People.ai, Inc.

Jose Alberto Muniz Navarro

Oleg Rogynskyy

Rajit Kurien Joseph

Stefan Hermanek

Vardhman Jain

Dylan Halladay

Yurii Brunets

Heorhiy Kozlov

Ostap Korkuna

Andrey Akselrod

Devin Rice

Yury Markovsky

Wei Hai

Kavita Shah

Adam Draper

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.

Systems and methods for generating new record objects based on 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 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 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.

Systems and methods for merging tenant shadow systems of record into a master system of record

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 with node profiles

The systems and methods relate to updating a system of record by selectively generating record objects for the system of record according to information generated by parsing the electronic activities according to specific matching rules and/or filtering rules. By selectively generating the record objects in the specific manners described herein, the systems and methods can provide for better determinations about whether to generate new record objects that match the information generated by parsing the electronic activities, or to update an existing record object.

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

This disclosure relates to methods, systems, and storage media for generating a performance profile of a node profile. First electronic activities linked to a first node profile can be accessed. For each first electronic activity, a type of the first electronic activity can be determined. A feature extraction policy can be selected to generate a first feature array for the first electronic activity. The first feature array for the first electronic activity can be generated based on the type of the first electronic activity. A first performance profile of the first node profile can be generated for the time period by providing the generated first feature array for each first electronic activity to one or more models trained using second feature arrays corresponding to second electronic activities of second node profiles. An association between the first node profile and the first performance profile can be stored.

Systems and methods for generating a performance profile of a node profile including field-value pairs using electronic activities

Systems and methods for matching electronic activities to record objects of systems of record with node profiles

The system described herein can automatically match, link, or otherwise associate electronic activities with one or more node profiles. For an electronic activity that is eligible or qualifies to be matched with one or more node profiles, the system can selectively apply rules to match the electronic activity to a subset of the one or more node profiles based on values of fields extracted from the electronic activity and values of the node profiles. The system can then store an association between the electronic activity and the subset of the one or more node profiles.

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Foster City, CA, United States of America

Jose Alberto Muniz Navarro