Patents Assigned to People.ai, Inc.
  • Patent number: 10504050
    Abstract: Methods, systems, and storage media for managing electronic activity driven targets are disclosed. Example implementations may: maintain a plurality of node profiles; select, for a first node profile, using one or more field-value pairs of the first node profile, an endpoint profile generated using electronic activities of second node profiles including one or more field-value pairs that match the one or more field-value pairs of the first node profile, the endpoint profile specifying electronic activity driven targets that can be tracked by parsing electronic activities corresponding to the first node profile; store in one or more data structures, an association between the first node profile and the endpoint profile specifying the electronic activity driven targets; parse a plurality of electronic activities corresponding to the first node profile; and update a metric relating to the electronic activity driven targets responsive to parsing the second plurality of electronic activities.
    Type: Grant
    Filed: May 23, 2019
    Date of Patent: December 10, 2019
    Assignee: PEOPLE.AI, INC.
    Inventors: Oleg Rogynskyy, Wei Hai, Kavita Shah
  • Patent number: 10496688
    Abstract: Systems and methods for inferring schedule patterns using electronic activities of node profiles are disclosed.
    Type: Grant
    Filed: April 29, 2019
    Date of Patent: December 3, 2019
    Assignee: PEOPLE.AI, INC.
    Inventors: Oleg Rogynskyy, John Wulf, Yurii Brunets
  • Patent number: 10496635
    Abstract: The present disclosure relates to systems and methods for assigning tags to values of node profiles based on detected electronic activity. Exemplary implementations may: maintain node profiles; access a response to an electronic activity transmitted or received via an electronic account; detect responsive to parsing the response, that the response is one of a bounce-back electronic activity indicating that the recipient of the electronic activity is invalid or an automatic responder electronic activity generated by an autoresponder of the recipient; compare a communication identifier of the response to the node profile(s) to identify a node profile having a matching communication identifier; assign a respective tag to the identified at least one node profile responsive to detecting that the electronic activity is the bounce-back electronic activity or the automatic responder electronic activity; and update a node field-value pair of the identified at least one node profile based on the assigned tag.
    Type: Grant
    Filed: March 21, 2019
    Date of Patent: December 3, 2019
    Assignee: PEOPLE.AI, INC.
    Inventors: Yurii Brunets, Devin Rice, Oleg Rogynskyy, Jose Alberto Muniz Navarro
  • Patent number: 10496675
    Abstract: The present disclosure is related to systems and methods of merging tenant shadow systems of record into a master system of record. First tenant record objects of a first tenant system of record can be accessed. A master record object for a master system of record can be generated using the corresponding first tenant record object. A second tenant record object of a second tenant system of record can be accessed. Whether the second tenant record object is to be merged into the corresponding master record object can be determined. When determined to merge, the second tenant record object can be merged into the corresponding master record object. When determined to not merge, a new master record can be generated.
    Type: Grant
    Filed: April 30, 2019
    Date of Patent: December 3, 2019
    Assignee: People.ai, Inc.
    Inventors: Oleg Rogynskyy, Vardhman Jain, Rajit Kurien Joseph, Jose Alberto Muniz Navarro
  • Patent number: 10496681
    Abstract: The present disclosure relates to electronic activity classification. A plurality of node profiles corresponding to a plurality of unique entities is maintained. A plurality of electronic activities is accessed from electronic accounts of one or more data source providers. Features are extracted from the electronic activities to determine a classification of the first electronic activity. A confidence score is determined indicating a likelihood that the first electronic activity of a classification type. An association is stored between the first electronic activity and a tag corresponding to the first classification type. The confidence score is updated based on a second electronic activity.
    Type: Grant
    Filed: May 21, 2019
    Date of Patent: December 3, 2019
    Assignee: People.ai, Inc.
