I would like to see CAST AI improved with deeper and more intelligent answers and solutions, along with additional optimization and customization options. The customization option in particular could be enhanced to help further. Overall, the platform is very strong, and most improvements could include advanced customization, advanced reporting, and documentation on a large scale.
CAST AI can be improved in that automation policies require careful tuning. Sometimes it can be confusing for non-technical people or managers who are not familiar with technical details. However, it is good for technical people who are already into DevOps or cloud engineering. Spot strategies may need adjustment for sensitive workloads. The reporting and UI part can be somewhat better. Technical support can also be improved. Documentation is somewhat unclear sometimes, but not everywhere. There are many pros here, including easy onboarding, simple deployment, and excellent Kubernetes visibility, strong spot instance automation, and automated right-sizing. These features are very good for our organization because they reduce a lot of cost and reduce a lot of manual effort. However, some things can be improved, such as automation policies that require careful tuning and may need somewhat more help. Spot strategies can be improved, and some UI and documentation can also be improved.
Siem Engineer at a tech services company with 11-50 employees
Real User
Top 5
Jun 27, 2026
I would appreciate seeing CAST AI improved with more granular reporting, deeper cost allocation insights, and additional customization options for optimization policies. Overall, the platform is strong. The most needed improvements would be around reporting and advanced governance capabilities for large organizations. The reason I did not give it a perfect score is that I would still prefer to see more advanced cost reporting and workload-level analytics. Some additional improvements needed with CAST AI would include enhanced forecasting capabilities and more detailed workload-level cost analytics, which would be very useful.
I would like to see more granular reporting, deeper cost allocation insights, and additional customization options for optimization policies in CAST AI. Overall the platform is strong, and most improvements needed would be around reporting and advanced governance capabilities for larger organizations. Regarding CAST AI's AI capabilities, the governance and security controls are solid. It provides sufficient visibility into cluster changes and optimization actions, although more advanced policy would be beneficial. Enhanced forecasting capabilities and more detailed workload-level cost analytics would be useful improvements for CAST AI that I have not mentioned yet.
The limitations of CAST AI include reporting and customization options. I think they can improve in these areas, especially when some advanced settings require a learning curve, particularly for teams new to Kubernetes optimization. More detailed documentation and deeper visibility into certain optimization decisions would also be helpful.
General Manager at a manufacturing company with 10,001+ employees
Real User
Top 5
Dec 23, 2025
The documentation of CAST AI can definitely be improved for first-time users. When we are onboarding a new user, the team needs some time to tune the policies and build confidence in automation because it actively makes infrastructure-level changes that must be validated against the real production workloads. The user interface can definitely be optimized further. Support-wise, they are good.
CAST AI is revered for its powerful cloud optimization capabilities, notably in cost reduction, performance enhancement, and security strengthening. It automates resource management and scales operations efficiently, leading to significant organizational improvements in efficiency, cost savings, and smoother cloud integration and management.
I would like to see CAST AI improved with deeper and more intelligent answers and solutions, along with additional optimization and customization options. The customization option in particular could be enhanced to help further. Overall, the platform is very strong, and most improvements could include advanced customization, advanced reporting, and documentation on a large scale.
CAST AI can be improved in that automation policies require careful tuning. Sometimes it can be confusing for non-technical people or managers who are not familiar with technical details. However, it is good for technical people who are already into DevOps or cloud engineering. Spot strategies may need adjustment for sensitive workloads. The reporting and UI part can be somewhat better. Technical support can also be improved. Documentation is somewhat unclear sometimes, but not everywhere. There are many pros here, including easy onboarding, simple deployment, and excellent Kubernetes visibility, strong spot instance automation, and automated right-sizing. These features are very good for our organization because they reduce a lot of cost and reduce a lot of manual effort. However, some things can be improved, such as automation policies that require careful tuning and may need somewhat more help. Spot strategies can be improved, and some UI and documentation can also be improved.
I would appreciate seeing CAST AI improved with more granular reporting, deeper cost allocation insights, and additional customization options for optimization policies. Overall, the platform is strong. The most needed improvements would be around reporting and advanced governance capabilities for large organizations. The reason I did not give it a perfect score is that I would still prefer to see more advanced cost reporting and workload-level analytics. Some additional improvements needed with CAST AI would include enhanced forecasting capabilities and more detailed workload-level cost analytics, which would be very useful.
I would like to see more granular reporting, deeper cost allocation insights, and additional customization options for optimization policies in CAST AI. Overall the platform is strong, and most improvements needed would be around reporting and advanced governance capabilities for larger organizations. Regarding CAST AI's AI capabilities, the governance and security controls are solid. It provides sufficient visibility into cluster changes and optimization actions, although more advanced policy would be beneficial. Enhanced forecasting capabilities and more detailed workload-level cost analytics would be useful improvements for CAST AI that I have not mentioned yet.
CAST AI could be improved by adding some AI agent capabilities.Improving the documentation would help the platform reach a perfect rating.
The limitations of CAST AI include reporting and customization options. I think they can improve in these areas, especially when some advanced settings require a learning curve, particularly for teams new to Kubernetes optimization. More detailed documentation and deeper visibility into certain optimization decisions would also be helpful.
The documentation of CAST AI can definitely be improved for first-time users. When we are onboarding a new user, the team needs some time to tune the policies and build confidence in automation because it actively makes infrastructure-level changes that must be validated against the real production workloads. The user interface can definitely be optimized further. Support-wise, they are good.