Zenhub previews AI for software project management

Zenhub previews AI for software project management

Zenhub is adding AI capabilities to automate task labeling, prioritise work, estimate completion dates, and provide insights into challenges and blockages.

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Zenhub is offering an early access preview of Zenhub AI, a cloud-hosted service that incorporates AI into Zenhub's software project management platform, with the intent to simplify day-to-day processes and enable faster shipping of code.

Zenhub AI assists in ancillary activities to writing code such as managing tasks and projects, categorising and prioritizing work, and other productivity activities, the company said on August 15. Zenhub has detailed several new AI-enabled features, with an AI labels capability available in beta today and the rest due soon.

Specific capabilities of Zenhub AI include:

  • AI labels, a planning capability leveraging AI to help teams ensure reporting accuracy. As soon as a team member starts entering data into Zenhub, the system suggests potential labels for the information. With labels powering reporting and analytics across the development ecosystem, this feature reduces cognitive load and saves developers time while ensuring accuracy across the development process, according to Zenhub.
  • AI estimations, giving developer teams insight into how challenging a process may be. Estimations will help teams agree on what is easy and what is challenging, as well as on what resources are needed. Completion of prior work will influence future work estimations.
  • AI prioritisation, using AI to speed up backlog refinement by using past behavior as a guide to prioritise unfinished tasks. This capability will suggest optimal priorities for new tasks and categorise them as high, medium, or low priority.
  • AI daily feed, giving developers insights into what has been accomplished, what needs to be done today, and what priorities are required in the near term. Zenhub is exploring sentiment analysis within issues, user stories, and comments to understand where team members might be blocked or stuck.
  • AI-powered sprint demos, for reviewing work done during a sprint or during the week.
  • AI retros, to provide suggestions on how teams can improve processes by using AI to determine what went well in recent sprints, what issues were faced, and what improvements can be made.

Tags project managemnt

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