    Inventors: Oleg Rogynskyy, Stefan Hermanek, Yury Markovsky
  • Patent number: 10496634
    Abstract: The present disclosure relates to a method for determining a completion score for a record object based on electronic activities. The method includes accessing record objects, each of which corresponds to a record object type and includes object fields having object field-values. The method includes selecting one of the record objects. The method includes identifying electronic activities transmitted or received associated with the record object. Each of the electronic activities has a timestamp indicating a receipt time or transmission time of the respective electronic activity. The method includes determining a participant of each of the electronic activities. The method includes determining a completion score indicating a likelihood of completing an event associated with the record object based on the timestamp of each of the electronic activities and the participant of each of the electronic activities. The method includes storing an association between the record object and the completion score.
    Type: Grant
    Filed: April 29, 2019
    Date of Patent: December 3, 2019
    Assignee: PEOPLE.AI, INC.
    Inventors: Oleg Rogynskyy, Yury Markovsky, Eric Jeske, Tetiana Lutsaievska, Hang Li
  • Patent number: 10498856
    Abstract: The present disclosure relates to systems and methods for determining an engagement profile of a participant by associating electronic activities to a profile. It may generate the engagement profile based on analysis of the electronic activity level. An example implementation may contain the following steps. The system may access for a first record object a plurality of electronic activities linked with the first record object. The system may identify for a participant from the plurality of electronic activities a set of electronic activities including the participant. The system may determine an engagement profile of the participant based on a first number of electronic activities of the set of electronic activities sent by the participant, a second number of the set of electronic activities received by the participant and a temporal distribution of the set of electronic activities. The system may store the engagement profile in one or more data structures.
    Type: Grant
    Filed: May 23, 2019
    Date of Patent: December 3, 2019
    Assignee: PEOPLE.AI, INC.
    Inventors: Oleg Rogynskyy, Dylan Halladay, Stefan Hermanek, Yurii Brunets
  • Patent number: 10496636
    Abstract: The present disclosure relates to assigning labels based on matching electronic activities to record objects. Electronic activities of one or more data source providers may be accessed. Each electronic activity may be matched with a record object of a system of record of the one or more data source providers. Record objects matching electronic activities may be identified. Values from object field-value pairs of the matching record objects may be extracted. Labels may be selected based on the extracted values. Associations between electronic activities and the selected labels may be stored.
    Type: Grant
    Filed: May 21, 2019
    Date of Patent: December 3, 2019
    Assignee: PEOPLE.AI, INC.
    Inventors: Oleg Rogynskyy, Stefan Hermanek, Dylan Halladay, Ostap Korkuna, Jose Alberto Muniz Navarro
  • Publication number: 20190361934
    Abstract: The present disclosure relates to methods, systems, and storage media for identifying node hierarchies and connections using electronic activities. The method may include maintaining node profiles corresponding to unique entities; selecting electronic activities linked to both a first node profile and a second node profile of the plurality of node profiles; generating for each electronic activity of the plurality of electronic activities, a relevancy score based on a respective time at which the electronic activity was transmitted or received; generating a connection profile for a connection between the first node profile and the second node profile based on the respective relevancy score of each electronic activity and storing in a data structure, an association between the connection profile, the first node profile, and the second node profile.
    Type: Application
    Filed: March 31, 2019
    Publication date: November 28, 2019
    Applicant: People.ai, Inc.
    Inventors: Oleg Rogynskyy, Stefan Hermanek, John Wulf, Devin Rice, Yury Markovsky
  • Publication number: 20190361924
    Abstract: Systems and methods for matching electronic activities to record objects using feedback based match policies can include accessing a plurality of electronic activities and record objects. The systems and method can include identifying candidate record objects by applying a matching model. The systems and methods can include selecting a record object based on a match score. The systems and methods can include configuring the matching model in a first configuration responsive to a first feedback type or configuring the matching model in a second configuration responsive to a second feedback type.
    Type: Application
    Filed: May 21, 2019
    Publication date: November 28, 2019
    Applicant: People.ai, Inc.
