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Machine Learning as a Service (MLaaS) Market Projected to Hit USD 304.82 billion at a 36.20% CAGR by 2032- Report by Market Research Future (MRFR)

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New York, USA, June 23, 2023 (GLOBE NEWSWIRE) — According to the research report published by Market Research Future (MRFR), “Machine Learning as a Service (MLaaS) Market Information Deployment Mode, By Organization Size, And By Region – Market Forecast Till 2032”. The Machine Learning as a Service (MLaaS) Market could thrive at a rate of 36.20% between 2023 and 2032. The market size will be reaching around USD 304.82 billion by the end of the year 2032.

Big data and machine learning enable Airbnb to deliver world-class service. Data science has played a significant role in enabling us to serve more than 80 million visitors globally and provide first-rate service.

Machine Learning as a Service (MLaaS) Market Synopsis:

Airbnb is able to uphold its core ideals while offering tailored service to each of its customers because to the knowledge that big data and machine learning generate. An analysis of the historical data offers precise, suggestive guidance on how to raise the bar for service and narrow the gap between what can be beneficial and profitable for the business and the customers.

The expanding use of IoT is what is driving the CAGR for Machine Learning as a Service (MLaaS) add-ons. The market will grow as IoT and automation usage increase. IoT operations guarantee the proper and safe operation of the hundreds or more devices connected to a company network as well as the timely and accurate collection of data.

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Although complex back-end analytics engines handle the labor-intensive data stream processing, outmoded techniques are frequently utilised to verify the data’s integrity. In order to take control of sizable IoT systems, a number of IoT platform technology vendors are improving their operations management capabilities.

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MLaaS Industry Key Players

  • Google
  • BigML
  • Microsoft
  • IBM
  • Amazon Web Services
  • AT&T
  • Ai
  • Yottamine Analytics
  • Ersatz Labs, Inc.
  • Sift Science, Inc

Scope of the Report – Machine Learning as a Service (MLaaS) Market:

Report Metrics Details
Market Size by 2032 USD 304.82 billion
CAGR during 2023-2032 36.20%
Base Year 2022
Forecast 2023-2032
Key Market Opportunities Increasing demand for MLaaS Market.
Key Market Dynamics A rise in the amount of heterogeneous data makes it feasible for the machine learning as a service (MLaaS) sector to flourish.

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Market Drivers:

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More businesses employ machine learning technology for data analytics as IoT-based technologies and solutions are adopted more quickly by businesses. MLaaS would thereby encourage IoT innovation. IoT connections are anticipated to grow overall from 12.7 billion in 2021 to 32.5 billion in 2030, with a CAGR of 14%, according to Ericsson. MLaaS is already linked to a number of sensors, but it will be crucial to automation and the Internet of Things.

An AIOps survey from 2019 titled “Status of Automation, Artificial Intelligence, and Machine Learning in Network Management” found that 85% of respondents’ companies used a variety of automation techniques. However, only 27% of respondents said their company was sufficiently prepared for 100% automation. However, more than 65% of study participants said that machine learning was important for network administration and that it will likely lead to further automation in the future. resulting in the growth of the Machine Learning as a Service (MLaaS) business.

Segmentation

Software tools, Cloud APIs, and Web-based APIs are included in the market segmentation for Machine Learning as a Service (MLaaS) based on component. With 35% of market sales, the cloud APIs sector dominated the market.

The market for machine learning services is likely to be driven by factors such as the expansion of end-use industries and application domains in developing countries.

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Large and small and medium businesses are included in the Machine Learning as a Service (MLaaS) market segmentation based on organisation size. The segment of small and medium-sized businesses produced the highest revenue (66%). Small firms that use IoT could save a lot of time on the laborious machine learning process.

Network analytics, predictive maintenance, augmented reality, marketing and advertising, risk analytics, and fraud detection are among the applications that make up the Machine Learning as a Service (MLaaS) market segmentation. The largest money was made in the marketing and advertising area.

To display clients products they are currently interested in, recommendation systems are used. The marketing work algorithm is as follows: Marketing experts create, assess, test, and examine hypothese. This venture is time- and labor-intensive, and the results are occasionally erroneous because information changes every second. Based on this data, marketers may utilise machine learning to make quick judgements.

Manufacturing, healthcare, BFSI, transportation, government, and retail are among the market segments for Machine Learning as a Service (MLaaS) that are based on end users. In 2022, the retail sector held the lion’s share, providing around 38% of the market revenue for machine learning as a service (MLaaS). The retail trade sector has seen the success of e-commerce. The retail industry is changing and requires greater contacts with customers.

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https://www.marketresearchfuture.com/reports/machine-learning-as-a-service-market-2505

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Regional Insights:

North America, Europe, Asia-Pacific, and the rest of the world are all included in the regional breakdown of the markets in the research. This market will be dominated by the North American Machine Learning as a Service (MLaaS) market segment since it has a strong infrastructure and the financial means to purchase an MLaaS solution. Additionally, it is anticipated that the market would grow during the projected period as a result of increased defence spending and developments in telecommunications technology.

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Browse through more Information And Communications Technology Research Reports.

