Uipath Inc.

Microsoft Technology Licensing, LLC

Ankit Saraf

Palak Kadakia

Mircea Grigore

Evan Cohen

Naren Venkateswaran

Sankara Narayanan Venkataraman

Yasser Elsayed Shaaban

Remus Rusanu

Andrew Hall

Weizhu Chen

Eslam K Abdelreheem

Chao Li

Andrew Michael Pennell

Justin Marks

Jiayuan Huang

Bridgette Graham

Changhong Yuan

Jing Jin

Minyi Zhong

Jinglong Yang

Xiaoying Guo

Yunjing Ma

Shean Wang

Tsuyoshi Watanabe

Jaclyn Ruth Elizabeth Phillips

Yuantao Wang

Justin Carl Wong

Nan Zhao

Siu Yu Cherie Quek

According to one or more embodiments, a method is provided. The method is implemented by a trigger engine stored on a memory as processor executable instructions. The processor executable instructions being executed by a processor. The trigger engine operates as an intermediary for robotic process automations of a software platform. The method includes tracking operations within external systems and registering available events with respect to the operations into a database accessible by the robotic process automations. The method also includes enabling an active event of the external systems to be visible via a trigger of the trigger engine to the robotic process automations.

Cloud triggers for scheduling robots

In some examples, iterative sampling based dataset clustering may include sampling a dataset that includes a plurality of items to identify a specified number of sampled items. The sampled items may be clustered to generate a plurality of clusters. Un-sampled items may be assigned from the plurality of items to the clusters. Remaining un-sampled items that are not assigned to the clusters may be identified. A ratio associated with the remaining un-sampled items and the plurality of items may be compared to a specified threshold. Based on a determination that the ratio is greater than the specified threshold, an indication of completion of clustering of the plurality of items may be generated.

Iterative sampling based dataset clustering

A process for invoking a robot from an application may include launching the application from a computing system to invoke a robot link embedded within the application. The process may also include initiating from the application a port discovery process to identify a port, port details, and a token. The process may further include generating by the application a randomized code and invoking a consent application requesting approval from a user of the computing system to invoke the robot from the application. The process may also include registering the randomized code with a local listener module and passing user information and the token to a global listener module. The process may further include receiving from the global listener module the token and port identification, allowing the application to authenticate itself with, and communicate with, the robot, thereby completing the robot invoking process.

Robot browser embedding

A computing device including a memory and a processor is provided. The memory stores processor executable instructions for an entity engine. The processor is coupled to the memory. The processor executes the entity engine to cause the computing device to model entities, which hold or classify data. The processor executes the entity engine to cause the computing device to store in the memory a list identifying each of the entities and the entities themselves in correspondence with the list. The processor executes the entity engine to cause the computing device to provide, in response to a selection input from an external system, access to the entities based on the list. The access includes providing the list to the external system, receiving the selection input identifying a first entity of the entities, and exporting the first entity from the memory to the external system.

Entity engine of a computing platform

A system and method provide an integrated automation solution that links multiple systems and applications of a contact center operation and provides a unified support interface and unified knowledge base that delivers relevant data in real-time to assist contact center personnel during a customer interaction. Robotic Process Automation (RPA) is used for automating workflows and processes with robots (e.g., attended and/or unattended) that perform various tasks and activities for capturing information (data, documents, etc.) from multiple front-end and/or back-end systems and applications to provide the necessary data and information in real-time during a contact center session.

Unified support framework for a contact center

Application integration for robotic process automation (RPA) using a development application configured for development of RPA-enabled applications is disclosed. The development application in some embodiments may be used for application integration with attended robots that execute locally on the same computing system as an instance of the RPA-enabled application, unattended robots that execute on a remote computing system, or both, creating an RPA-enabled application. One or more user interface (UI) elements, variables, and/or events of an RPA-enabled application may be linked to one or more respective RPA processes, causing respective RPA robot(s) to carry out the associated functionality.

Application integration for robotic process automation

One or more robots may be invoked from one or more applications for robotic process automation (RPA). A process for invoking a robot from an application may include launching the application from a computing system to invoke a robot link embedded within the application. The process may also include initiating from the application a port discovery process to identify a port, port details, and a token. The process may further include generating by the application a randomized code and invoking a consent application requesting approval from a user of the computing system to invoke the robot from the application. The process may also include registering the randomized code with a local listener module and passing user information and the token to a global listener module. The process may further include receiving from the global listener module the token and port identification, allowing the application to authenticate itself with, and communicate with, the robot, thereby completing the robot invoking process.

An integrated application environment includes a host web application executed in a browser, and a target application embedded in a container of the host web application. Interoperability layers facilitate messaging between the host web application and a host entity object of the target application in the container according to multiple communication protocols.

Interoperability between a host application and an embedded target application

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Bellevue, WA, United States of America

Ankit Saraf