Palantir Technologies Inc.

Charles Shepherd

Daniel Patrick Cervelli

Peter Maag

Thomas Powell

Spencer Tank

Brian Lee

Ezra Spiro

Quentin Spencer-Harper

Andre Frederico Cavalheiro Menck

Anshuman Prasad

Dylan Scott

Kevin Verdieck

Alexander Ryan

Matthew Julius Wilson

Guillem Palou Visa

Arthur Thouzeau

Joanna Peller

Trevor Sontag

Trevor Fountain

Caroline Henry

Jennifer Yip

Marco Diciolla

Matthew Todd

Tom Alexander

Daniel Horbatt

Emily Nguyen

Various systems and methods are provided that display various geographic maps and depth graphs in an interactive user interface in substantially real-time in response to input from a user in order to determine information related to measured data points, depth levels, and geological layers and provide the determined information to the user in the interactive user interface. For example, a computing device may be configured to retrieve data from one or more databases and generate one or more interactive user interfaces. The one or more interactive user interfaces may display the retrieved data in a geographic map, a heat map, a cross-plot graph, or one or more depth graphs. The user interface may be interactive in that a user may manipulate any of the graphs to identify trends or current or future issues.

Interactive user interfaces for location-based data analysis

Systems, methods, non-transitory computer readable media can be configured to access a plurality of sensor logs corresponding to a first machine, each sensor log spanning at least a first period; access first computer readable logs corresponding to the first machine, each computer readable log spanning at least the first period, the computer readable logs comprising a maintenance log comprising a plurality of maintenance task objects, each maintenance task object comprising a time and a maintenance task type; determine a set of statistical metrics derived from the sensor logs; determine a set of log metrics derived from the computer readable logs; and determine, using a risk model that receives the statistical metrics and log metrics as inputs, fault probabilities or risk scores indicative of one or more fault types occurring in the first machine within a second period.

Machine fault modelling

Systems, methods, non-transitory computer readable media can be configured to accessing a target sensor log corresponding to a first machine; accessing one or more prior sensor logs corresponding to the first machine and one or more prior sensor logs corresponding to a plurality of second machines which are of the same type as the first machine; accessing a plurality of computer readable logs corresponding to the first machine and the second machines, the computer readable logs for each second machine comprising a maintenance log comprising a plurality of maintenance task objects, each maintenance task object comprising a time and a maintenance task type; determining a set of statistical metrics characterising a difference between the target sensor log and each prior sensor log; selecting a sub-set of the prior sensor logs in dependence upon the statistical metrics; analysing the maintenance logs to correlate each prior sensor log included in the subset to one or more correlated maintenance tasks; selecting a priority maintenance task based on the sub-set of prior sensor logs, t and the correlated maintenance tasks; and outputting the priority maintenance task.

Determining maintenance for a machine

Systems, methods, non-transitory computer readable media can be configured to access a plurality of sensor logs corresponding to a first machine, each sensor log spanning at least a first period. Access first computer readable logs corresponding to the first machine, each computer readable log spanning at least the first period, the computer readable logs comprising a maintenance log comprising a plurality of maintenance task objects, each maintenance task object comprising a time and a maintenance task type. Determine a set of statistical metrics derived from the sensor logs; determine a set of log metrics derived from the computer readable logs. Determine, using a risk model that receives the statistical metrics and log metrics as inputs, fault probabilities or risk scores indicative of one or more fault types occurring in the first machine within a second period.

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London, United Kingdom

Charles Shepherd