Salesforce.Com, Inc Patent Portfolio Statistics

Salesforce.Com, Inc.

Profile Summary

This article summarizes the perfomance of the assignee in the recent years. The overall statistics for this portfolio help to analyze the areas where the assignee is performing well. The filing trend, perfomance across the tech centers and the perfomance of the recent applications has been mentioned below. All the stats are calculated based on the perfomance in USPTO.

How does the overall patent portfolio of Salesforce.Com, Inc. look like?

Assignee Art Units
Total Applications: 3,645 1,064,579
Granted Patents: 2,443 500,810
Grant Index 84.33% 70.64%
Abandoned/Rejected Applications: 454 (15.67%) 208,160 (29.36%)
In-Process Applications: 727 355,609
Average Grant Time: 2.96 Years 3.42 Years
Average Office Actions: 1.97 2.14

Which Technology Area Salesforce.Com, Inc. is filing most patents in? (Last 10 years)

Art Unit Definition Total Applications
Opap Parked GAU 137
2162 Data Bases & File Management 102
2165 Data Bases & File Management 93
2166 Data Bases & File Management 82
2169 Data Bases & File Management 82

How many patents are Salesforce.Com, Inc. filing every year?

Year Total Applications Predicted
2022 0* 786
2021 115* 784
2020 434 674
2019 471 471
2018 473
2017 385
2016 272
2015 237
2014 241
2013 269

*The drop in the number of applications filed in last two years compared to previous years is because applications can take up to 18 months to get published

Recently filed patent applications of Salesforce.Com, Inc. in USPTO?

Publication number: US20220100903A1
Application number: 17/643,573

Abstract:
An indication of an action is received through and application program interface (API) provided by one or more hardware processing devices. The action corresponds to communication with a specified party. Multiple disparate tables stored in at least one database of a of a database environment associated with the one or more hardware processing devices are searched for records having the field property corresponding to the specified party. The field property from the corresponding multiple disparate tables are evaluated. A unified field property is determined based on the evaluation of the field property from the corresponding multiple disparate tables. The unified field property is returned through the API.

Publication date: 2022-03-31
Applicant: Salesforce.Com, Inc.
Inventors: Hay Marla


Publication number: US20220091862A1
Application number: 17/643,089

Abstract:
Techniques are disclosed relating to emphasizing user interface elements for different users based on user attributes. In some embodiments, a system maintains a set of information (e.g., for a particular product) that includes multiple types of information. The system may access the same set of information for different user requests. The computing system may determine first and second subsets of the set of information based on attributes of the different users. The computing system may cause display of a first user interface on a device of the first user showing only the first subset of item fields for the two or more of the first set of items. The computing system may cause display of a second user interface on a device of the second user showing only the second subset of item fields for the two or more of the second set of items.

Publication date: 2022-03-24
Applicant: Salesforce.Com, Inc.
Inventors: Andolina Joseph


Publication number: US20220083819A1
Application number: 17/457,163

Abstract:
Computing systems may support image classification and image detection services, and these services may utilize object detection/image classification machine learning models. The described techniques provide for normalization of confidence scores corresponding to manipulated target images and for non-max suppression within the range of confidence scores for manipulated images. In one example, the techniques provide for generating different scales of a test image, and the system performs normalization of confidence scores corresponding to each scaled image and non-max suppression per scaled image These techniques may be used to provide more accurate image detection (e.g., object detection and/or image classification) and may be used with models that are not trained on modified image sets. The model may be trained on a standard (e.g. non-manipulated) image set but used with manipulated target images and the described techniques to provide accurate object detection.

Publication date: 2022-03-17
Applicant: Salesforce.Com, Inc.
Inventors: Ankit Chadha


How are Salesforce.Com, Inc.’s applications performing in USPTO?

Application Number Title Status Art Unit Examiner
17/643,573 Techniques And Architectures For Managing Privacy Information And Permissions Across Disparate Database Tables Docketed New Case – Ready for Examination OPAP Central, Docket
17/643,089 Adjusting Emphasis Of User Interface Elements Based On User Attributes Docketed New Case – Ready for Examination OPAP Central, Docket
17/457,163 Image Augmentation And Object Detection Docketed New Case – Ready for Examination OPAP Central, Docket
17/538,815 Estimation Of Network Quality Metrics From Network Request Data Docketed New Case – Ready for Examination OPAP Central, Docket
17/534,425 Updating Of A Denormalized Database Object After Updating, Deleting, Or Inserting A Record In A Source Database Object Docketed New Case – Ready for Examination OPAP Central, Docket