CAST AI Group Inc.
03/18/2026 | Press release | Distributed by Public on 03/18/2026 08:22
Cast AI Named a Leader in G2 Spring 2026 Reports for Cloud Cost Management and Auto Scaling
Cast AI, the leading automation platform valued at over $1 billion, today announced it has been recognized as a Leader in G2's Spring 2026 Grid® Reports for Cloud Cost Management and Auto Scaling, earning top rankings and 20 badges across 36 reports based on verified customer reviews.
G2, the world's largest and most trusted software marketplace, evaluates products based entirely on authentic user feedback. The Leader designation is reserved for vendors that demonstrate both exceptional customer satisfaction and significant market presence.
#1 Rankings Across Key Categories
Cast AI achieved #1 rankings in multiple critical categories, demonstrating market leadership in both cloud cost optimization and infrastructure automation:
- Grid® Report for Cloud Cost Management | Spring 2026
- Mid-Market EMEA Regional Grid® Report for Cloud Cost Management | Spring 2026
- Europe Regional Grid® Report for Cloud Cost Management | Spring 2026
- EMEA Regional Grid® Report for Cloud Cost Management | Spring 2026
- Momentum Grid® Report for Auto Scaling | Spring 2026
- Usability Index for Auto Scaling | Spring 2026
- Results Index for Auto Scaling | Spring 2026
- Relationship Index for Auto Scaling | Spring 2026
- Implementation Index for Auto Scaling | Spring 2026
These #1 rankings underscore Cast AI's position as the category leader in autonomous Kubernetes optimization, validating the company's approach to infrastructure automation that goes far beyond traditional monitoring.
Leader Status Across Enterprise, Mid-Market, and Regional Segments
Cast AI achieved Leader recognition across market segments and geographies:
Leader Status:
- Grid® Report for Cloud Cost Management
- Mid-Market Grid® Report for Cloud Cost Management
- Enterprise Grid® Report for Cloud Cost Management
- Momentum Grid® Report for Cloud Cost Management
- Grid® Report for Auto Scaling
- Momentum Grid® Report for Auto Scaling
Exceptional Customer Satisfaction Scores
The numbers tell the story: Cast AI customers are overwhelmingly satisfied, with some of the highest ratings in the cloud infrastructure category.
Across the Spring 2026 G2 reports, Cast AI earned exceptional scores:
- 98% of users gave Cast AI 4 or 5 stars
- 100% of users believe Cast AI is headed in the right direction
- 93% of users would recommend Cast AI to their peers
These aren't just good scores. They're outstanding for enterprise infrastructure software, where complexity and operational challenges often lead to lower satisfaction ratings.
What are customers particularly happy about? Cast AI's highest-rated features include Ease of Use, Ease of Setup, Ease of Admin, and Quality of Support. These ratings reflect the platform's core promise: autonomous operations that actually work.
What Customers Are Saying
Customers highlight Cast AI's ability to eliminate overprovisioning, automate complex optimization tasks, and free engineering teams to focus on innovation rather than infrastructure management.
Fernando C, DevOps/CloudOps professional at an Enterprise organization, emphasized the dual benefits of cost and operational efficiency:
"Cast AI helps us solve problems of overprovisioning and low efficiency in our Kubernetes infrastructure, as it automatically optimizes resource usage and selects more suitable instances according to actual demand. This mainly translates into a reduction in cloud costs, along with improved performance and greater application stability. Additionally, by automating optimization tasks that previously required manual intervention, it reduces the operational burden on the team and allows us to focus on other priorities."
Saravanan M., DevOps Engineer at an Enterprise organization, highlighted the platform's autonomous capabilities:
"Cast AI eliminates over-provisioning and node fragmentation through aggressive, real-time bin-packing and automated rightsizing of CPU/memory requests. It automates the entire lifecycle of node provisioning and spot instance orchestration, including seamless fallbacks to on-demand instances during market interruptions. This transforms our Kubernetes clusters into a self-optimizing system, significantly reducing our cloud spend while freeing the team to focus on delivery pipelines rather than manual scaling policies."
Oded Sagie, SVP of R&D at a Mid-Market organization, summarized the business impact:
"Cast AI is solving the problem of inefficient Kubernetes resource utilization and unpredictable cloud costs. Before using it, we were overprovisioning to avoid performance risks, which resulted in wasted spend and constant manual monitoring. Cast AI automates cluster scaling, right sizing, and spot instance management, which reduces overprovisioning while maintaining reliability. This directly benefits us by lowering infrastructure costs, improving resource efficiency, and freeing our engineering team from repetitive operational tasks so they can focus on higher value initiatives."
Leadership Perspective
"Recognition from G2 is particularly meaningful because it comes directly from the customers using Cast AI in production every day," said Laurent Gil, Co-Founder and President of Cast AI. "Achieving Leader status across both Cloud Cost Management and Auto Scaling validates our vision that infrastructure optimization isn't about choosing between cost and performance; it's about autonomous systems that deliver both simultaneously. These customer satisfaction scores reflect our commitment to making cloud infrastructure fully autonomous, so engineering teams can focus on building products, not managing infrastructure."
CAST AI Group Inc. published this content on March 18, 2026, and is solely responsible for the information contained herein. Distributed via Public Technologies (PUBT), unedited and unaltered, on March 18, 2026 at 14:22 UTC. If you believe the information included in the content is inaccurate or outdated and requires editing or removal, please contact us at [email protected]