Asana had two patents in artificial intelligence during Q4 2023. Asana Inc’s patent filed in Q4 2023 focuses on systems and methods for generating prioritization models and predicting workflow prioritizations. The technology involves managing environment state information in a collaboration environment, presenting questions to users, generating prioritization models based on user responses, and determining priorities for users within a set of work units. This innovation aims to help users prioritize their tasks effectively. GlobalData’s report on Asana gives a 360-degreee view of the company including its patenting strategy. Buy the report here.

Asana grant share with artificial intelligence as a theme is 50% in Q4 2023. Grant share is based on the ratio of number of grants to total number of patents.

Recent Patents

Application: Systems and methods for generating prioritization models and predicting workflow prioritizations (Patent ID: US20230325747A1)

The patent filed by Asana Inc. describes systems and methods for generating prioritization models and predicting workflow prioritizations. The system involves managing environment state information in a collaboration environment, presenting a series of questions to a user, generating a prioritization model based on user responses, and determining priorities for the user's work based on the model. The prioritization model is trained using a neural network and considers user parameters and work unit parameters to prioritize tasks effectively.

The system further includes generating a graphical user interface to display the priorities determined for the user's work, communicating this interface to the user's computing platform, and training the model based on additional prioritization information received. The method involves obtaining a trained prioritization model, determining priorities for the user's work, and generating a graphical user interface to display these priorities. It also includes managing environment state information, training the model using a neural network, and incorporating user actions within the collaboration environment into the prioritization process. Additionally, the method allows for exporting the trained prioritization model upon request. Overall, the system and method aim to enhance workflow efficiency by prioritizing tasks based on user responses and interactions within a collaboration environment.

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