Optum Services (Ireland) Limited

Optum, Inc.

Kevin Larkin

Conor Breen

Peter Cogan

Colum Foley

Claudia Burri Devereux

Nancy N Flores

David Scott Bachert

Anthony R O'Neill

Eric Brian Tal

Conor M McDermott

Jamie Howard

Octavio Palomo Sanchez

Mark Tonge

Various embodiments of the present disclosure provide message filtering and routing techniques for intelligently routing messages within a complex network domain. The techniques may include receiving, originating from a provider system, a provider-platform request message that identifies a provider service request and a designated coverage platform corresponding to the provider service request. In response to an identification of a designation error associated with the designated coverage platform, the techniques may include providing to a primary coverage platform, using a cross-platform interface, a platform-platform request message that identifies the provider service request; and providing an alert message to the provider system.

Intelligent message filtering and forwarding using cross platform interfaces

Various embodiments of the present disclosure provide methods, apparatus, systems, computing devices, computing entities, and/or the like for performing predictive data analysis, wherein an opportunity prediction is generated for an input data object using a relationship matrix database object and based at least in part on a network segment associated with the input data object.

Predictive data analysis operations using a relationship machine learning framework

Various embodiments of the present invention disclose techniques for orchestrating a complex data processing scheme for an investigative process using a machine-learning based orchestration model that is trained to optimize the use of computing resources based at least in part on a feedback loop. An input data object associated with an investigative process can be selected for investigation; a predictive data analysis sub-routine for processing the input data object can be intelligently selected from a plurality of predictive data analysis sub-routines by the machine-learning based orchestration model; and a processing orchestration action can be initiated based at least in part on an investigative score output by the predictive data analysis sub-routine. The processing orchestration action can include closing the input data object, continuing to process the input data object with additional predictive data analysis sub-routines, or passing the input data object to a predictive entity for further processing.

Intelligent automatic orchestration of machine-learning based processing pipeline

Various embodiments of the present invention provide methods, apparatus, systems, computing devices, computing entities, and/or the like for performing predictive mapping operations with respect to a ground-truth database table. Certain embodiments of the present invention utilize systems, methods, and computer program products that perform predictive mapping operations utilizing a hierarchical string matching machine learning framework using at least one or more of an exact match model, a probabilistic match model, a disjoint match model, and an embedding-based match model.

Machine learning techniques for generating string-based database mapping prediction

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Kildare, Ireland

Kevin Larkin