When using Digital.ai Release, I would rate it a nine out of ten overall. I chose nine out of ten for Digital.ai Release because if they can improve its downsides, it takes some time to learn. There are a lot of configuration options, and setting up release workflows can be challenging, especially for someone new to the platform. If the user interface could also be simpler, particularly when managing approvals and complex release pipelines, it would be a ten out of ten. Regarding Digital.ai Release's AI capabilities, I rate its governance and security ten out of ten. Digital.ai Release is useful because security can be built into the release process instead of being treated as something we check at the end. We can include security scans, testing, and comprehensive checks as part of the release workflow before it goes into production. On the AI side, it helps us identify patterns and potential problems in the release processes, such as repeated deployment failures. I see any issue more as decision support to make important production decisions. Based on my experience, the accuracy and reliability of Digital.ai Release's output are quite high. The value gained is mainly in helping us spot patterns, identify possible issues, and make better decisions around the release. For instance, if the system sees repeated deployment failures or unusual patterns, it can help us focus on areas that need attention. However, we still have to validate important findings before taking action, especially for production releases, as there can be false alerts that could introduce risk, but it remains reliable. My advice for others looking into using Digital.ai Release is first to look at the current release process and identify where the most time is being lost. Do not just buy the platform because you want automation. Rather, it is important to know which approvals, testing steps, or handoffs you want to improve. I also recommend starting with one or two pilot applications instead of trying to move every resource onto the platform at once. This approach gives the team time to build workflows and test integrations before making adjustments. My overall rating for Digital.ai Release is nine out of ten.
Application Architect at a insurance company with 1,001-5,000 employees
Real User
Top 20
Jun 16, 2026
My advice to others looking into using Digital.ai Release is that it seems very flexible. I understand we are using Digital.ai Release's Jenkins integration, and for the Jenkins component, potentially I could switch to other solutions. It seems to me it is a flexible framework to release cloud-based resources, so it is a good option for this purpose. I would like to see more AI capability in Digital.ai Release because AI has improved our productivity in different areas of our daily working environment. When we do development using Copilot, I see improvements when we use the cloud to help us in our development. However, in Digital.ai Release, since I am not a frequent user, I do not see much integration with AI yet, and that is an area where I would like to see further development. I would rate this review as a nine out of ten.
Release Manager at a consultancy with 201-500 employees
Real User
Top 20
Jun 15, 2026
My advice for others looking into using Digital.ai Release is that it is a nice solution for corporate companies. It is particularly valuable when you have different roles interacting in the pipeline, and it provides an easy way to connect with other applications such as Jenkins and servers including Linux, Control-M, and others. As a user from a corporate company, the details of the configuration, possibilities, and features such as the mentioned AI capabilities are somewhat closed off to me. I would appreciate knowing more, and I wonder if you have any demo account or something I could use for a trial period. I also have a small company with solutions in AWS using Python and different Linux servers, Kubernetes, and similar technologies, and I would like to try to see how Digital.ai Release could be useful for my personal company. I gave this review a rating of eight out of ten.
I would suggest using Digital.ai Release because it is best suited for enterprise DevOps teams managing complex release pipelines, particularly for multi-team projects that require coordination between development, testing, and operations. I give Digital.ai Release a rating of 9.
Software Configuration Specialist at a insurance company with 10,001+ employees
Real User
Top 10
May 16, 2025
I provided a review on PeerSpot about Digital.ai Release two years ago, where I shared my opinion about Digital.ai Release. I am still working with Digital.ai Release and we still use their product. I have no idea about the pricing for Digital.ai Release, as I don't manage financials. Overall, I would give Digital.ai Release a rating of nine out of ten; there's always room for improvement, but it's really good. I can definitely recommend Digital.ai Release to other users. I am Jane-Marie Chuldron, working as a software configuration manager for Sanlam, and my email is jane-marie.chuldron@sanlam.com.za. I am fine with my review on PeerSpot being published with my personal name as my opinion, without contact details or my company name.
Regarding Digital.ai, you have to make automation a priority. You can integrate multiple tools with it, which you can use for various automation. However, it's not easy; you can't just get the software and start using it from day one. You have to learn how to use YAML files, how to integrate other applications, and how to create different tasks, like deployments, Jira tickets, or sending emails. There's a lot to learn, so you have to understand the process as well. I would recommend it. Overall, I would rate the solution a seven out of ten.
DevOps Tech Lead at a financial services firm with 5,001-10,000 employees
Real User
Dec 15, 2022
The solution requires little management and effectively automates deployments. The team spends less time deploying things ourselves. I recommend the solution and rate it a nine out of ten.
Senior, Workload Automation Analyst at a government with 501-1,000 employees
Real User
Nov 19, 2020
Even though we're not going to use the tool, I think we captured some ideas and we've moved forward with that. We've automated some of our backfilling, so it was influential and it did cause change within us. Overall, it's been a good experience. Overall, on a scale from one to ten, I would give XebiaLabs XL Release a rating of eight — nothing is perfect, there is always room for improvement.
