Patents Assigned to Cerebri AI Inc.
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Patent number: 11941691Abstract: Provided is process, including: obtaining interaction-event records; determining, based on at least some of the interaction-event records, sets of event-risk scores, wherein: at least some respective event-risk scores are indicative of an effective of a respective risk ascribed by a first entity to a respective aspect of a second entity; and at least some respective event-risk scores are based on both: respective contributions of respective corresponding events to a subsequent event, and a risk ascribed to a subsequent event; and storing the sets of event-risk scores in memory.Type: GrantFiled: August 12, 2022Date of Patent: March 26, 2024Assignee: CEREBRI AI INC.Inventors: Jean Belanger, Alain Briancon, James Stojanov, Gabriel M. Silberman
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Patent number: 11922435Abstract: In some implementations, a computing device determines an event timeline that comprises one or more finance-related events associated with a person. A production classifier may be used to determine (i) an individual contribution of each event in the event timeline to a financial capacity of the person and (ii) a first decision regarding whether to extend credit to the person. A bias monitoring classifier may, based on the event timeline, determine a second decision whether to extend credit to the person. The bias monitoring classifier may be trained using pseudo-unbiased data. If a difference between the first decision and the second decision satisfies a threshold, the production classifier may be modified to reduce bias in decisions made by the production classifier.Type: GrantFiled: September 1, 2020Date of Patent: March 5, 2024Assignee: CEREBRI AI INC.Inventors: Gabriel M. Silberman, Michael Louis Roberts, Jean Belanger, Karen Bennet
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Patent number: 11900397Abstract: In some implementations, an event timeline that includes one or more interactions between a customer and a supplier may be determined. A starting value may be assigned to individual events in the event timeline. A sub-sequence comprising a portion of the event timeline that includes at least one reference event may be selected. A classifier may be used to determine a previous relative value for a previous event that occurred before the reference event and to determine a next relative value for a next event that occurred after the reference event until all events in the event timeline have been processed. The events in the event timeline may be traversed and a monetized value index assigned to individual events in the event timeline.Type: GrantFiled: September 15, 2022Date of Patent: February 13, 2024Assignee: Cerebri AI Inc.Inventors: Jean Belanger, Michael L. Roberts, Gabriel M. Silberman, Karen Bennet
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Patent number: 11893520Abstract: Provided is a process that includes sharing information among two or more parties or systems for modeling and decision-making purposes, while limiting the exposure of details either too sensitive to share, or whose sharing is controlled by laws, regulations, or business needs.Type: GrantFiled: June 7, 2022Date of Patent: February 6, 2024Assignee: Cerebri AI Inc.Inventors: Gabriel Mauricio Silberman, Alain Charles Briancon, Lee David Harper, Luke Philip Reding, David Alexander Curry, Jean Joseph Belanger, Michael Thomas Wegan, Thejas Narayana Prasad
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Patent number: 11783375Abstract: Provided is a process, including: obtaining a first training dataset, training a first machine-learning model on the first training dataset, obtaining a set of candidate question sequences, forming virtual subject-entity records, forming a second training dataset, training a second machine-learning model, and storing the adjusted parameters of the second machine-learning model in memory.Type: GrantFiled: July 8, 2022Date of Patent: October 10, 2023Assignee: Cerebri AI Inc.Inventors: Alain Charles Briancon, Jean Joseph Belanger, James Cvetan Stojanov, Christopher Michael Coovrey, Pranav Mahesh Makhijani, Gregory Klose, Max Changchun Huang, Mounib Mohamad Ismail, Michael Henry Engeling, Hongshi Li
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Patent number: 11776060Abstract: Provided is a process including: writing, with a computing system, a first plurality of classes using object-oriented modelling of modelling methods; writing, with the computing system, a second plurality of classes using object-oriented modelling of governance; scanning, with the computing system, a set of libraries collectively containing both modelling object classes among the first plurality of classes and governance classes among the second plurality of classes to determine class definition information; using, with the computing system, at least some of the class definition information to produce object manipulation functions, wherein the object manipulation functions allow a governance system to access methods and attributes of classes among first plurality of classes or the second plurality of classes to manipulate objects of at least some of the modelling object classes; and using at least some of the class definition information to effectuate access to the object manipulation functions.Type: GrantFiled: June 3, 2020Date of Patent: October 3, 2023Assignee: Cerebri AI Inc.Inventors: Alain Charles Briancon, Jean Joseph Belanger, Chris Michael Coovrey, Thejas Narayana Prasad, Mirza Safiullah Baig
