Gusto. has been granted a patent for a central database system that manages human resources functions by assessing the default probability of entities. The system utilizes a machine-learned model to evaluate risk tolerance and streamline database interactions, enhancing the submission of evidence from entities based on historical data. GlobalData’s report on Gusto 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 Gusto, Social media analytics was a key innovation area identified from patents. Gusto's grant share as of July 2024 was 68%. Grant share is based on the ratio of number of grants to total number of patents.
Central database system for managing human resources functions
The patent US12045881B2 outlines a method and system designed to enhance database interactions through the use of a machine-learned model. This model is trained on a dataset that includes historical interactions and characteristics of entities that have previously engaged with a central database system. The primary function of the model is to determine the rate at which evidence submissions are required from entities interacting with the system. If the model identifies that this rate is insufficient, it can be retrained by adjusting its weights and parameters to increase the submission rate. The characteristics of historical entities considered in this process may include factors such as past failures, account age, and operational duration.
Additionally, the patent describes the submission of evidence through a second interface created by the central database system, which may include features like an upload interface for file submissions or a third-party API for accessing necessary documents. The evidence required can range from identity proofs to verifications from external systems. The method also allows for the integration of additional information from third-party sources to further refine the machine-learned model. Overall, this patent presents a structured approach to optimizing evidence submission processes in database interactions, leveraging machine learning to adapt and improve over time.
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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.
