C3.ai. has been granted a patent for a method that identifies transformation sequences for input datasets through a user interface. It selects an execution engine based on contextual dimensions and executes code, including machine learning algorithms, to perform the transformations effectively. GlobalData’s report on C3.ai gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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According to GlobalData’s company profile on C3.ai, AI for workflow management was a key innovation area identified from patents. C3.ai's grant share as of July 2024 was 23%. Grant share is based on the ratio of number of grants to total number of patents.
Method for transforming datasets using context-aware execution engines
The patent US12073202B2 outlines a method and apparatus for processing input datasets through a sequence of transformations, utilizing a user interface to facilitate user interaction. The method involves identifying a context associated with the dataset, which includes multiple dimensions such as interactivity, data size, data shape, security profile, resource availability, personal identifiable information (PII), retention policy, and computation comprehensiveness. Based on this context, a suitable execution engine is selected to perform the transformations, which are implemented through machine learning algorithms. The method also allows for the storage of a graph that represents the sequence of transformations, enhancing the organization and execution of the processing tasks.
Additionally, the patent describes the capability to handle requests for transformations on specified data, which may differ from the initial context. This includes selecting a different execution engine and generating corresponding code for the new context. The user interface is designed to accommodate multiple users, enabling them to define transformation sequences easily. The apparatus is equipped with processing devices that execute the transformations and manage the associated contexts, ensuring that the processing is tailored to the specific requirements of the data being handled. Overall, the patent presents a comprehensive framework for efficiently managing data transformations in various contexts, leveraging machine learning and user-defined parameters.
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GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.