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Patent number: 11757850Abstract: Disclosed herein are methods, systems, and processes for distributed logging for securing non-repudiable transactions. Credentials, request information, response information, and action items generated and received by a requesting computing system and a responding computing system, and transmitted between the requesting computing system and the responding computing system are separately recorded and stored in a requestor log maintained by the requesting computing system and in a responder log maintained by the responding computing system.Type: GrantFiled: June 29, 2021Date of Patent: September 12, 2023Assignee: Cerebri AI Inc.Inventors: Gabriel M. Silberman, Jean Belanger, Karen Bennet, Michael L. Roberts, Jay M. Williams
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Out-of-band authentication to access web-service with indication of physical access to client device
Patent number: 11647023Abstract: Provided is a process that affords out-of-band authentication for confirmation of physical access or when a device utilized for out-of-band authentication lacks connectivity to a network. An asymmetric cryptographic key-pair is established, a first device obtaining a key operable to decrypt data. A remote server obtaining a key operable to encrypt data and associating that key with an identifier of an identity or account associated with a user. An access attempt from the second device is received in association with the identifier of the identity associated with the user. A notification including data encrypted by the encryption key is generated by the remote server and transmitted to the second device. The first device obtains the notification data from the second device and decrypts the data to determine a notification response which is returned to the remote server for verification to permit or deny the access attempt of the second device.Type: GrantFiled: October 14, 2021Date of Patent: May 9, 2023Assignee: Cerebri AI Inc.Inventors: George Avetisov, Bojan Simic, Roman Kadinsky -
Patent number: 11636393Abstract: Provided is a process including: obtaining, for a plurality of entities, entity logs, wherein: the entity logs comprise events involving the entities, a first subset of the events are actions by the entities, at least some of the actions by the entities are targeted actions, and the events are labeled according to an ontology of events having a plurality of event types; training, with one or more processors, based on the entity logs, a predictive machine learning model to predict whether an entity characterized by a set of inputs to the model will engage in a targeted action in a given duration of time in the future; and storing the trained predictive machine learning model in memory.Type: GrantFiled: May 6, 2020Date of Patent: April 25, 2023Assignee: Cerebri AI Inc.Inventors: Sathish Kumar Lakshmipathy, Eyal Ben Zion, David Alexander Curry, Alain Charles Briancon, Michael Henry Engeling, Dmitrii Aleksandrovich Boldyrev, Sara Amini
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Patent number: 11620477Abstract: Provided is a process including: writing classes using object-oriented modelling of modeling topics; scanning the classes to determine class definition information; receiving from a subscribing modeling object a request for a subscription to a given modeling topic in a given modeling topic class, the subscription request including a modeling topic filter to select the given modeling topic from a plurality of modeling topics described by the given modeling topic class; registering a modeling topic accessor associated with the subscribing modeling object and a modeling topic mutator associated with the subscribing modeling object; processing, through the modeling topic filter a modeling topic that is accessed through an accessor and is described by the modeling topic class, the modeling topic being received from a modeling publisher object; notifying the subscribing object of the received modeling topic through a registered modeling topic listener; and mutating the received modeling topic.Type: GrantFiled: June 3, 2020Date of Patent: April 4, 2023Assignee: Cerebri AI Inc.Inventors: Bryan Wayne Collins, Eric Paver Simon, Alain Charles Briancon, Mirza Safiullah Baig, Yarden Arane, Wenjie Wu, Divya Karumuri, Kevin Bryce
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Patent number: 11615271Abstract: Provided is a process of modeling methods organized in racks of a machine learning pipeline to facilitate optimization of performance using modelling methods for implementation of machine learning design in an object-oriented modeling (OOM) framework, the process including: writing classes using object-oriented modelling of optimization methods, modelling methods, and modelling racks; writing parameters and hyper-parameters of the modeling methods as attributes as the modeling methods; scanning modelling racks classes to determine first class definition information; selecting a collection of rack and selecting modeling method objects; scanning modelling method classes to determine second class definition information; assigning racks and locations within the racks to modeling method objects; and invoking the class definition information to produce object manipulation functions that allow access the methods and attributes of at least some of the modeling method objects, the manipulation functions being configurType: GrantFiled: June 3, 2020Date of Patent: March 28, 2023Assignee: Cerebri AI Inc.Inventors: Eyal Ben Zion, Alain Charles Briancon, Pranav Mahesh Makhijani, Thejas Narayana Prasad, Sara Amini, Jian Deng, Ngoc Thu Nguyen, Jean Joseph Belanger
