Palantir Technologies Inc.

Audi Ag

Volkswagen Ag

Jack Grossman

James Thompson

Myles Scolnick

Jim Inoue

David Cohen

Parvathy Menon

Adam Borochoff

Michael Harris

Michael Kross

Jason Ma

Matthew Sprague

Ilya Nepomnyashchiy

Bing Jie Fu

Steven Berler

Alex Smaliy

Julia Boortz

Quentin Spencer-Harper

Richard Niemi

Thomas Mcintyre

Michael Xiaoxuan Yang

Lawrence Manning

Gregory Martin

Carl Freeland

Bianca Rahill-Marier

Ryan Beiermeister

John Chakerian

Adam Torres

Andrew Elder

Brian H Hamilton

Sharon Hao

Mitchell Beard

Juan Ricafort

Kevin Verdieck

Paul Ryan

Xinyi Wang

Christopher Richbourg

Joshua Zavilla

Ryan Xie

Divya Mahalingam

Bradley Engel

Marc Frankel

Mark Elliot

Thomas Powell

Rick Ducott

Andy Chen

Aakash Goenka

Jeremy Kong

Matthew Jolda

Subbanarasimhiah Harish

Diogo Bonfim Moraes Morant De Holanda

Tao Wei

Francis Screene

Ragnar Vorel

David Skiff

Daniel Erenrich

Arseny Bogomolov

Alessandro Mingione

James Toggweiler

Cooper Bills

Antoine Llorca

Eric Anderson

Nathaniel Klein

Marvin Sum

Gautam Punukollu

Eric Raboin

Matthew Levan

Christopher Cook

Kevin Simons

Matthew Gerhardt

Stefan Henze

Gabriel Boning

Westin Miller

Shelby Pefley

James Rosswog

Tim O'Brien

Noah Öhrner

Ji Young Ohn

Drew Thoennes

In Hwa Kang

Nikita Morozov

Peter Goldberg

Computing systems methods, and non-transitory storage media are provided for obtaining a request or query indicative of a resource, tool, task, or workflow, determining any entities including data, logic, dependencies and libraries, within a remote server, corresponding to the resource, tool, task, or workflow, and selectively provisioning or caching, from the remote server, the entities at the computing system.

Caching framework to increase resilience to network instability

A search request relating to one or more datasets in the data repository can be received, the search request comprising a display request to display at least a portion of the one or more datasets. In response to the search request, a searchable database can be generated from the one or more datasets in a data repository based on ontological data associated with the one or more datasets. An object view of at least the portion of one or more datasets can be generated from the searchable database, the view being generated based on the ontological data. The generated object view can be provided to be displayed on a display device.

System and method for querying a data repository

This disclosure relates to a system and method for data analysis. According to a first aspect, there is described a method, the method being performed using one or more processors, comprising: receiving one or more user inputs indicative of one or more relationships between data in a plurality of datasets; determining, based on the one or more user inputs, at least one object view for visualizing the data in the plurality of datasets; generating, based on the one or more user inputs, metadata comprising: an object graph indicative of the one or more relationships between two or more of the plurality of datasets; and information identifying the at least one object view; and in response to a query relating to the plurality of datasets, using the metadata to determine how response data responding to the query should be provided.

Data analysis system and method

Embodiments of the present disclosure relate to a data analysis system that may automatically generate memory-efficient clustered data structures, automatically analyze those clustered data structures, and provide results of the automated analysis in an optimized way to an analyst. The automated analysis of the clustered data structures (also referred to herein as data clusters) may include an automated application of various criteria or rules so as to generate a compact, human-readable analysis of the data clusters. The human-readable analyses (also referred to herein as 'summaries' or “conclusions”) of the data clusters may be organized into an interactive user interface so as to enable an analyst to quickly navigate among information associated with various data clusters and efficiently evaluate those data clusters in the context of, for example, a fraud investigation. Embodiments of the present disclosure also relate to automated scoring of the clustered data structures.

