Digital.ai Release Reviews

Name: Digital.ai Release
Brand: Digital.ai
Rating: 4.2 (5 reviews)

4.2 out of 5

5 reviews
100% willing to recommend

414 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 Release Automation solutions, #12 ranked solution in top DevSecOps solutions, and #19 ranked solution in top Build Automation solutions. PeerSpot users give Digital.ai Release an average rating of 8.4 out of 10. Digital.ai Release is most commonly compared to Microsoft Azure DevOps: Digital.ai Release vs Microsoft Azure DevOps. Digital.ai Release is popular among the large enterprise segment, accounting for 49% of users researching this solution on PeerSpot. The top industry researching this solution are professionals from a educational organization, accounting for 43% of all views.

Helped 851,604 peers since 2012

Featured Digital.ai Release reviews

Jeanne-Mari Chandran

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

The features I find most valuable in Digital.ai Release are the integration with MS Teams, because we have MS Teams channels that publish or push notifications to that. When we start deployments, it sends a notification to the people that we are doing a deployment to their environment. It notifies them when the deployment is started, completed, or if attention is required. I also appreciate the fact that it has plugins for Bamboo and I use lots of Gradle and JSON scripts, and we do SQL upgrades as well, triggering Flyway scripts via Bamboo, along with the integration with XLD and Jira; it's all Atlassian software. Regarding environment management capabilities, Digital.ai Release is mostly useful for me, as it is more application related and that is managed via my XLD dictionary. We have one artifact that is environment agnostic, which has placeholders that correspond to my XLD keys and values, and at deployment time, it substitutes the placeholders with those environment specific values. We don't need to make a specific deployment artifact for dev, test, or production; it is all the same artifact using environment variables, ensuring what we take to production is what was tested.

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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 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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Digital.ai Release mindshare

Product category:

As of May 2025, the mindshare of Digital.ai Release in the Build Automation category stands at 0.8%, down from 1.0% compared to the previous year, according to calculations based on PeerSpot user engagement data.

Build Automation

PeerResearch reports based on Digital.ai Release reviews

Type	Title	Date
Category	Build Automation	May 19, 2025	Download
Product	Reviews, tips, and advice from real users	May 19, 2025	Download
Comparison	Digital.ai Release vs GitLab	May 19, 2025	Download
Comparison	Digital.ai Release vs Tekton	May 19, 2025	Download
Comparison	Digital.ai Release vs Jenkins	May 19, 2025	Download

Title	Rating	Mindshare	Recommending
Microsoft Azure DevOps	4.1	N/A	95%	133 interviews Add to research
GitLab	4.3	15.9%	97%	84 interviews Add to research

Valuable Features

Digital.ai Release's valuable features include robust orchestration capabilities, integration with various deployment systems like XLD and documentation automation. Its built-in metrics assist in executive communication while facilitating cohesive workflows through integrations with tools such as Bamboo and Jira. The platform supports efficient environment management with artifact placeholders and environment-specific values. Notifications via MS Teams and rollback capabilities for error recovery enhance its usability. Load times are efficient, supporting smooth operations across multiple applications.

"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."
"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."

Room for Improvement

Digital.ai Release requires improvements in automating backfill processes, optimizing pricing strategies, and enhancing plugin compatibility for mainframe tools. Users find it expensive and overly complex, suggesting a streamlined version. There's also a need for better cloud capabilities to aid in migration, and the deployment process could benefit from automated artifact management. Additionally, the system might be upgraded with plugins for other deployment tools to simplify tasks.

"I would like to improve Digital.ai Release by exploring its cloud capabilities as we are currently in the middle of migrating to the cloud, but I actually have no idea what Digital.ai's cloud capabilities are."
"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."

Pricing

"The solution's license includes all features."
"Overall, the price is just too high; especially considering we're in the middle of a pandemic."

Popular Use Cases

Organizations utilize Digital.ai Release primarily to coordinate and manage software releases, handling tasks such as orchestrating deployments, managing templates, integrating with tools like GitHub and Jenkins, and supporting infrastructure and DevOps teams. It assists in moving software through development stages and optimizing processes, reducing manual effort and increasing efficiency by automating documentation and communication tasks, accommodating hundreds of users without immediate plans for expansion.

Service and Support

Digital.ai Release offers efficient customer service and support, according to users. Teams quickly resolve installation and configuration issues, ensuring someone is always available with answers. Large organizations in South Africa purchase comprehensive support options, reflecting their confidence. A multinational rates them highly for tech support, emphasizing the importance of high availability, data integrity, and security. Users express satisfaction with the assistance received, highlighting the effectiveness of Digital.ai Release's support services.

Deployment

Users found Digital.ai Release's initial setup straightforward despite some complexity due to terminology differences. Understanding jargon eased the process. Basic setup was rated highly, although integrating with systems like Bamboo and Xray for dashboards added complexity. Deployment time was significantly reduced, boosting efficiency. ExcelR facilitated easy application version management, with automation improving tracking and notifications. Experimentation with templates helped users learn.

Scalability

Digital.ai Release is perceived as having strong scalability capabilities, handling both small and large deployments effectively. Its ability to scale is rated highly, though it primarily depends on hardware resources. Organizations may need additional memory or resources for effective scaling. However, some note the absence of auto-scaling options, with capacity predetermined. With ratings between eight to ten for scalability and support for extensive operations, it serves a considerable number of users efficiently.

Stability

Users highlight Digital.ai Release as reliable and solid, providing consistency with minimal issues. Despite high marks for stability, some report occasional glitches, requiring manual intervention. These errors can cause frustration when deployments need to be handled by a separate team. However, it’s suggested that deploying to outdated systems such as IBM WebSphere could be partly responsible for any instabilities, indicating an external factor rather than an inherent flaw in Digital.ai Release itself.

These insights are based on the in-depth reviews provided by peers to help you make a better buying decision.

Download our Digital.ai Release Buyer's Guide for additional reliable information.