Digital.ai Agility Reviews

I primarily use Digital.ai Agility for Agile project management, sprint planning, backlog management, and tracking team progress and deliveries. We use Digital.ai Agility for Agile project and portfolio management, including backlog management and sprint planning. It helps us monitor team progress in sprints and the capacity and release timelines. We also use dashboards to identify blockers and track delivery status. It provides better visibility and helps the team stay aligned with the Agile processes.

We also use Digital.ai Agility to track dependencies, manage defects, and coordinate work across teams. It helps us maintain clear ownership of tasks and provides full visibility into sprint progress and upcoming releases. Overall, it keeps our daily planning and delivery process more organized.

The best features offered by Digital.ai Agility are backlog and sprint planning, dependency management, and customizable dashboards. The dashboard provides strong visibility into velocity and delivery progress, defects, and team performance. I also appreciate the portfolio planning and roadmap because they help connect team-level work with a larger business scope. The integration capabilities make it easier to connect Digital.ai Agility with other tools in the development ecosystem.

Digital.ai Agility has improved our project visibility, sprint planning, and team coordination. It has helped us organize backlogs and priorities. We can track progress, dependencies, and delivery risk in one place. It has also reduced manual status reporting and improved communication. Overall, it has made our Agile delivery process more structured and predictable.

I would like to see more advanced reporting and analytics customization. The existing dashboards are useful for tracking velocity, backlog, and delivery, but deeper real-time insights would improve decision-making. I would also like simpler integrations and more flexibility, especially across large teams and complex projects.

Another improvement I would like is more flexible reporting and dashboard customization, especially for creating organization-specific metrics. More intuitive visualizations would also help.

Digital.ai Agility can be improved mainly by making reporting and dashboard customization more flexible and intuitive. I would also like simpler integrations with third-party tools and easier configurations of automated workflows. Better dependency visualizations and real-time alerts for delivery risk would help large teams identify blockers earlier. The user interface could also be simplified to make it easier for new users. Overall, these improvements would make day-to-day planning, reporting, and cross-team coordination more efficient.

There are a few areas where improvements are needed. I would like to see further improvements in user experience and navigation, especially making commonly used features easier to access for new users. More intuitive dashboard customization, better dependency visualization, and simpler third-party integrations would also help.

I have been working more than three years in my current organization using Digital.ai Agility.

In my experience, Digital.ai Agility is stable for day-to-day Agile project management. We have used it consistently for blocking, sprint, and release tracking without major stability issues. It also supports regular releases and ongoing maintenance. The main areas I would watch for performance are at very large scale and occasional UI navigation issues, which some users have also reported.

Digital.ai Agility scalability is effective for managing multiple team portfolios. It supports scaling Agile practices from individual teams to programs and the overall portfolio. The customer support is good and responsive, although there are sometimes delays that may take some time.

I rate customer support as eight out of ten.

Before Digital.ai Agility, we used Azure DevOps for development tracking, but it was less suitable for enterprise-level Agile planning and portfolio visibility. We switched to Digital.ai Agility because it provides better support for scaled Agile processes, dependency management, and organization.

The overall experience with pricing and licensing was fairly straightforward, although it required some planning around the number of users and the edition we needed. Since we used the on-premises version, the initial setup involved infrastructure, database configuration, authentication, and user provisioning. The license is user-based, and different editions provide different layers of integrations, analytics, and AI capabilities. Overall, the cost is reasonable for the enterprise Agile platform, particularly when you consider the visibility and planning capabilities it provides.

We have seen positive return on investment mainly through time-saving and improved productivity. We estimated Digital.ai Agility saves around five to ten hours per week, sometimes fifteen, by reducing manual status reporting and blocking and coordination. It also helped reduce unnecessary meetings by approximately fifteen to twenty percent since teams have better visibility into progress and blockers. We have not reduced headcount, but the same team can spend more time on developing and higher-value activities. Overall, the biggest benefits have been better delivery visibility, improved planning, faster decision-making, and reduced administrative effort. Digital.ai also cites an independent Forrester TEI study reporting one to two percent ROI for a composite organization, although that figure is not our own measured result.

We evaluated other options before choosing Digital.ai Agility. We compared Jira, Azure DevOps, and Rally mainly on enterprise planning, dependency management, reporting, integrations, and scalability.