    Inventors: Oleg Rogynskyy, Volodymyr Nykytiuk, Stefan Hermanek, Ostap Korkuna
  • Publication number: 20190361936
    Abstract: The present disclosure relates to methods, systems, and storage media for detecting events based on updates to node profiles from electronic activities. Exemplary implementations may access an electronic activity transmitted or received via an electronic account associated with a data source provider; generate a plurality of activity field-value pairs; maintain a plurality of node profiles; identify a first state of a first node profile of the plurality of node profiles; update the first node profile using the electronic activity; identify a second state of the first node profile subsequent to updating the first node profile using the electronic activity; detect a state change of the first node profile based on the first state and the second state; determine that the state change satisfies an event condition; and store an association between the first node profile and an event type corresponding to the event condition.
    Type: Application
    Filed: March 31, 2019
    Publication date: November 28, 2019
    Applicant: People.ai, Inc.
    Inventors: John Wulf, Sathya Hariesh Prakash, Yurii Brunets, Oleg Rogynskyy, Rajit Kurien Joseph, Yury Markovsky
  • Publication number: 20190361872
    Abstract: The present disclosure relates to methods, systems, and storage media for updating confidence scores of labels based on subsequent electronic activities. Exemplary embodiments may maintain a plurality of node profiles corresponding to a plurality of unique entities; access a plurality of electronic activities transmitted or received via electronic accounts associated with one or more data source providers; identify a first electronic activity to process; assign a tag to the first electronic activity based on the data included in the electronic activity; determine a confidence score of the tag based on the data included in the first electronic activity; identify a second electronic activity to process; and update the confidence score of the tag assigned to the first electronic activity responsive to parsing the second electronic activity.
    Type: Application
    Filed: March 21, 2019
    Publication date: November 28, 2019
    Applicant: People.ai, Inc.
    Inventors: John Wulf, Sathya Hariesh Prakash, Vardhman Jain, Stefan Hermanek, Wei Hai, Oleg Rogynskyy
  • Publication number: 20190362452
    Abstract: The present disclosure relates to generating field-specific health scores for a system of record. Record objects of a system of record corresponding to a data source provider may be accessed. Each record object may correspond to a record object type and have one or more object field-value pairs. Node profiles may be maintained. Each node profile may include one or more node field-value pairs. A subset of node field-value pairs of the node profiles with confidence scores greater than a threshold score may be identified. Node profiles having the subset of node field-value pairs may be identified. Node field-value pairs of the subset may be compared with corresponding object field-value pairs of the record objects. A field-specific health score for each field may be generated based on the comparison.
    Type: Application
    Filed: March 31, 2019
    Publication date: November 28, 2019
    Applicant: People.ai, Inc.
    Inventors: Yurii Brunets, Oleg Rogynskyy, Devin Rice, Yury Markovsky, Tetiana Lutsaievska
  • Publication number: 20190362284
    Abstract: The present disclosure relates to systems and methods for estimating time to perform electronic activities. Exemplary implementations may: identify an electronic activity identifying a sender and one or more recipients and a body including content; determine using a quality estimation model, a quality of electronic activity (QoE) score corresponding to an estimated quality of the electronic activity; parse the content of the electronic activity; generate, using a language complexity determination engine, a language complexity score indicating a level of language complexity; determine a character count or word count; determine an estimated amount of time taken to generate the electronic activity using the language complexity score and the character count or word count; generate the QoE score corresponding to the estimated quality based on the estimated amount of time; and store in a data structure, an association between the electronic activity and the QoE score.
    Type: Application
    Filed: March 31, 2019
    Publication date: November 28, 2019
    Applicant: People.ai, Inc.
    Inventors: John Wulf, Sathya Hariesh Prakash, Tetiana Lutsaievska, Oleg Rogynskyy
  • Publication number: 20190364009
    Abstract: The system and methods described herein can classify electronic activities based on sender and recipient information. The system can determine a relationship between a sender of an electronic activity and at least one recipient of the electronic activity using a sender node profile and a recipient node profile. The system can assign a tag to the electronic activity based on the relationship between the sender and one or more recipients of the electronic activity. The system can process the electronic activity based on the assigned tag.
    Type: Application
    Filed: March 21, 2019
    Publication date: November 28, 2019
    Applicant: People.ai, Inc.
