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Apptio One vs CAST AI comparison

 

Comparison Buyer's Guide

Executive Summary

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

Apptio One
Ranking in Cloud Cost Management
8th
Average Rating
8.0
Reviews Sentiment
6.1
Number of Reviews
3
Ranking in other categories
IT Financial Management (2nd)
CAST AI
Ranking in Cloud Cost Management
19th
Average Rating
8.0
Reviews Sentiment
9.2
Number of Reviews
1
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of January 2026, in the Cloud Cost Management category, the mindshare of Apptio One is 4.0%, down from 6.0% compared to the previous year. The mindshare of CAST AI is 1.8%, up from 1.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Cloud Cost Management Market Share Distribution
ProductMarket Share (%)
Apptio One4.0%
CAST AI1.8%
Other94.2%
Cloud Cost Management
 

Featured Reviews

Neil Anson - PeerSpot reviewer
Global IT Financial Architect at a manufacturing company with 10,001+ employees
A highly stable and scalable solution that provides good out-of-the-box reporting
I am using the latest version of Apptio One. Apptio One is deployed on-cloud in our organization. Apptio One's maintenance involves validating the model and the monthly data loads. I would recommend Apptio One to other users. Before choosing Apptio One, users should ensure they align their use cases to achieve specific and measurable targets. Overall, I rate Apptio One ten out of ten.
RA
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.

Quotes from Members

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

Pros

"The TBM model and the out-of-the-box reporting are the most valuable features of Apptio One."
"With Apptio One, the advantage lies in its no-code approach, eliminating the need to write scripts for data retrieval."
"Its most significant value lies in its ease of use which extends to both configuration and the subsequent deployment of additional components."
"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."
 

Cons

"Encouraging or providing more out-of-the-box solutions that cater to a wider audience could enhance the overall effectiveness of the application."
"However, a notable challenge is the requirement to obtain consistent raw data, especially when operating in multiple regions with varying data sets. Each region may have distinct field names or data setups, necessitating the standardization of data before loading it into Apptio One. In Apptio One, there are areas for improvement, particularly in addressing potential bugs. An instance of this is observed when transitioning changes from the development region to the staging or production region. In instances with larger datasets, the calculation process may experience delays. Once the calculation concludes, the process proceeds to the subsequent region, whether it be staging or production."
"The solution's reporting layer, advanced conditional formatting, and reporting features could be improved."
"The documentation of CAST AI can definitely be improved for first-time users."
 

Pricing and Cost Advice

"It comes with a considerable cost."
"Regarding the pricing structure for various products within Apptio, such as APE One or APE One Plus, the cost is intricately tied to the selected license. There are two distinct types of licenses available. Opting for the basic license provides access to APT1, while an alternative license, known as APL One Plus, encompasses additional features like Cloudability and other components. The specific features accessible depend on the chosen license."
"Apptio One is an expensive solution."
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Top Industries

By visitors reading reviews
Financial Services Firm
18%
Computer Software Company
11%
Government
9%
University
7%
No data available
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
No data available
 

Questions from the Community

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What is your experience regarding pricing and costs for CAST AI?
In terms of setup cost, licensing, and pricing, I find the experience good. It's enterprise-grade, and the pricing is usage-based with no heavy upfront setup cost, which makes the onboarding straig...
What needs improvement with CAST AI?
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 bec...
What is your primary use case for CAST AI?
Our main use case for CAST AI is that we use it as a cloud provider and for Kubernetes clusters. We are using secure access roles and all those requirements for right-sizing the containers' workloa...
 

Comparisons

 

Overview

 

Sample Customers

Nationwide Building Society, State of Washington, Nationwide Building Society, DIRECTV, CME Group, Swiss Re, Cox Automotive
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