I can advise others to use Digital.ai Agility for organizations. It is good for enterprise-level Agile planning across multiple teams and portfolios. Before implementing it, I would suggest starting with a few key use cases, such as backlog management, sprint planning, dependency tracking, and reporting. Make sure the team gets proper onboarding because some features can take time to learn. I would also recommend evaluating all required integrations and the deployment model early, especially for on-premises environments. Overall, it is a good choice if you need scaled Agile practices across multiple teams rather than just managing individual projects. I would rate this solution as seven out of ten.

My main use case for Digital.ai Agility is learning to create a dashboard and prompt engineering. I am trying to automate my tasks by automating the dashboard.

The best feature Digital.ai Agility offers me so far is that I write a prompt and receive the result for that.

I see the time saving with Digital.ai Agility, but I have not worked much on that, so I am still figuring out other features.

The response from Digital.ai Agility is a little bit slow and could be faster.

I have been familiar with Digital.ai Agility for the last two months.

4

You can use Digital.ai Agility for automating your tasks and creating your dashboard. I would rate this product an 8.

We were explaining how to set up the project itself, which describes the main use cases for Digital.ai Agility. This includes how to set up the workflow and how to manage and build a Kanban. I wanted to set up a Kanban, as I am a Kanban trainer. That is where my bias is towards Kanban. I was looking towards those capabilities where I can set a Kanban and get the team collaboration running, and how a full system can be set up.

When they demoed it, they showed it, and Digital.ai helped with those key queries regarding support for this type of setup. However, after that, I couldn't personally explore it, to be frank.

The solution is excellent for collaboration. From the agility point of view, they have very good sprint functionality, allowing you to set up sprints effectively. For Scrum teams, it is particularly good and easy to set up. With respect to sprints and getting metrics out, such as velocity and related measurements, the functionality is robust.

The Scrum boards are particularly effective. Based on my colleague's exploration and setup, I observed how easily the team was able to use it. The integration with that tool was particularly helpful.

It was not supporting some plugins. We wanted to migrate data that we were already using. The migration of data and getting it up and running from the legacy system took some time to get accustomed to.

I conducted the comparative analysis in 2024, within the last 12 months.

To set up the project, it took around 5 to 10 days for one of our projects. Initially, team members struggled, but afterward they adapted because everyone wanted different matrices, and they had many good options. That is where they were helping each other, which caused a slight delay. Other than that, setting up and using it was straightforward.

I would rate the support at seven out of ten. There were some communication gaps, specifically language barriers. We don't have local support in India, which was somewhat hampering.

Positive

Some customization was done regarding dashboards. Though it was around one year back, I'm not able to recall specific details as my team handled it. We received good support from Digital.ai Agility when we got the customized dashboard.

Digital.ai Agility has a bigger reach because it has many good integration points. It can be a one-stop solution for different needs, eliminating the need to use multiple pieces of software. However, it somewhat lacks from the marketing side, as people were not able to actually find the tool. Compared to Jira, it is more expensive. Jira has been giving some plugins these days, so people are content with what they have and are not investing in alternatives at present. Overall rating: 7 out of 10.

My team is currently using this solution as our backlog management tool. We have both an on-prem version and a public cloud. We have some traditional software development teams that are using the on-prem version. For our cloud version, right now we have non-software teams that are experimenting using Agile.

My team has been using the information on flow throughput and really looking at the larger stories that seem to take a lot longer to get through. We've been focused on improving our flow by breaking down the work into smaller chunks, and we're seeing a better throughput by doing that.

The most valuable thing is kind of the whole package together. The problem that we have with some of the other tools is that you have to buy 20 different plugins to get to the same capability that comes with the basic Agility capability.

There is room for improvement in getting the analytics portion of the solution more integrated with the rest of it.

The feature I would like to see is already in their newer licensing structure, and that's the live integration between Agility, Jira and Azure DevOps. That's the piece that I think is really valuable.

I have used this solution since it was called VersionOne back in 2010.

The stability is great. On occasion, we might have an issue with an incompatibility between the browser we're using and an update, but I have not had any issues with stability.

The solution is definitely scalable. The part of our organization that has the on-prem version probably has 12 different programs that are utilizing the same instance. We have about 2,500 users, and the entire organization accesses the tool.

Our goal is to increase usage and integrate the solution with Jira and Azure DevOps so that it sits on top of those and provides the higher level reporting, while the other teams can be working in Jira and Azure DevOps themselves.

On a scale of one to five, one being useless and five being perfect, I would give the tech support team a five. They tend to bend over backwards to provide us with the support that we need.

The initial setup was pretty straightforward, especially because you don't have to install anything with the cloud version.

Our deployment was done totally in-house. People could get into the tool by request, so our IT organization built a capability around requesting a user account so they could keep track of the users.