Digital.ai Release enhances deployment pipelines, integrating with tools like GitHub and Jenkins. It enables coordination across development, testing, and production while reducing manual efforts, making it ideal for large projects.Digital.ai Release is designed to automate and orchestrate application deployments, offering features like email approvals, deployment notifications, and system communication with XLD. It supports integration with tools such as Bamboo, Jira, and MS Teams to create...
When using Digital.ai Release, I would rate it a nine out of ten overall. I chose nine out of ten for Digital.ai Release because if they can improve its downsides, it takes some time to learn. There are a lot of configuration options, and setting up release workflows can be challenging, especially for someone new to the platform. If the user interface could also be simpler, particularly when managing approvals and complex release pipelines, it would be a ten out of ten. Regarding Digital.ai Release's AI capabilities, I rate its governance and security ten out of ten. Digital.ai Release is useful because security can be built into the release process instead of being treated as something we check at the end. We can include security scans, testing, and comprehensive checks as part of the release workflow before it goes into production. On the AI side, it helps us identify patterns and potential problems in the release processes, such as repeated deployment failures. I see any issue more as decision support to make important production decisions. Based on my experience, the accuracy and reliability of Digital.ai Release's output are quite high. The value gained is mainly in helping us spot patterns, identify possible issues, and make better decisions around the release. For instance, if the system sees repeated deployment failures or unusual patterns, it can help us focus on areas that need attention. However, we still have to validate important findings before taking action, especially for production releases, as there can be false alerts that could introduce risk, but it remains reliable. My advice for others looking into using Digital.ai Release is first to look at the current release process and identify where the most time is being lost. Do not just buy the platform because you want automation. Rather, it is important to know which approvals, testing steps, or handoffs you want to improve. I also recommend starting with one or two pilot applications instead of trying to move every resource onto the platform at once. This approach gives the team time to build workflows and test integrations before making adjustments. My overall rating for Digital.ai Release is nine out of ten.
My advice to others looking into using Digital.ai Release is that it seems very flexible. I understand we are using Digital.ai Release's Jenkins integration, and for the Jenkins component, potentially I could switch to other solutions. It seems to me it is a flexible framework to release cloud-based resources, so it is a good option for this purpose. I would like to see more AI capability in Digital.ai Release because AI has improved our productivity in different areas of our daily working environment. When we do development using Copilot, I see improvements when we use the cloud to help us in our development. However, in Digital.ai Release, since I am not a frequent user, I do not see much integration with AI yet, and that is an area where I would like to see further development. I would rate this review as a nine out of ten.
My advice for others looking into using Digital.ai Release is that it is a nice solution for corporate companies. It is particularly valuable when you have different roles interacting in the pipeline, and it provides an easy way to connect with other applications such as Jenkins and servers including Linux, Control-M, and others. As a user from a corporate company, the details of the configuration, possibilities, and features such as the mentioned AI capabilities are somewhat closed off to me. I would appreciate knowing more, and I wonder if you have any demo account or something I could use for a trial period. I also have a small company with solutions in AWS using Python and different Linux servers, Kubernetes, and similar technologies, and I would like to try to see how Digital.ai Release could be useful for my personal company. I gave this review a rating of eight out of ten.
I would suggest using Digital.ai Release because it is best suited for enterprise DevOps teams managing complex release pipelines, particularly for multi-team projects that require coordination between development, testing, and operations. I give Digital.ai Release a rating of 9.
I provided a review on PeerSpot about Digital.ai Release two years ago, where I shared my opinion about Digital.ai Release. I am still working with Digital.ai Release and we still use their product. I have no idea about the pricing for Digital.ai Release, as I don't manage financials. Overall, I would give Digital.ai Release a rating of nine out of ten; there's always room for improvement, but it's really good. I can definitely recommend Digital.ai Release to other users. I am Jane-Marie Chuldron, working as a software configuration manager for Sanlam, and my email is jane-marie.chuldron@sanlam.com.za. I am fine with my review on PeerSpot being published with my personal name as my opinion, without contact details or my company name.
Regarding Digital.ai, you have to make automation a priority. You can integrate multiple tools with it, which you can use for various automation. However, it's not easy; you can't just get the software and start using it from day one. You have to learn how to use YAML files, how to integrate other applications, and how to create different tasks, like deployments, Jira tickets, or sending emails. There's a lot to learn, so you have to understand the process as well. I would recommend it. Overall, I would rate the solution a seven out of ten.
The solution requires little management and effectively automates deployments. The team spends less time deploying things ourselves. I recommend the solution and rate it a nine out of ten.
Even though we're not going to use the tool, I think we captured some ideas and we've moved forward with that. We've automated some of our backfilling, so it was influential and it did cause change within us. Overall, it's been a good experience. Overall, on a scale from one to ten, I would give XebiaLabs XL Release a rating of eight — nothing is perfect, there is always room for improvement.