CAST AI vs Spot comparison

CAST AI and Spot - A Flexera company are both solutions in the Cloud Cost Management category. CAST AI is ranked #31, while Spot - A Flexera company is ranked #7 with an average rating of 7.0. CAST AI holds a 1.8% mindshare in CCM, compared to Spot - A Flexera company’s 4.6% mindshare. Additionally, 100% of CAST AI users are willing to recommend the solution, compared to 100% of Spot - A Flexera company users who would recommend it.

CAST AI

Read 1 CAST AI review

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252 Comparison Views

100% willing to recommend

Spot

Read 3 Spot reviews

1,388 Views
708 Comparison Views

100% willing to recommend

CAST AI

Spot

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Executive SummaryUpdated on Oct 19, 2025

CAST AI and Spot are both competing within the cloud management landscape, providing solutions designed for optimizing cloud expenses and resources. CAST AI seems to have the upper hand due to favorable feedback on its pricing model and support, while Spot's extensive feature set offers potentially superior value for those seeking comprehensive functionalities.

Features: CAST AI offers automatic optimization, multi-cloud capabilities, and efficient cross-platform cost management. Spot provides real-time monitoring, predictive scaling, and robust cloud infrastructure management. CAST AI focuses on cost efficiency, whereas Spot prioritizes operational control and scalability.

Ease of Deployment and Customer Service: CAST AI provides an intuitive deployment process and comprehensive customer support. Spot offers a more complex deployment with granular control. CAST AI is recognized for its streamlined approach, while Spot caters to needs requiring high customization.

Pricing and ROI: CAST AI is linked with lower setup costs and consistent ROI due to effective resource management and reduced cloud expenses. Spot may have a higher initial pricing model but provides strong ROI with its extensive feature set. CAST AI is more financially accessible, while Spot demands a larger upfront investment with potentially higher long-term returns for larger operational needs.

To learn more, read our detailed Cloud Cost Management Report (Updated: December 2025).

Buyer's Guide

Cloud Cost Management

December 2025

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Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Categories and Ranking

CAST AI

Ranking in Cloud Cost Management

31st

Average Rating

8.0

Reviews Sentiment

9.2

Number of Reviews

Ranking in other categories

No ranking in other categories

Spot

Ranking in Cloud Cost Management

7th

Average Rating

8.6

Reviews Sentiment

7.5

Number of Reviews

Ranking in other categories

Cloud Management (32nd), Server Virtualization Software (15th), Cloud Operations Analytics (2nd), Cloud Analytics (4th), Compute Service (11th), Containers as a Service (CaaS) (6th)

Mindshare comparison

As of December 2025, in the Cloud Cost Management category, the mindshare of CAST AI is 1.8%, up from 1.5% compared to the previous year. The mindshare of Spot is 4.6%, up from 4.0% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Cloud Cost Management Market Share Distribution
Product	Market Share (%)
Spot	4.6%
CAST AI	1.8%
Other	93.6%

Cloud Cost Management

Featured Reviews

RahulArora

Global Head - DevOps and AIOps Startegist at a manufacturing company with 10,001+ employees

Automation has optimized Kubernetes costs and right-sizing cuts manual cluster work

CAST AI helps us with automated node provisioning, workload right-sizing, intelligent auto-scaling, and overall cost visibility of the containerized systems that we have on the cloud. The best features CAST AI offers are the Kubernetes auto-scaling mechanism, continuous analysis of the pod-level CPU and memory usage, and ensuring that workload right-sizing is being done and our nodes are not over-provisioned. Identifying inaccuracies in the resource request is what we find quite useful with CAST AI. It definitely saves time and money as well, along with peace of mind because CAST AI continuously analyzes the pod-level CPU and memory usages. This helps us to optimize the request and the limits adjustments on our usage pattern, and overall, right-sizing improves the packing and reduces the wasted compute that we have in the cloud. In terms of overall impact on the organization, CAST AI has definitely helped us optimize our Kubernetes resources and given us automation capabilities. It is definitely helping us reduce the manpower and overall compute which is wasted. We can definitely save these using CAST AI. We will be notified upfront and proactively about any wastages that are happening, or any cost leakages that are happening in our system.