Phishing data item clustering and analysis

Various systems and methods are provided for accessing and traversing one or more data structures and generating a functional user interface that can enable non-technical users to quickly and dynamically search for resources of an organization and/or associated documents, events, entities, and/or other data. The user interfaces are interactive such that a user may make selections, provide inputs, and/or manipulate outputs. In response to various user inputs, the system automatically accesses and traverses data structures relating to resources, documents, events, entities, and other data, identifies resources, documents, events, entities, and/or other data that meet search criteria, and returns search results including resources that meet the search criteria and/or resources that are associated with documents, events, entities, and/or other data that meet the search criteria. Resources, documents, events, entities, and other data can be represented by respective types of data structures, which may be associated with other types of data structures. Properties or fields of data structures can have security settings and permissions associated with them.

System and user interfaces for searching resources and related documents using data structures

Embodiments of the present disclosure relate to a data analysis system that may automatically generate memory-efficient clustered data structures, automatically analyze those clustered data structures, and provide results of the automated analysis in an optimized way to an analyst. The automated analysis of the clustered data structures (also referred to herein as data clusters) may include an automated application of various criteria or rules so as to generate a compact, human-readable analysis of the data clusters. The human-readable analyses (also referred to herein as 'summaries' or 'conclusions') of the data clusters may be organized into an interactive user interface so as to enable an analyst to quickly navigate among information associated with various data clusters and efficiently evaluate those data clusters in the context of, for example, a fraud investigation. Embodiments of the present disclosure also relate to automated scoring of the clustered data structures.

Computer-implemented systems and methods are disclosed to interface with one or more storage devices storing a plurality of documents, wherein each of the plurality of documents is associated with one or more tags of one or more predefined hierarchies of tags, wherein the one or more hierarchies of tags include multiple dimensions. In accordance with some embodiments, a method is provided to identify one or more documents from the data storage devices. The method comprises acquiring, via an interface, a selection of one or more tags of the one or more predefined hierarchies of tags. The method further comprises identifying one or more documents from the data storage devices in response to the selection, the identified one or more documents having tags that have a relationship with the selected tags, and providing data corresponding to the identified documents for displaying in the interface.

Systems and methods for organizing and identifying documents via hierarchies and dimensions of tags

Systems and methods are provided for providing an object platform for datasets A definition of an object may be obtained. The object may be associated with information stored in one or more datasets. The information may be determined based at least in part on the definition of the object. The object may be stored in a cache such that the information associated with the object is also stored in the cache. One or more interfaces through which requests to perform one or more operations on the object are able to be submitted may be provided.

Systems and methods for providing an object platform for datasets

Computer-implemented systems and methods are disclosed for automatically generating and displaying a chronology of events, where events may be represented by data objects in one or more databases. Events/data objects may be identified as relevant to an investigation or analysis based on specified criteria. A timeline may be generated based on the identified set of relevant events, and interactive user interfaces may be generated and displayed that present the events as a timeline and a list. Events may be selected from the timeline or the list, may be identified as key events in the chronology, and additional events related to a selected event may be determined and added to the chronology. Timelines may be compared to other data sets, including other timelines, other event lists, and other relevant data.

Systems and interactive user interfaces for automatic generation of temporal representation of data objects

This disclosure relates to a system and method for data analysis. According to a first aspect, there is described a method, the method being performed using one or more processors, comprising: receiving one or more user inputs indicative of one or more relationships between data in a plurality of datasets; determining, based on the one or more user inputs, at least one object view for visualising the data in the plurality of datasets; generating, based on the one or more user inputs, metadata comprising: an object graph indicative of the one or more relationships between two or more of the plurality of datasets; and information identifying the at least one object view; and in response to a query relating to the plurality of datasets, using the metadata to determine how response data responding to the query should be provided.

External malware data item clustering and analysis

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San Francisco, CA, United States of America

Jack Grossman