About Market Research Future:

At Market Research Future (MRFR), we enable our customers to unravel the complexity of various industries through our Cooked Research Report (CRR), Half-Cooked Research Reports (HCRR), Raw Research Reports (3R), Continuous-Feed Research (CFR), and Market Research & Consulting Services.

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MRFR team have supreme objective to provide the optimum quality market research and intelligence services to our clients. Our market research studies by products, services, technologies, applications, end users, and market players for global, regional, and country level market segments, enable our clients to see more, know more, and do more, which help to answer all their most important questions.

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Artificial Intelligence

GEEKOM releases a perfect mini PCs with dual 2.5Gbps Ethernet ports – GEEKOM GT1 MEGA

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TAIPEI, Sept. 20, 2024 /PRNewswire/ — GEEKOM, a Taiwanese tech company also known as the Green Mini PC Global Leader, recently released a strong lineup of flagship mini PCs with Intel Core Ultra processors and dual Ethernet ports, making it possible for users to enjoy impeccable performance and superb networking functionalities at the same time.

One of these mini PCs is the GEEKOM GT1 Mega, which employs a beautiful aluminum chassis with plenty of I/O, including two full-function 40Gbps USB4 Type-C, six USB Type-A, 2 HDMI2.0, a 3.5mm audio jack, an SD card reader and dual Ethernet ports. The two Ethernet jacks are both of 2.5Gbps standard, which not only delivers high-speed and reliable internet connection for people’s daily computing chores, but also enables the mini PC to serve more sophisticated networking functionalities as a soft router, a virtual machines, a hardware firewall, or even a home server. Besides, dual Ethernet ports can separate internal and external network connections, providing logical and physical separation of trusted and untrusted network traffic and keeping data safe from potential cyber-attacks.
The GT1 Mega is powered by Intel’s latest and smartest Core™ Ultra processor (up to CoreTM U9-185H) and dual-channel DDR5-5600MHz RAM. Thanks to the new CPU, GPU, and NPU three tier multi-processing architecture, the mini PC is ready to harness the superpowers of Artificial Intelligence. It is compatible with more than 500 AI models across 20+ categories and supports high-performance low-power processing in a wide range of computing scenarios, which include enhancing facial features and blurring the background during video calls, removing the vocals from songs to create karaoke tracks, and generating large-scale images based on texts or voice commands. Basically, the GT1 Mega allows users to finish tasks that used to take hours or even days through only a few keystrokes!
The GEEKOM GT1 Mega,is now available on GEEKOM’s official website.
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Artificial Intelligence

Lucinity Partners with Sift for Unified Fraud and AML Case Management

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SAN FRANCISCO, Sept. 19, 2024 /PRNewswire/ — Lucinity and Sift have announced a partnership, unifying fraud and Anti-Money Laundering (AML) into Lucinity’s integrated FinCrime compliance platform for case management, agent-enabled workflow automation, and Generative AI.

Sift is an AI-powered fraud platform securing digital trust for leading global businesses. Its Global Data Network analyzes more than 1 trillion events and identity signals per year to prevent fraud across the entire consumer journey. Lucinity and Sift formed this new partnership to address the challenges of fragmented fraud and AML systems, aiming to centralize and enhance financial crime investigations.
Sift’s AI-powered solution will now be integrated into Lucinity’s platform. This collaboration enhances Lucinity’s ability to provide a seamless and efficient compliance solution. It allows teams to review and manage fraud alerts more effectively through Lucinity’s unified Case Management system, thanks to the native integration between the systems. Key benefits to Lucinity’s users include:
Real-Time Fraud Screening: Payments are screened for potential fraud in real time, utilizing Sift’s fraud detection capabilities.Automatic Payment Holds: Payments suspected of fraud are temporarily held, ensuring verification before processing.Streamlined Reviews: Compliance teams can conduct thorough reviews of flagged payments within Lucinity’s Case Management solution.Risk Level Adjustments: Fraud detection parameters can be customized to adjust sensitivity levels, adapting to emerging fraud trends and risk appetites.This partnership also enables users to leverage Lucinity’s Generative AI capabilities through the Luci copilot to investigate fraud cases more efficiently.
Udi Nessimyan, President and Chief Revenue Officer of Lucinity, comments, “One of the greatest challenges in fighting financial crime is fragmented systems and data. Our partnership with Sift helps address this challenge by providing a centralized platform for various case types, including AML, fraud, sanctions, and ad hoc cases. Our collaboration significantly enhances the productivity of investigation teams, reducing the time spent on cases from hours to minutes.”
Sift’s Chief Marketing Officer, Armen Najarian, emphasizes the collaborative effort to enhance financial crime prevention, stating, “Cybercriminals are increasingly leveraging AI to bypass traditional anti-money laundering and fraud controls, creating sophisticated and dynamic threats. To combat these evolving risks, companies must adopt a ‘fight fire with fire’ approach by leveraging AI-powered solutions. Through Sift’s partnership with Lucinity, businesses can stay ahead of fraudsters, ensuring robust protection against abuse and enabling fearless growth.”
About Sift: https://sift.com About Lucinity: https://lucinity.com
Media contact:Celina [email protected] +354 792 4321

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Artificial Intelligence

Employee Background Check Software Market Size to Grow USD 828.8 Million by 2030 at a CAGR of 4.9% | Valuates Reports

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BANGALORE, India, Sept. 19, 2024 /PRNewswire/ — Employee Background Check Software Market is Segmented by Type (Cloud-Based, On Premises), by Application (SMEs, Large Enterprises): Global Opportunity Analysis and Industry Forecast, 2024-2030.

