Palantir Technologies Inc.

Anirvan Mukherjee

Daniel Erenrich

William Dwyer

Andre Frederico Cavalheiro Menck

Guodong Xu

David Lisuk

Simon Slowik

Aleksandr Zamoshchin

Luis Voloch

Daniel Chin

Rahul Kumar Agarwal

Di Wu

Parvathy Menon

John Kenneth Garrod

Ankit Shankar

Allen Cai

Geoff Stowe

Eli Bingham

Jacob Scott

Feridun Arda Kara

Zachary Bush

Brian Ngo

Andrew Ash

Greg Martin

Diane Wu

Sean Kelley

Winnie Chai

Engin Ural

Ted Mabrey

Drausin Wulsin

Gilad Gray

Asli Ozyar

Mike Reilly

Matt Sills

Spencer Stamats

Samir Talwar

Holt Wilkins

Greg Cohan

Chris Dorsey

Dennis Kwon

Chris Lewis

Joyce Yu-Hsin Chen

Bar Kaya

Patricio Jones Velez

Johannes Beil

Yu-Hsin Joyce Chen

Baris Kaya

P J Valez

Pj Valez

Shubhankar Sachdev

Craig De Souza

Michael Zullo

Jessica Winssinger

Rushad Heerjee

Rahul Agarwal

Edgar Gomes De Araujo

Computer-implemented systems and methods are disclosed, including systems and methods utilizing language models for generating data objects and/or updating an ontology. A computer-implemented method may include: employing one or more large language models ('LLMs') to generate at least a data triple and a classified triple; executing, using the classified triple, a similarity search with reference to an ontology to determine that the classified triple at least partially matches one or more data object types defined in the ontology; in response to the determination, adding into a first database at least a first data object of a first data object type that represents a first entity in the data triple and a second data object of a second data object type that represents a second entity in the data triple.

Language model-based data object extraction and visualization

A model management system provides a centralized repository for storing and accessing models. The model management system receives an input to store a model object in a first model state generated based on a first set of known variables. The model management system generates a first file including a first set of functions defining the first model state and associates the first file with a model key identifying the model object. The model management system receives an input to store the model object in a second model state having been generated based on the first model state and a second set of known variables. The model management system generates a second file including a second set of functions defining the second model state and associates the second file with the model key. The model management system identifies available versions of the model object based on the model key.

Model object management and storage system

Systems and methods are disclosed for determining a propensity of an entity to take a specified action. In accordance with one implementation, a method is provided for determining the propensity. The method includes, for example, accessing one or more data sources, the one or more data sources including information associated with the entity, forming a record associated with the entity by integrating the information from the one or more data sources, generating, based on the record, one or more features associated with the entity, processing the one or more features to determine the propensity of the entity to take the specified action, and outputting the propensity.

System and method for determining a propensity of entity to take a specified action

Systems and methods are provided for analyzing entity performance. In one implementation, a method is provided that includes recognizing an identifier associated with an entity and accessing a data structure comprising information associated with a plurality of interactions. The method also comprises identifying one or more interactions of the plurality of interactions based on the recognized identifier. The method further comprises processing the information of the identified interactions to analyze a performance of the entity and providing the processed information to display the performance of the entity on a user interface.

Methods and systems for analyzing entity performance

Systems and methods are provided for analyzing entity performance. In accordance with one implementation, a method is provided that includes receiving data associated with a geographic region and transforming the received data into an object model. The method also includes analyzing the object model to associate the received data with a plurality of entities and to associate the received data with a plurality of sub-geographic regions of the geographic region. The method also includes applying a prediction model to the plurality of sub-geographic regions using the object model to determine a predicted performance for at least one entity of the plurality of entities. Further, the method includes determining actual performance for the at least one entity and providing a user interface that includes information associated with the predicted performance, the actual performance, or a combination of the predicted performance and the actual performance.

Systems and methods for analyzing performance of an entity

Systems and methods are provided for analyzing entity performance. In one implementation, a method is provided that includes receiving a request with one or more filter selections and accessing a data structure comprising a plurality of categories of information showing interactions associated with multiple entities. The method also comprises identifying a set of categories of the plurality of categories within the data structure based on the one or more filter selections. The method further comprises processing the information of the identified categories to analyze a performance of one or more entities of the multiple entities in accordance with the one or more filter selections and providing the processed information to display the performance of the one or more entities on a user interface.

Systems and methods are provided for analyzing entity performance. In one implementation, a method is provided that includes accessing a data structure comprising a plurality of interactions associated with multiple entities. The method also includes evaluating one or more interactions of the plurality of interactions associated with a consuming entity of the multiple entities. The method further includes determining whether the one or more interactions associated with the consuming entity comprise an identified location information of the consuming entity.

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Mountain View, CA, United States of America

Anirvan Mukherjee