WEKA Named a 2025 Customers' Choice in Gartner® Peer Insights™ for File and Object Storage Platforms

CAMPBELL, Calif., May 30, 2025 /PRNewswire/ -- WEKA, the AI-native data platform company, announced that it has been recognized as a Customers' Choice in the 2025 Gartner^® Peer Insights^™ Voice of the Customer: File and Object Storage Platforms for a second time. The company received the Customers' Choice recognition based on feedback and ratings from verified enterprise customers across various industries who have hands-on experience working with the WEKA Data Platform.

WEKA's data platform software is purpose-built to manage unstructured datasets and accelerate AI model training, inference and HPC workloads, delivering microsecond latency performance at scale with a frictionless data architecture that gets faster, stronger, and more efficient as an AI infrastructure environment grows. The WEKA Data Platform runs virtually anywhere, providing seamless multitenancy and data portability across on-premises, cloud, edge, hybrid and multicloud environments.

WEKA received a 4.9 out of 5-star rating in both the overall customer experience and support experience categories. Ninety-eight percent of reviewers indicated that they would recommend the WEKA Data Platform.

"We are honored to be again recognized as a Gartner Peer Insights Customers' Choice for File and Object Storage Platforms," said Liran Zvibel, cofounder and CEO at WEKA. "Our customers' feedback fuels our business and strengthens our product development. Thank you to all WEKA customers who took the time to share their honest feedback. We could not have received this recognition without you."

A complimentary copy of the 2025 Gartner Peer Insights Voice of the Customer: File and Object Storage Platforms report is available from WEKA. To obtain a copy, visit weka.io/customerschoice.

Supporting Customer Quotes
"Exceptional level of support for a magnificent product. Solved many of the problems we were confronting previously. We cut costs by 20x per terabyte for our AI HPC cluster in the cloud, while increasing both performance and storage size." – Engineering Manager, Software Industry

"The standout feature of WEKA is undoubtedly its exceptional read/write performance. The speeds achieved during data operations significantly outpace industry standards, enabling our team to handle large datasets with ease and efficiency, especially to meet the tough demands of our trading team's requirements. This high performance has streamlined our workflows, reduced processing times and allowed us to focus on insights rather than waiting on data transfers." – Senior Site Reliability Engineer, Finance Industry

"WEKA solved a significant problem for our scale-out compute cluster storage needs. It was simple to install, easy to administer and blazingly fast." –Production Engineer, Media

(Note: Reviews may be edited for length and clarity.)

To read additional customer feedback about the WEKA platform, visit WEKA's profile on Gartner Peer Insights: https://www.gartner.com/reviews/market/file-and-object-storage-platforms/vendor/weka/product/weka-data-platform.

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About WEKA
WEKA is architecting a new approach to the enterprise data stack built for the era of agentic AI. The WEKA® Data Platform sets the standard for AI infrastructure, providing a cloud and AI-native foundation for enterprise AI that can be deployed anywhere with seamless data portability across on-premises, cloud, and edge environments. It transforms legacy data silos into dynamic data pipelines that dramatically increase GPU utilization, enabling AI model training, inference, and HPC workloads to run faster and more efficiently, and delivering microsecond latency performance at scale. WEKA helps the world's most innovative enterprises and research organizations accelerate time to market, discovery, and insights with AI, including 12 of the Fortune 50. Visit www.weka.io to learn more, or connect with WEKA on LinkedIn and X.
 
WEKA and the WEKA logo are registered trademarks of WekaIO, Inc. Other trade names used herein may be trademarks of their respective owners. 

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