People.ai, Inc.

Other

Oleg Rogynskyy

Yurii Brunets

Rajit Kurien Joseph

Yury Markovsky

Stefan Hermanek

John Wulf

Jose Alberto Muniz Navarro

Vardhman Jain

Dylan Halladay

Tetiana Lutsaievska

Devin Rice

Wei Hai

Sathya Hariesh Prakash

Eric Jeske

Brittney Hall

Heorhiy Kozlov

Ostap Korkuna

David Flink

Kavita Shah

Nicholas Dingwall

Andrey Akselrod

Hang Li

Armine Seropyan

Cathy Xi

Cameron Feenstra

Volodymyr Nykytiuk

Mykola Pavlov

Maksym Kysylov

James Wilson

Sergey Surkov

Oleksandr Oleinikov

Dmitry Starshov

Andrii Kvachov

Adam Draper

Kyle Gerbe

Volodymyr Petrov

The system described herein can automatically match, link, or otherwise associate electronic activities with one or more record objects. For an electronic activity that is eligible or qualifies to be matched with one or more record objects, the system can identify one or more set of rules or rule sets. Using the rule sets, the system can identify candidate record objects. The system can then rank the identified candidate record objects to select one or more record objects with which to associate the electronic activity. The system can then store an association between the electronic activity and the selected one or more record objects.

Systems and methods for matching electronic activities directly to record objects of systems of record

The present disclosure relates to generating performance profiles of member nodes. A plurality of electronic activities can be accessed. A subset of electronic activities from the plurality of electronic activities can be identified. The subset of electronic activities can be parsed to identify participants of the electronic activities. A second node profile can be accessed for each participant. Participant types can be identified from each second node profiles. A distribution of the subset of electronic activities can be determined. A performance profile can be generated.

Systems and methods for updating record objects of a system of record

Systems and methods for providing content items can generate the content items based on impact scores associated with actions of the content items. The system and methods can include accessing, for an entity, a plurality of record objects linked with one or more electronic activities having the entity as a participant, each record object corresponding to an event to be completed; identifying, for each record object of the plurality of record objects, an action to perform to increase a completion score; determining, for each action, using the electronic activities linked with the record object and a current completion score of the record object, an impact score indicating an amount of change in the completion score of the record object corresponding to the action; and providing, for presentation to a device of the entity, a content item corresponding to the action based on the impact score.

Systems and methods for generating a content item based on a status of a node profile determined using electronic activities

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.

Systems and methods for classifying electronic activities based on sender and recipient information

The present disclosure relates to systems and methods for updating email addresses based on email generation patterns. The method includes accessing a plurality of electronic activities used to update a plurality of member node profiles. The method includes determining that the plurality of member node profiles is linked to a group node profile of a group entity. The methods includes identifying, for each of the plurality of member node profiles, a first field-value pair of the member node profile corresponding to an email address. The method includes determining, for each member node profile, a correlation between the email address, a second field-value pair corresponding to a first name and a third field-value pair corresponding to a last name. The method includes determining, based on the determined correlation, an electronic account identifier pattern. The method includes storing an association between the group node and the electronic account identifier pattern.

Systems and methods for updating email addresses based on email generation patterns

The present disclosure relates to systems and methods for automatic generation of summaries for record objects using one or more large language models. The system can identify a plurality of electronic activities matched to a record object of a customer relationship management system. The system can generate one or more text strings from the plurality of electronic activities using the large language models. The system can generate a first set of topics by inputting a first set of text strings into the large language models. The system can generate a second set of topics by inputting a first subset of text strings of the first set of text strings into the large language models. The system can transmit one or more topics to a computing device for presentation.

Systems and methods for automatic generation of electronic activity content for record objects using machine learning architectures

The present disclosure relates to determining detecting blast electronic activities. A method can include identifying a plurality of first electronic activities transmitted by a first electronic account of a data source provider. For each first electronic activity of the plurality of first electronic activities, a plurality of features can be extracted. For at least one first electronic activity of the plurality of first electronic activities, a blast probability score can be generated indicating a likelihood that the at least one first electronic activity is a blast electronic activity. The blast probability score can be generated using a machine learning model trained using features extracted from second electronic activities labeled as blast electronic activities and features extracted from third electronic activities labeled as non-blast electronic activities. An association between the at least one first electronic activity and the blast probability score can be stored in a data structure.

Systems and methods for blast electronic activity detection

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.

Systems and methods for detecting events based on updates to node profiles from electronic activities

The present disclosure relates to systems and methods for removing electronic activities from systems of record based on filtering policies. The method includes accessing record objects of one or more systems of record. The method includes identifying a plurality of electronic activities stored in a record object of one of the systems of record. The method includes parsing the plurality of electronic activities. The method includes determining that one of the electronic activities is associated with an electronic account corresponding to a data source provider. The method includes selecting one or more filtering policies associated with the electronic account. The method includes applying the selected one or more filtering policies to the plurality of electronic activities to identify a subset of electronic activities. The method includes initiating a process to cause removal of at least one electronic activity of the subset of electronic activities from the system of record.

Systems and methods for removing electronic activities from systems of records based on filtering policies

The present disclosure relates to systems and methods for matching electronic activities with record objects based on entity relationships. The method can include accessing a plurality of electronic activities, identifying an electronic activity, identifying a first participant associated with a first entity and a second participant associated with a second entity, determining whether a record object identifier is included in the electronic activity, identifying a first record object of the system of record that includes an instance of the record object identifier, and storing an association between the electronic activity and the first record object. The method can include determining a second record object corresponding to the second entity, identifying, using a matching policy, a third record object linked to the second record object and identifying a third entity, and storing, by the one or more processors, an association between the electronic activity and the third record object.

Systems and methods for matching electronic activities with record objects based on entity relationships

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.

Systems and methods of generating an engagement profile

The present disclosure relates to systems and methods for generating new node profiles using information from electronic activities. The system is configured to maintain node profiles corresponding to unique entities; access electronic activities transmitted or received via electronic accounts associated with data source providers; identify a first email address of a sender and second email addresses of respective recipients of an electronic activity; identify that the first email address matches a value of a field of a first node profile; link the electronic activity to the first node profile; determine that a second email address of a respective recipient of the electronic activity cannot be matched to any node profile associated with the respective participant; and generate, responsive to determining that the electronic activity cannot be matched to any node profile of the plurality of node profiles, a new node profile including the second email address of the respective recipient.

Systems and methods for generating node profiles using electronic activity information

The present disclosure relates to for managing the generation or deletion of record objects based on electronic activities and communication policies. Data of a plurality of electronic activities from one or more electronic accounts of the entity may be identified. It may be determined whether the identified data satisfies a communication policy. The communication policy may include one or more rules based on the electronic activities. Instructions to generate a contact record object or instructions to delete an existing contact record for the entity may be transmitted based on the condition of the communication of the communication policy that is satisfied.

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Menlo Park, CA, United States of America

Oleg Rogynskyy