterprise Asset Management (EAM) and Field Service Management (FSM) as needed, enabling a solid data foundation across organization, and therefore delivering faster time to insight and minimizing costs. IFS Cloud will also enable the company to easily integrate users from MS Dynamics CRM systems, one of ZwickRoell’s key requirements.
Klaus Cierocki, CEO of ZwickRoell, said: “We are excited to begin a new chapter with IFS. Their manufacturing industry expertise and leading enterprise software differentiated them during the competitive selection process and they have given us complete confidence that they will support. IFS Cloud will provide us with the single platform that we knew was necessary to properly support our entire manufacturing and production cycle, ultimately helping us deliver better value to our customers and to build resiliency and agility into our business.”
Frank Beerlage, Managing Director DACH, IFS, said: “ZwickRoell is a strong family-run organization with traditions reaching back 160 years. Its values of honesty and fairness and its commitment to its customers are deeply aligned with IFS’s own mission. Globally, we are seeing manufacturers are increasingly accelerating their adoption of cloud-enabled solutions to enable the agility needed in the face of global challenges. We look forward to partnering with ZwickRoell on their digital transformation journey with IFS Cloud a core part of their strategic growth plans.”
The scale of deployment will include 1,390 users and two sites in Germany and Austria, with an 18-month global rollout to follow.
About ZwickRoell
For more than 160 years ZwickRoell has delivered outstanding technical performance, innovation and quality, in materials and component testing. ZwickRoell testing machines are used in R&D and quality assurance in more than 20 industries with one common goal – reliable test results This is ensured by a team of 1,900 dedicated employees in +50 countries, with competence, openness and passion.
Learn more about how automation and digitalization can make testing processes more efficient, simpler and safer at  
About IFS
IFS develops and delivers cloud enterprise software for companies around the world who manufacture and distribute goods, build and maintain assets, and manage service-focused operations. Within our single platform, our industry specific products are innately connected to a single data model and use embedded digital innovation so that our customers can be their best when it really matters to their customers-at the Moment of Service™. The industry expertise of our people and of our growing ecosystem, together with a commitment to deliver value at every single step, has made IFS a recognized leader and the most recommended supplier in our sector. Our team of over 6,000 employees every day live our values of agility, trustworthiness, and collaboration in how we support our 6,500+ customers. Learn more about how our enterprise software solutions can help your business today at
IFS Press Contacts:EUROPE / MEA / APJ: Adam GillbeIFS, Director of Corporate & Executive CommunicationsEmail: [email protected]: +44 7775 114 856
NORTH AMERICA / LATAM: Mairi MorganIFS, Director of Corporate & Executive CommunicationsEmail: [email protected]: +44 7018 607 299
The following files are available for download:
ZwickRoell PR Final,c3271329

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