For our on-prem version, we have a maintenance team of about four people. We don't have any support staff for the cloud version.

We pay an annual fee based on a certain number of users and a rate that they gave us based on the number of users. Comparing the pricing to other products, I think this solution is in the middle. We really want to figure this out exactly, but I think if we were to take Jira and Azure DevOps and add up all of the add-ins needed to make them equivalent to what we have in Agility, we'd be paying about the same amount.

There are three tools, Digital.ai Agility, Jira, and Microsoft Azure DevOps, that we use in-house. Some of them are used more than others, but I found that Agility really has the full package which makes it easier because then teams don't have multiple things to be worried about. They can just get the one tool, and it has everything they need.

For others looking at implementing this product, my advice would be to take a systems-thinking view of the tool that you are looking for and make sure that you don't just go on price points.

I would rate this solution as a nine out of ten.

Our client uses Agility in a highly defined way, but it's not flexible. That's what we brought to the table. We handled the transition and mapping to take data from Jira and define a mapping solution in Digital.ai then push that upstream through to Clarity. Then we map the data to terminology because the hierarchies are very different between safe and agile.

They're a siloed organization, but the C-suite executives don't care, and they're not going to change that. They're unwilling to change their software, but they want reports, so they brought us in to reconcile this and push the data that they need to file their financial and forecasting reports. 

Even though if, in the strictest methodology sense, it didn't make that much sense but from reporting it was able to push the data. You wouldn't normally mach, for instance, a feature to an epic. You wouldn't do that because they're not at all the same. Things like that. They took terminology from Jira and they mapped it through to Agility and then took from Agility and mapped it up to Clarity. Actually, that interface was done first, the Agility to Clarity.

Agility is highly flexible. It can do much more than what our client is doing with it. They use it in a defined way. Some at that company have a much broader knowledge of agile and SAFe, but they're given applications and a mandated way to work. We had to work within their parameters and provide an accurate transition so the data would be mapped and pushed through.

In my work as a contractor, it's always frustrating when a client has multiple software applications that don't talk to each other and they all perform the same function. That presents a huge challenge between their IT groups. 

I did not use Agility before this current project, so I've only been using it for five or six months. I don't have a lot of hands-on experience with Agility, but I know Rally and Jira like the back of my hand. In the past, I worked on a project where we used seven versions of Jira, and I had to define a new methodology for the company. 

I've used Jira and Rally in the past, but we're using Digital.ai because it's crucial to our clients. Agility can scale from traditional agile to SAFe. Jira is great, but it's so customizable that you can get into trouble sometimes. At the same time, a lot of companies use Jira. I'm not a flag-waving fan of Jira, but it was the first one in that space, and that's how it got its hold in the market. Today, a lot of other great products have come along. I like Agility's scalability and flexibility. Honestly, I even like Rally better than Jira.

I wasn't involved with the setup. I just deal with the mapping components.

I rate Digital.ai Agility eight out of 10. Before implementing Agility, I would consider your use case and requirements. What were you going to use it for? Is it strictly internal? Are you working with lots of other clients that might default to Jira? 

I recommend defining your use case and deciding if Digital.ai Agility is suitable. I prefer Agility out of the three applications we work with because it has the most flexibility and can work at a higher level. It can also be scaled to profile for either SAFe or standard agile. Having something flexible and scalable gives a company a better opportunity to have a support application that can be used by different business units or technology units within the firm. I recommend doing your homework, looking at requirements, and making decisions. I rank Agility among the top five.

The Excel Release and Excel Deploy is part of the continuous delivery management stack and we use this to plan release automation. We also use it to standardize complex enterprise scale application deployments in complex environments, usually using virtual machines, containers and cloud infrastructure.

It has accelerated issue resolution and reduced lead times. It has helped to increase communication. From a high-level perspective, it has increased software delivery speed and reliability.

For visualization capabilities, the automation capabilities make it possible to support the different personas. The features and capabilities are great and come with excellent customer support.

The machine learning features are a new capability but could be improved. This is being worked on by Digital.ai currently. Multicolor simulation, specifically, could be improved. 

We have been using this solution for 5 years. 

It is a very stable solution.

It is a scalable solution. 

Currently, less than 10 staff are using this solution as the specific project we are using it for is in the early stages. 

The customer support is excellent. The one aspect that could be improved from a support perspective is the personas and machine learning capabilities.

Positive

We previously used Azure DevOps and have a strategy to integrate Agility.ai and Azure DevOps. We would use Agility.ai for enterprise planning in a scaled environment and Azure DevOps would be used on a team level. The integration of the two tools would be used for delivery pipelines.

