Digital.ai Release Reviews

Name: Digital.ai Release
Brand: Digital.ai
Rating: 4.1 (4 reviews)

4.1 out of 5

4 reviews
100% willing to recommend

418 followers

What is Digital.ai Release?

Automate, orchestrate, and gain visibility into your release pipelines at scale using Digital.ai Release, a release management tool that is designed for enterprises. Control and track releases, standardize processes, and bake compliance and security into your software release pipelines.

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Digital.ai Release is the #12 ranked solution in top DevSecOps solutions, #13 ranked solution in top Release Automation solutions, and #18 ranked solution in top Build Automation solutions. PeerSpot users give Digital.ai Release an average rating of 8.2 out of 10. Digital.ai Release is most commonly compared to GitLab: Digital.ai Release vs GitLab. Digital.ai Release is popular among the midsize enterprise segment, accounting for 57% of users researching this solution on PeerSpot. The top industry researching this solution are professionals from a educational organization, accounting for 55% of all views.

Helped 838,640 peers since 2012

Featured reviews

Navanath Gajare

DevOps Tech Lead at a financial services firm with 5,001-10,000 employees

Our company uses the solution to handle deployments for new releases. Whenever there is a new release, the solution creates a new provision template for deployment. We also orchestrate and manage all users. We integrate with other tools like GitHub, Jenkins, or Digital.ai Deploy to manage…

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Jeanne-Mari Chandran

Software Configuration & Deployment Specialist at a insurance company with 10,001+ employees

The basic setup is straightforward. However, because we have a very integrated system of work reception integrating with Bamboo, integrated also with BDD Cucumber tests and sync up into Xray for dashboards, that customization is quite involved and quite integrated. The basic setup is easy, but it can become more complex. Our application deployment used to take approximately an hour. With Digital.ai Release it is cut down to 10 minutes. The steps we took for the implementation started with ExcelR, we are able to easily configure the specific versions of applications that we want to deploy. ExcelR retrieves these versions from our Nexus Repository and allows us to simply specify which version to deploy to a particular environment. When we click the deployment button, ExcelR handles the rest of the process, including creating Jiras for tracking and auditing, sending notifications to relevant teams and channels about the deployment, and closing the Jira when the deployment is complete. This automation saves us a lot of time and effort. I rate the initial setup of Digital.ai Release an eight out of ten.

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Satish Jaiswal

DevOps Engineer at LTIMINDTREE

We start by creating documentation for all these tasks. Initially, this includes all the details of the artifacts and the database. Then, the developer updates these details. We perform the deployments using Digital.ai Release. What we do is input the artifact information, and it handles all the deployments in the lower environments, usually within a minute or up to five minutes. This way, we avoid the need to use Jenkins to locate the artifacts and then deploy them, which would take much more time. Here, we simply input all the artifact details once, and later, we only need to update the artifact version for deployment. This significantly reduces our time. Moreover, once the deployment is completed, Digital.ai Release automatically sends an email notification stating that the deployment is complete, and we can begin testing. So, that's how it works efficiently for us.

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Digital.ai Release mindshare

Product category:

As of February 2025, the mindshare of Digital.ai Release in the Build Automation category stands at 0.8%, down from 1.1% compared to the previous year, according to calculations based on PeerSpot user engagement data.

Build Automation

PeerAnalyst reports

Type	Title	Date
Category	Build Automation	Feb 21, 2025	Download
Product	Reviews, tips, and advice from real users	Feb 21, 2025	Download
Comparison	Digital.ai Release vs GitLab	Feb 21, 2025	Download
Comparison	Digital.ai Release vs Tekton	Feb 21, 2025	Download
Comparison	Digital.ai Release vs Jenkins	Feb 21, 2025	Download

Title	Rating	Mindshare	Recommending
GitLab	4.3	17.0%	97%	82 interviews Add to research
Jenkins	4.0	11.0%	87%	93 interviews Add to research

Valuable Features

"The time is also reduced because the manual work has tremendously decreased. We just have to click one button, and it will create everything for us."
"The most valuable feature of Digital.ai Release is its ability to communicate with various deployment systems, such as XLD and batch deployments, as well as integrate with tools, such as Flyway and Bamboo. We use Bamboo as our build orchestrator, and Digital.ai Release also integrates with Jira, another Atlassian solution. These capabilities make it a powerful tool for managing workflow, test automation, and other processes."
"The solution can apply one template across multiple applications."

Room for Improvement

"Currently, we put artifact details manually. What we could improve, in our case, is the deployment instruction base. Developers input all the information, including which artifact and where it needs to be deployed. What Digital.ai could do is automatically go to the deployment instruction page, take those artifact details, and implement them."
"Digital.ai Release could improve by having a better plugin that works with Guardian that we use for mainframe migrations. If there could be an interface or plugin for Guardian that would be beneficial."
"The solution is a little bit expensive."