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reviewer2784786

Global Hyperscaler Alliances Director at a tech vendor with 1,001-5,000 employees

Cloud optimization has transformed our cost control and now drives efficient FinOps decisions

The best features that Spot offers include automated cost optimization, advanced container and Kubernetes management, and extensions to security as well as compliance, AI-driven insights, and multi-cloud integration, enabling organizations to work across different cloud environments and benefit any customer.Spot's automated cost optimization works by continuously analyzing the workload and applying policies to minimize cloud spend without sacrificing performance. Spot automatically chooses the most cost-effective mix of pricing models such as spot instances, reserved instances, savings plans, and on-demand based on real-time demand and availability. Spot has positively impacted our organization by automating cloud resource management, which has significantly cut costs and improved efficiency. We have seen up to 70 percent savings, as well as better scalability, reliability, and tighter integration with AWS. This integration has opened several doors to the partner ecosystem, different marketplaces, and has allowed us to leverage programs while tapping into the Amazon network and ecosystem more effectively.

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Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Pros

"We observed a 20 to 30% reduction in Kubernetes infrastructure cost, node utilization is improved, and we could see a 60 to 70% reduction in our manual cluster optimization efforts that we used to put initially."

"The solution offers both block access and file access, making it a nice solution for customers."

"The solution helps us to manage and scale automatically whenever there is a limit to the increase in the application workflow."

"Spot has positively impacted our organization by automating cloud resource management, which has significantly cut costs and improved efficiency."

Cons

"The documentation of CAST AI can definitely be improved for first-time users."

"The solution doesn't have support from OCI, and it should start working to onboard OCI."

"There are no particular areas for improvement I can identify."

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Top Industries

By visitors reading reviews

No data available

Manufacturing Company

19%

Computer Software Company

17%

Healthcare Company

Financial Services Firm

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

Questions from the Community

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What do you like most about Spot Ocean?

The solution helps us to manage and scale automatically whenever there is a limit to the increase in the application workflow.

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What needs improvement with Spot Ocean?

Spot can be improved by adding deeper multi-cloud integrations, enhancing real-time security automation, and continuously making advancements based on customer feedback.

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What is your primary use case for Spot Ocean?

I have been using Spot for five years. My main use case for Spot is cloud optimization.We use Spot for optimization by leveraging real-time optimization as well as auto-optimization. The company al...

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Comparisons

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Compared 32% of the time

Turbo360 (Formerly Serverless360) vs CAST AI

Compared 30% of the time

VMWare Tanzu CloudHealth vs CAST AI

Compared 16% of the time

More CAST AI Competitors

IBM Turbonomic vs Spot

Compared 16% of the time

ProsperOps vs Spot

Compared 9% of the time

Flexera Cloud Cost Management vs Spot

Compared 8% of the time

Pump.co vs Spot

Compared 7% of the time

Zesty vs Spot

Compared 5% of the time

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Product Reports

Buyer's Guide

Cloud Cost Management

December 2025

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Buyer's Guide

Cloud Analytics

December 2025

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Also Known As

No data available

Spot Ocean, Spot Elastigroup, Spot Eco

Overview

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.

CAST AI

Spot provides dynamic workload management for cloud environments, offering cost optimization and enhanced performance. It stands out with its unique approach to managing resources efficiently.

Spot is designed to enhance cloud resource utilization and cost-effectiveness through intelligent workload management. With real-time analysis, Spot determines and deploys the most efficient resources, ensuring optimal performance for applications. Businesses benefit from reduced cloud expenses and increased operational efficiency, making it an essential tool for managing cloud infrastructure effectively.

What are the key features of Spot?

Automated Scaling: Automatically adjusts cloud resources based on demand and usage patterns.
Real-Time Monitoring: Provides continuous oversight to ensure optimal performance and operational efficiency.
Cost Optimization: Reduces expenses by utilizing spot instances and leveraging cost-effective cloud resources.
Seamless Integration: Easily integrates with existing cloud services and infrastructures.

What benefits should users look for in Spot?

Cost Reduction: Users can expect to see a significant decrease in cloud expenses.
Improved Efficiency: Enhancements in operational processes and workload management.
Resource Optimization: Better allocation and usage of cloud resources.
Scalability: Capability to handle increasing amounts of work effectively.

In finance, Spot ensures cost-effective cloud computing for trading platforms, while in e-commerce, it dynamically manages back-end processes. In the entertainment industry, Spot optimizes media streaming by deploying resources when user demand spikes. Each industry leverages Spot to maximize performance and minimize operational costs, demonstrating its versatility and reliability across sectors.

Spot - A Flexera company

Sample Customers

Information Not Available

Freshworks, Zalando, Red Spark, News, Trax, ETAS, Demandbase, BeesWa, Duolingo, intel, IBM, N26, Wix, EyeEm, moovit, SAMSUNG, News UK, ticketmaster

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December 2025

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