    Inventors: Rajit Joseph, Stefan Hermanek, Jose Alberto Muniz Navarro, Dylan Halladay, Heorhiy Kozlov, Oleg Rogynskyy
  • Publication number: 20190361890
    Abstract: Systems and methods for forecasting record object completions can include accessing, for a first record object, electronic activities linked with the first record object. Each electronic activity can identify participants associated with the first record object. The first record object can include a first object field-value pair identifying a stage of a process. The method can include identifying electronic activities. The systems and methods can include determining a role of participants. The systems and methods can include determining a likelihood that the process of the first record object is completed within a predetermined time period. The systems and methods can include storing an association between the first record object and the likelihood that the process of the first record object is completed within a predetermined time period.
    Type: Application
    Filed: May 23, 2019
    Publication date: November 28, 2019
    Applicant: People.ai, Inc.
    Inventors: Oleg Rogynskyy, Yurii Brunets, Eric Jeske, Nicholas Dingwall
  • Publication number: 20190361935
    Abstract: Methods, systems, and storage media for generating new record objects based on electronic activities are disclosed. Example implementations may: access a plurality of electronic activities; access a plurality of record objects; parse an electronic activity of the plurality of electronic activities; determine, responsive to parsing the electronic activity, that the electronic activity is to be matched to one or more record objects; determine for each candidate record object that a match score indicating a likelihood of electronic activity being matched to the candidate record object is below a threshold; determine an object type of a new record object to generate based on one or more participants of the electronic activity; generate the new record object of the determined type; and store in a data structure an association between the new record object and the electronic activity.
    Type: Application
    Filed: March 31, 2019
    Publication date: November 28, 2019
    Applicant: People.ai, Inc.
    Inventors: Jose Alberto Muniz Navarro, Vardhman Jain, Andrey Akselrod, Heorhiy Kozlov, Rajit Kurien Joseph, Oleg Rogynskyy
  • Publication number: 20190361864
    Abstract: The present disclosure relates to methods, systems, and storage media for updating field-value pairs of record objects using electronic activities linked to the record objects. The method can maintain a plurality of node profiles corresponding to a plurality of unique entities; access a plurality of electronic activities transmitted or received via electronic accounts associated with one or more data source providers; identify a record object of a plurality of record objects of one or more systems of record; match electronic activity of the plurality of electronic activities to the record object based on content of the electronic activity and the object field-value pairs of the record object; identify a node profile matched with the electronic activity of the plurality of electronic activities; determine a weighting factor for the electronic activity; and update a stage field of the record object to a second stage value indicating a second proximity to the completion of the event.
    Type: Application
    Filed: March 31, 2019
    Publication date: November 28, 2019
    Applicant: People.ai, Inc.
    Inventors: Devin Rice, Stefan Hermanek, Wei Hai, Oleg Rogynskyy, Rajit Kurien Joseph
  • Publication number: 20190361925
    Abstract: The present disclosure relates to generating a master group node graph from a plurality of systems of record. Record objects of a system of record corresponding to a data source provider may be accessed. Each record object can have a record object type and identify a group entity. Each record object can be linked to one or more second record objects of a second record object type and identifying a respective member entity. A record object corresponding to a group entity can be identified. A connection profile between the record objects of the group entity and another group entity can be generated. An association between the group node profiles and the connection profile can be stored.
    Type: Application
    Filed: May 21, 2019
    Publication date: November 28, 2019
    Applicant: People.ai, Inc.
    Inventors: Oleg Rogynskyy, Yurii Brunets, Devin Rice, Vardhman Jain
  • Publication number: 20190361929
    Abstract: The present disclosure relates to systems and methods for filtering electronic activities. Exemplary implementations may include ingesting a first electronic activity; identifying an associated entity; and selecting a first filtering model based on the entity, the first filtering model trained to indicate whether to restrict further processing of ingested electronic activities.
    Type: Application
    Filed: May 21, 2019
    Publication date: November 28, 2019
    Applicant: People.ai, Inc.
    Inventors: Oleg Rogynskyy, Yury Markovsky, Tetiana Lutsaievska, John Wulf