People.ai, Inc.

Workday, Inc.

Yury Markovsky

Oleg Rogynskyy

Yurii Brunets

Tetiana Lutsaievska

John Wulf

Rajit Kurien Joseph

Eric Jeske

Stefan Hermanek

Hang Li

Sathya Hariesh Prakash

Devin Rice

Parag Avinash Namjoshi

Harikrishna Narayanan

Sergei Winitzki

Lakshminarayanan Renganarayana

Jose Alberto Muniz Navarro

Nicholas Dingwall

Maksym Kysylov

Kyle Gerbe

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 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 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. The method may further include generating a plurality of structured data tags for the first electronic activity; applying the selected first filtering model to the plurality of structured data tags for the first electronic activity to determine whether the first electronic activity satisfies a first restriction condition; and responsive to the first electronic activity satisfying the first restriction condition, restricting the first electronic activity from further processing; or responsive to the first electronic activity not satisfying the first restriction condition, further processing, by the one or more processors, the first electronic activity.

Systems and methods for auto discovery of filters and processing electronic activities using the same

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.

Systems and methods for determining a completion score of a record object from electronic activities

Methods, systems, and storage media for identifying a sequence of events and participants for record objects are disclosed. Exemplary implementations may: access record objects of a system of record; identify a subset of record objects associated with a group entity and having a first record object status; identify one or more electronic activities linked to the record objects; determine an event-participant pattern based on the electronic activities linked to the record object; identify electronic activities linked with a second record object; determine that a first event is performed by the a participant type and a second event is not yet performed by a second participant type; generate a content item identifying an action to trigger a performance of the second event; and transmit the content item to a device of a participant of at least one electronic activity linked with the second record object.

Systems and methods for identifying a sequence of events and participants for record objects

The present disclosure relates to maintaining extracted data in a group node profile from electronic activities. A group node profile associated with a group entity is maintained. A first data point including an electronic activity or a record object is accessed. The first data point is parsed using a value detection policy to obtain a first value. The group node profile is updated based on the first value. An association score between the group node profile and the first value is generated. A second data point is accessed. The second data point is parsed. The association score between the group node profile and the first value is updated.

Systems and methods for maintaining extracted data in a group node profile from electronic activities

Methods, systems, and computer-readable storage mediums for standardizing node field-value pairs of node profiles generated using electronic activities across multiple entities are described. In one aspect, the system can access, for a node profile of an entity, data points linked to the node profile. The system may determine a seniority value and a department value using the data points. The system may generate a normalized job title value by combining the seniority value and the department value using a title formatting policy specifying a format in which to combine to the seniority value and the department value. The normalized job title value may identify the seniority and department of entity. The system may store an association between the node profile and the normalized job title value in one or more data structures.

Systems and methods for standardizing field-value pairs across different entities

The present disclosure relates to a method for determining node metrics based on node field-value pairs and electronic activities. The method includes identifying a first node profile. The method includes identifying a plurality of electronic activities associated with the first node profile. The method includes identifying a first group of node profiles of a first category with a predetermined event. The method includes selecting a second group of node profiles. The method includes parsing the plurality of electronic activities to identify creation timestamps and participant characteristics of the electronic activities. The method includes generating an input array based on the timestamps and the participant characteristics. The method includes generating, for each of the second group of node profiles, a respective array. The method includes determining a probability score indicating a likelihood that the node profile belongs to the first category.

Systems and methods of determining node metrics for assigning node profiles to categories based on field-value pairs and electronic activities

A secure tenant activity data system for a deployment service includes processor that is configured to decrypt a set of encrypted stream processed monitoring data to recover a set of stream processed monitoring data; determine a transaction identifier associated with the set of stream processed monitoring data; determine whether the transaction identifier has been seen associated with a set of previous data; in response to determining that the transaction identifier has been seen associated with the set of previous data, retrieve the set of previous data; decrypt the set of previous data to recover a set of decrypted previous data; aggregate the set of stream processed monitoring data with the set of decrypted previous data to generate a set of aggregated data; encrypt the set of aggregated data to create a set of encrypted aggregated data; and provide the set of encrypted aggregated data to a safe storage area.

User action collection for sensitive customer data

A secure tenant activity data system for a deployment service includes an interface and a processor. The interface is configured to receive a set of encrypted monitoring data collected and encrypted from a monitoring instrument from a tenant system. The processor is configured to decrypt the data for stream processing; encrypt and store the stream processed data; and provide the encrypted data with a tenant identifier to a deployment service. Steam processing is one or more of data cleaning, data rounding, data filtering, data smoothing, algorithmic processing, improving ranking of results, improved navigation, generating recommendations, generating metrics, or computation of features for a machine learning system.

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San Francisco, CA, United States of America

Yury Markovsky