The Global Employee Background Check Software Market was valued at USD 587 Million in 2023 and is anticipated to reach USD 828.8 Million by 2030, witnessing a CAGR of 4.9% during the forecast period 2024-2030.
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Major Factors Driving the Growth of Employee Background Check Software Market:
The employee background check software market is growing due to increasing demands for secure hiring processes and regulatory compliance, especially in industries such as finance, healthcare, and IT. As companies look to reduce risks associated with fraud, legal liabilities, and workplace safety, background checks are becoming a critical part of recruitment processes. The rise of remote work has further accelerated the need for digital solutions. However, challenges include concerns over data privacy and varying legal frameworks across regions, which may slow adoption in some areas.
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TRENDS INFLUENCING THE GROWTH OF THE GLOBAL EMPLOYEE BACKGROUND CHECK SOFTWARE MARKET:
Cloud-based background check software is gaining traction due to its scalability, remote access, and cost-effectiveness. With cloud-based systems, businesses can streamline their hiring processes, particularly when operating across multiple locations. The ability to access data and conduct checks in real-time is highly valuable for organizations managing large workforces or remote employees. The flexibility and lower upfront investment of cloud-based solutions make them popular among businesses seeking efficient and adaptable systems for their recruitment processes.
On-premises solutions remain important for organizations with strict security and data control requirements, such as those in government, defense, or finance. These companies often need complete ownership of their data, which on-premises software offers, reducing the risk of external breaches. Although it requires significant upfront investment and maintenance, on-premises software provides a high level of customization and security. It’s especially useful for businesses dealing with sensitive information and industries where compliance with local data protection laws is critical.
Large enterprises, particularly those operating in regulated industries like banking and healthcare, are the major adopters of employee background check software. These organizations deal with large volumes of hires, making streamlined background checks essential for compliance and operational efficiency. The ability to integrate background check systems with existing HR tools, such as applicant tracking systems, allows large companies to manage their recruitment processes more effectively. The need for comprehensive and accurate background checks is crucial for mitigating risk and ensuring legal compliance.
The rise in remote working has increased the demand for background check software that allows companies to vet employees regardless of their location. Digital background checks, particularly cloud-based ones, make it easier for organizations to screen remote workers efficiently. This trend is expected to continue as more companies adopt hybrid or fully remote work models, where geographical barriers no longer restrict talent acquisition but require thorough and remote-friendly verification processes.
As regulatory frameworks for employment practices become more stringent globally, businesses are increasingly relying on background check software to ensure compliance. Laws like the General Data Protection Regulation (GDPR) in Europe and the Fair Credit Reporting Act (FCRA) in the U.S. have made it mandatory for companies to conduct background checks within specific legal parameters. This has led to increased demand for software solutions that can automate these processes while maintaining compliance with regional and international laws.
A major trend in the employee background check software market is the integration of these solutions with human resources management systems (HRMS). Integrating background checks with HR software streamlines the hiring process by consolidating background checks, employee records, and onboarding into one system. This improves operational efficiency for businesses, particularly large enterprises that handle significant recruitment volumes. Integration with HRMS allows for real-time updates, making background screening an even more integral part of the hiring process.
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EMPLOYEE BACKGROUND CHECK SOFTWARE MARKET SHARE
North America dominates the market due to stringent employment regulations and widespread adoption across industries. Europe is another key region, driven by GDPR compliance and demand in finance and healthcare. The Asia-Pacific region is experiencing rapid growth due to increasing awareness of the importance of background checks, especially in countries like China and India, where digital hiring platforms are becoming more popular. The market is also expanding in the Middle East and Africa as businesses prioritize secure hiring practices.
Key Companies:
HireRightGoodHireCheckrSterlingHireologyINTELIFIGood EggPeopleG2VitayCertnGlobal HR ResearchVeritable ScreeningXrefZincPaycomADPVICTIGIntelliCorp (Cisive)SpringVerifyAsurintUniversalAssureHireVerified FirstHireSafePurchase Chapters: https://reports.valuates.com/request/chaptercost/QYRE-Auto-2A10579/Global_Employee_Background_Check_Software 
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DISCOVER MORE INSIGHTS: EXPLORE SIMILAR REPORTS!
–  Employer of Record Services market was valued at USD 128.2 Million in 2023 and is anticipated to reach USD 196 Million by 2030, witnessing a CAGR of 6.8% during the forecast period 2024-2030.
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–  Employee Productivity Tracking Software market is projected to reach USD 311.8 Million in 2029, increasing from USD 219 Million in 2022, with the CAGR of 5.2% during the period of 2023 to 2029.
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