We focused on cloud deployment and it took one week.

We used a vendor and we had a great experience

We evaluated Atlassian, which includes Jira, and Siemens Pularium.

Digital.ai Agility is an excellent tool to implement or adopt safe frameworks. Staff should have some knowledge and engage in training so that they know what they are doing. You need some time and experience to understand all the dependencies of the tool.

I would rate this solution a nine out of ten. 

We are using this solution to do the following:

• Define portfolio epics. 
• Define strategic themes and link portfolio items to them.
• Create features under portfolio epics.
  
• Create enabler epics that encapsulate governance artifacts.
  
• Create value streams (operational and development).
• Associate portfolio items with value streams.
• Roll up features and users' stories and tasks to achieve portfolio items and value streams.
• Create teams and associate tasks with teams.
• Assign points to user stories.
• Assign hours to tasks.
• Calculate the velocity of the team showing how many points they can take on in each iteration.

Digital.ai Agility helped our organization define the Enterprise Value Streams. These value streams account for all the activities that contribute to the bottom line of the organization.

In the Digital.ai Agility tool, you can derive all user stories, features, and epics from the top-level portfolio items and value streams. Any work that is done must contribute to the value streams, otherwise, it should be questioned why that effort is being executed.

The most valuable features are:

• The associations between the development tasks and how much these development tasks contribute to advancing the bottom line of the organization.
• The rolling up of work done on features to epics, both for portfolio epics and enabler epics.
• The ability to define multiple planning levels, so each team within the organization can use their own planning level without affecting the work of other teams.
• The ability to define iterations, including iteration planning, iteration closing, carry over, and tasks.
• It can generate reports showing a burndown chart, burnup chart, and the planned vs actual velocity.

The user interface can be improved by adding Save button to the popup windows that are displayed when you click on a child item. The current behavior is a new tab in your browser opens up and shows the child item content. It is intuitive to search for "Save" button after you make your changes but there is no "Save" button. You just need to close the tab and go back to the original tab and refresh and this is cumbersome. 

We have been using Digital.ai Agility for one year.

Azure DevOps was used by the development teams but was not adequate to manage the enterprise-level planning exercises.

You get what you pay for. Don't let your development teams dictate what the portfolio management team should use as the main tool.

We evaluated both Jira and Azure DevOps before choosing this solution.

If your organization is adopting SAFe (ScaledAgileFramework) processes and methodologies, Digital.ai Agility is the tool to manage those processes.

As an Agile coach, I have recommended the use of VersionOne to several clients. 

Being the Agile coach, I work with clients to help them install it into their local environment, then conduct an initial administration to the application. Afterward, I help them use it to manage their Scrum, Kanban, and SAFe implementations.

It allows my clients to have one central tool to manage their agile projects. It provides the necessary metrics for reporting. 

VersionOne delivers a total ALM solution for whether you are operating a single team, like Scrum and Kanban for IT operations, or implementing an agile enterprise approach, like SAFe.

• The team room feature is excellent for conducting DSUs. 
• Another great feature is the "what if" capability to evaluate how the project forecast may change if you modify scope or resources. 
• VersionOne ALM Connect plugin is very helpful for filling data in from other tools that your client may already be using, like HPE Quality Center.

Improve how to create and track releases. Currently, I have to create child projects.

I have never had a problem with stability or reliability of the application.  I have used both the cloud and locally installed versions and never seen any issues.

It comes out of the box ready to support all levels of SAFe.

Customer service/Technical support for this product has been very good unlike some other tools support.

Before using VersionOne we tracked our Agile projects in the traditional fashion using index cards on a board.    

I find the set up fairly straight forward.    Like any tool you have to learn the quirks with it and where to find the things you are looking to admin.    It does have a import option that is great but does require some knowledge how the import works.

While all of my installs have been in-house when we have needed support they have been very knowledgeable.

Given the higher entry price it could take a couple of years to see the ROI captured

Many people like JIRA because of its low capex but the entry level JIRA lacks some key capabilities and thus you have to obtain additional plugins to get JIRA to do what you may want it to.    This all increases the opex of JIRA.    VersionOne has a higher entry price (capex) but it comes out of the box with everything you need.     

As for installation I find VersionOne quite easy to setup.

I have used JIRA, HPALM, and Rally as well as VersionOne.    I am evaluating the use of Agile Craft or Metranome as a possible alternative solutions.

I highly recommend VersionOne but would also recommend looking at Agile Craft as an alternative.