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Digital.ai Introduces New Version of Its AI-Powered DevOps Platform That Empowers Large Organizations

  • Keep software investments aligned to business objectives with collaboration and intelligence

  • Manage overall costs by leveraging existing assets and software delivery practices

  • Create a data-driven release strategy with long and short-term forecasting, armed with real time and historical data and AI-driven predictive insights

Digital.ai unveiled the Banff release of its AI-Powered DevOps Platform, featuring expanded intelligence, automation and collaboration, to further help companies accelerate digital transformation. The new version makes it possible for public sector and enterprise organizations to accelerate delivery while managing risk, all with a focus on driving maximum value from software investments.

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“We are truly excited to be delivering to our customers our latest release that removes the mystery and complexities in mapping software investments to topline business goals and priorities. Digital.ai believes that the future of enterprise DevOps is being able to turn data into actionable, predictive insights.”

At the heart of the AI-Powered DevOps Platform is its Intelligence capabilities which aggregate customer data spanning the entire software development and delivery lifecycle, automatically creating an industry-leading DevOps data lake. This data lake creates a single source of truth for an organization’s software investments across the full lifecycle from planning and into production. Customers gain real-time insights, historical trend analysis and predictability in augmented analytic dashboards. This contextual data allows organizations to observe top level trends across the enterprise and quickly drill down to the team and individual levels to drive successful business outcomes. This release includes further expansion of Digital.ai’s machine learning and artificial intelligence solutions, allowing customers to move past historical trends to predictive, actionable insights.

“We are investing significantly in AI and machine learning across all domains of IT, and a good example of this commitment is our partnership with Digital.ai,” said the CIO of Enterprise Infrastructure and Operations at one of the country’s largest financial services companies. “By using Digital.ai’s AI-driven Change Risk Prediction module we’ve been able to reduce business impact caused by change activity, increase the success of change releases and accelerate delivery of low-risk changes — ultimately freeing our developers to be more productive. We’ve been encouraged by these results and we plan to deploy additional Digital.ai features, such as Incident Topic Clustering and Change Impact Detection.”

Both private and public sector organizations are under increased pressure to manage overall costs and optimize existing software investments in an uncertain economic climate. At the same time, the need to develop and deliver secure, high-quality, innovative software releases at scale remains a business imperative. This situation is fueling global demand for software delivery platforms like Digital.ai’s AI-Powered DevOps Platform. Digital.ai solutions are currently being used by more than a thousand organizations worldwide including more than 50% of the Fortune 500 and the company’s technology protects 5+ billion app endpoints.

“Software strategy now underpins every business strategy and business leaders need to navigate global economic uncertainty with agility, automation and security,” said Stephen Elop, CEO of Digital.ai. “We are truly excited to be delivering to our customers our latest release that removes the mystery and complexities in mapping software investments to topline business goals and priorities. Digital.ai believes that the future of enterprise DevOps is being able to turn data into actionable, predictive insights.”

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Digital.ai solutions can be easily integrated into existing processes, applications and infrastructure to optimize existing investments while propelling innovation and bringing greater visibility and insight across the entire software architecture and ecosystem.

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New enhancements include:

Improved Software Delivery Insights

  • Model Monitoring dashboard: The updated model monitoring dashboard features key improvements for change risk prediction, making it easier to track the model’s performance of retraining and validation in production.
  • Deployment intelligence: Users can now capture all manual deployment tasks defined in a release and view the deployment metrics and impact on applications and environment.
  • Continuous Testing analytics: Organizations can now provide details of test execution and test by applications to get an understanding of the volume of testing and its results by various device types.

A More Comprehensive DevOps Ecosystem

  • A single identity across the platform: Digital.ai has enhanced identity protection and created a unified experience across all its products, docs, support and community, allowing users to seamlessly move between apps across Digital.ai with Digital.ai Identity. Beyond creating a new low friction experience, Digital.ai Identity brings key capabilities which modern enterprises require for their software development and delivery solutions, including enhanced shared service configurations, integration with common enterprise identity services and audit information.
  • Hoylu whiteboarding integration: Users can unlock the power of whiteboard-based collaboration with Hoylu’s visual and iterative approach for better agile planning. By combining whiteboarding techniques with scaled Agile practices, this integration provides distributed teams with new ways to collaborate and further understand risk and dependencies.
  • Digital.ai Community: Digital.ai Community provides an additional avenue of support so users and their teams can get more value out of Digital.ai products and processes. Digital.ai Community is designed for social, peer-to-peer engagement, and makes it easy for users to find answers, share product wisdom and get inspiration from other members of the Digital.ai Community.
  • Enhanced and expanded Cloud native deployments: A new integration of Argo Rollouts helps customers deploy strategies such as blue/green, canary, canary analysis, experimentation and progressive delivery features to Kubernetes®. Argo Rollouts helps developers manage the entire application release and deployment process – removing bottlenecks and risks of change failure and delivering a better user experience.

More Secure and Higher Quality Applications

  • Recorder for Testing: New enhancements to the recorder for test editor enable non-experts to easily record software experiences and generate tests. Automation and low code approaches of Continuous Testing help address the global shortage of QA professionals.
  • Expanded Accessibility Testing: Now Android™ environment developers can similarly take advantage of the robust level of accessibility monitoring offered for iOS, so they can increase compliance with global accessibility standards. The new Android™ Inspector feature identifies onscreen elements in Android™ applications and gives users information about different accessibility properties such as visual filters and Voiceover.
  • Application Security: New innovation reduces attack surface, allowing for faster reporting and more datasets – so organizations can secure a wider range of applications, including mobile, web and desktop apps made for more OS versions.

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