The recently published 2025 Machine Learning Emotional Footprint Report from global IT research and advisory firm Info-Tech Research Group highlights the top machineThe recently published 2025 Machine Learning Emotional Footprint Report from global IT research and advisory firm Info-Tech Research Group highlights the top machine

2025’s Top Machine Learning Platforms for Advancing AI Strategy Identified Through User Feedback by Info-Tech Research Group

The recently published 2025 Machine Learning Emotional Footprint Report from global IT research and advisory firm Info-Tech Research Group highlights the top machine learning platforms that help organizations accelerate AI adoption, enhance model performance, and improve operational efficiency. The report’s insights are based on feedback from users on the firm’s SoftwareReviews platform.

ARLINGTON, Va., Dec. 18, 2025 /PRNewswire/ – Info-Tech Research Group has released its 2025 Machine Learning Emotional Footprint Report, which identifies the top-performing platforms for the year. Drawing on in-depth user insights from Info-Tech Research Group’s SoftwareReviews platform, the report names four champion machine learning platforms that lead the market in value and user satisfaction.

Machine learning platforms help organizations make smarter and more informed decisions by transforming complex models, datasets, and workflows into clear and actionable insights. These platforms offer real-time visibility across the entire machine learning lifecycle, from data preparation and training to validation, deployment, and ongoing monitoring. This allows teams to improve model accuracy, streamline operations, and maintain strong governance.

Info-Tech’s Emotional Footprint measures high-level user sentiment. The report aggregates emotional response ratings across 25 questions, creating a powerful indicator of overall user feeling towards the vendor and product. The result is the Net Emotional Footprint, or NEF, a composite score that reflects the overall emotional tone of user feedback.

Data from 682 end-user reviews on Info-Tech’s SoftwareReviews platform was used to identify the top platforms for the 2025 Machine Learning Emotional Footprint Report. The insights published offer valuable guidance for organizations looking to strengthen their machine learning strategies and choose the platforms that best support their goals.

The 2025 Machine Learning Platform Champions are as follows:

  • Azure Machine Learning, +94 NEF, ranked high for being respectful.
  • Google Cloud Vertex AI, +94 NEF, ranked high for appreciating incumbent status.
  • Databricks, +95 NEF, ranked high for friendly negotiation.
  • AWS Machine Learning, +91 NEF, ranked high for its product enhancement features.

Analyst Insight:
“Organizations are rapidly expanding their use of artificial intelligence, and machine learning platforms have become an essential part of enterprise ecosystems by bringing discipline, transparency, and scalability to this growth,” says Reddy Doddipalli, senior technical counselor at Info-Tech Research Group. “Top-performing platforms excel at unifying data pipelines, auto-labeling, clarifying model performance, AI observability, and supporting dependable deployment at scale. Even teams with well-established AI practices gain measurable value from streamlined workflows, automated monitoring, and strengthened governance. For many organizations, selecting a leading machine learning platform is a direct step toward faster innovation, reduced operational friction, and more strategic outcomes from AI investments.”

User assessments of software categories on SoftwareReviews provide an accurate and detailed view of the constantly changing market. Info-Tech’s reports are informed by the data from users and IT professionals who have intimate experience with the software throughout the procurement, implementation, and maintenance processes. 

Read the full report: Top 2025 Machine Learning Platforms

For more information about Info-Tech’s SoftwareReviews, the Data Quadrant, or the Emotional Footprint, or to access resources to support the software selection process, visit softwarereviews.com.

About Info-Tech Research Group
Info-Tech Research Group is one of the world’s leading and fastest-growing research and advisory firms, serving over 30,000 IT, HR, and marketing professionals around the globe. As a trusted product and service leader, the company delivers unbiased, highly relevant research and industry-leading advisory support to help leaders make strategic, timely, and well-informed decisions. For nearly 30 years, Info-Tech has partnered closely with teams to provide everything they need, from actionable tools to expert guidance, ensuring they deliver measurable results for their organizations.

To learn more about Info-Tech’s HR research and advisory services, visit McLean & Company, and for data-driven software buying insights and vendor evaluations, visit the firm’s SoftwareReviews platform. 

Media professionals can register for unrestricted access to research across IT, HR, and software, and hundreds of industry analysts through the firm’s Media Insiders program. To gain access, contact pr@infotech.com.

For information about Info-Tech Research Group or to access the latest research, visit infotech.com and connect via LinkedIn and X. 

About SoftwareReviews
SoftwareReviews is a peer-review platform from Info-Tech Research Group, a global research and advisory firm. The platform provides verified end-user insights that help organizations evaluate software based on features, vendor experience, and overall value. In addition to end-user insights, the firm offers peer-driven resources and advisory services, including buyer reviews, marketing and product guidance, and go-to-market support. These offerings enable technology providers to better understand customer needs, refine product strategies, and clearly communicate differentiated value to the market.

Cision View original content to download multimedia:https://www.prnewswire.com/news-releases/2025s-top-machine-learning-platforms-for-advancing-ai-strategy-identified-through-user-feedback-by-info-tech-research-group-302646407.html

SOURCE Info-Tech Research Group

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