26.8 introduces two major features, Advanced Analytics and AI-Powered Root Cause Analysis, along with Pixel 11 Series support and same-day support for iOS 27.

👉 Read the full 26.8 Release Notes

A major OS update can change how your app behaves in ways you may not expect. Validate functionality, accessibility, performance, and hardened applications on real iOS 27 devices.

Watch the Overview

👉 Existing customer and want to upgrade your devices for iOS 27? Reach out to Support.

Requests are now available as a board, and that changes what a review feels like.

Read your intake in one look

Each request is a card in a column based on its status. Open the board and the pipeline is right there where requests are entering, where they are sitting, which stage is carrying more than its share. The questions that used to take a round of filtering get answered by looking.

The review becomes the work

When you decide something moves, you move it: drag a card to another column to update its status, or up within a column to change its ranking. Approved a request? Generate a story, portfolio item, defect, or issue right from the card. Nothing gets left in a notebook to action later.

Stakeholders get a picture, not a status report

"Your request is in review" lands very differently when someone can see it sitting next to everything else you are weighing. Install the board as a panel in a PlanningRoom and run the conversation on the live board — no exported snapshot that was stale before you sent it.

And it bends to how your team works

Set the fields on cards, group cards into rows by Priority, Source, Type and more, and write your board policies so everyone shares one definition of "In Review." Filters work exactly as they do on the list.

Try it on your next review

Open the hamburger menu > Product > Request Board, spend two minutes in the customise options, and run your next review on it. The list view has not changed most teams will want both: the board for the conversation, the list for the deep data work.

Over to you: What statuses does a request move through on your team, and where does it usually get stuck? Post your columns in the comments.

Teams can review accessibility findings alongside functional test results in the same test session, without switching tools or manually exporting data. This creates one review workflow with audit-ready evidence.

This video shows the product integration between Digital.ai Testing and Deque, and how easy it is to review and act on accessibility findings captured directly in the same test report.

👉 Video Overview

Earlier this year, we announced support for Android 17 Beta to help teams validate applications ahead of the official release. With Android 17 now stable, teams can continue testing on real devices using the released version of the OS. 

Teams can run manual and automated tests against real Android 17 hardware to validate functionality, performance, accessibility, and security-hardened applications. 

For teams that started testing on Android 17 Beta, GA devices are now available to continue validation. For teams beginning Android 17 testing now, real devices are available immediately. 

Watch the overview video: https://digital.ai/resource-center/videos/android-17-official-release/

New Features

Natively Built-In Accessibility Reports – Accessibility scan results, powered by Deque Axe, are now available directly within generated test reports, alongside functional test results in the same test session—creating one review workflow with audit-ready evidence.

Android 17 Support – Earlier this year, we announced support for Android 17 Beta to help teams validate applications ahead of the official release. Now, with the support for Android 17 official release, teams can test on the latest OS version to validate compatibility and uncover issues before they reach users.


Integrations & Ecosystem

Digital.ai Testing MCP Server – The MCP Server connects AI agent directly to your testing platform, turning natural language into real platform actions across administration, analysis, and test execution.

WebdriverIO MCP Server Support - We now support the WebdriverIO MCP Server, enabling AI agents to connect WebdriverIO workflows to real browsers and mobile devices on the Digital.ai Testing platform.


26.6 also includes important platform improvements and bug fixes focused on stability, reliability, and overall testing experience, along with a few deprecation notices to help you prepare for upcoming changes.

👉 Read the full 26.6 Release Notes

If you use Deploy and have ideas, challenges, or repetitive tasks where AI-assisted workflows could help, we’d love to hear from you.

💬 Leave a comment here, and we’ll reach out to schedule a short discovery session.

Our company is moving to feature releases. Does anyone have any best practices to naming of planning levels?

Thanks,

With Digital.ai Deploy 26.1, large artifact handling has been improved.
Deploy can now handle artifacts of 2 GB or larger more efficiently by using a streaming approach instead of loading the full artifact into memory.

Why does this matter?

Because deployment reliability is not only about the deployment logic itself. Sometimes, a deployment can be correctly configured but still run into problems because the package is large and difficult to process efficiently.

This improvement helps reduce memory pressure and makes large artifact deployments more resilient, especially for teams working with bigger packages or running multiple deployments in parallel.

This may be especially relevant if your teams deploy:

large application archives
folder-based deployment packages
generated enterprise bundles
packages with many nested files
multiple large artifacts in parallel

• How do you currently manage large deployment artifacts?

• Do you split packages, tune memory settings, use external storage, or rely on the deployment platform to handle large artifacts automatically?

For technical details, check the Deploy 26.1 documentation.