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Patent number: 11599752Abstract: Provided is a process including: writing modelling-object classes using object-oriented modelling of the modelling methods, the modelling-object classes being members of a set of class libraries; writing quality-management classes using object-oriented modelling of quality management, the quality-management classes being members of the set of class libraries; scanning modelling-object classes in the set of class libraries to determine modelling-object class definition information; scanning quality-management classes in the set of class libraries to determine quality-management class definition information; using the modelling-object class definition information and the quality-management class definition information to produce object manipulation functions that allow a quality management system to access methods and attributes of modelling-object classes to manipulate objects of the modelling-object classes; and using the modelling-object class definition information and the quality-management class definitioType: GrantFiled: June 3, 2020Date of Patent: March 7, 2023Assignee: Cerebri AI Inc.Inventors: Alain Charles Briancon, Jean Joseph Belanger, Chris Michael Coovrey, Travis Stanton Penn, Divya Karumuri, Valisis Sotiris
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Patent number: 11556846Abstract: Provided is a process that includes sharing information among two or more parties or systems for modeling and decision-making purposes, while limiting the exposure of details either too sensitive to share, or whose sharing is controlled by laws, regulations, or business needs.Type: GrantFiled: October 3, 2019Date of Patent: January 17, 2023Assignee: Cerebri AI Inc.Inventors: Gabriel Mauricio Silberman, Alain Charles Briancon, Lee David Harper, Luke Philip Reding, David Alexander Curry, Jean Joseph Belanger, Michael Thomas Wegan, Thejas Narayana Prasad
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Patent number: 11537878Abstract: Provided is a process, including: obtaining a first training dataset of subject-entity records; training a first machine-learning model on the first training dataset; forming virtual subject-entity records by appending members of a set of candidate action sequences to time-series of at least some of the subject-entity records; forming a second training dataset by labeling the virtual subject-entity records with predictions of the first machine-learning model; and training a second machine-learning model on the second training dataset.Type: GrantFiled: May 9, 2019Date of Patent: December 27, 2022Assignee: Cerebri AI Inc.Inventors: Gabriel M. Silberman, Alain Briançon, Gregory Klose, Michael Wegan, Lee Harper, Andrew Kraemer, Arun Prakash
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Patent number: 11501213Abstract: Provided is a process including: obtaining, for a plurality of entities, entity logs, wherein: the entity logs comprise events involving the entities, a first subset of the events are actions by the entities, at least some of the actions by the entities are targeted actions, and the events are labeled according to an ontology of events having a plurality of event types; training, with one or more processors, based on the entity logs, a predictive machine learning model to predict whether an entity characterized by a set of inputs to the model will engage in a targeted action in a given geographic locale in the future; and storing the training the trained predictive machine learning model in memory.Type: GrantFiled: May 6, 2020Date of Patent: November 15, 2022Assignee: Cerebri AI Inc.Inventors: Alain Charles Briancon, Eyal Ben Zion, Sumant Sudhir Kawale, Sara Amini
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Patent number: 11481790Abstract: In some implementations, an event timeline that includes one or more interactions between a customer and a supplier may be determined. A starting value may be assigned to individual events in the event timeline. A sub-sequence comprising a portion of the event timeline that includes at least one reference event may be selected. A classifier may be used to determine a previous relative value for a previous event that occurred before the reference event and to determine a next relative value for a next event that occurred after the reference event until all events in the event timeline have been processed. The events in the event timeline may be traversed and a monetized value index assigned to individual events in the event timeline.Type: GrantFiled: August 24, 2020Date of Patent: October 25, 2022Assignee: Cerebri AI Inc.Inventors: Jean Belanger, Michael L. Roberts, Gabriel M. Silberman, Karen Bennet
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Patent number: 11449931Abstract: Provided is process, including: obtaining interaction-event records; determining, based on at least some of the interaction-event records, sets of event-risk scores, wherein: at least some respective event-risk scores are indicative of an effective of a respective risk ascribed by a first entity to a respective aspect of a second entity; and at least some respective event-risk scores are based on both: respective contributions of respective corresponding events to a subsequent event, and a risk ascribed to a subsequent event; and storing the sets of event-risk scores in memory.Type: GrantFiled: July 23, 2020Date of Patent: September 20, 2022Assignee: Cerebri AI Inc.Inventors: Jean Belanger, Alain Briancon, James Stojanov, Gabriel M. Silberman
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Patent number: 11416896Abstract: Provided is a process, including: obtaining a first training dataset, training a first machine-learning model on the first training dataset, obtaining a set of candidate question sequences, forming virtual subject-entity records, forming a second training dataset, training a second machine-learning model, and storing the adjusted parameters of the second machine-learning model in memory.Type: GrantFiled: June 18, 2021Date of Patent: August 16, 2022Assignee: Cerebri AI Inc.Inventors: Alain Charles Briancon, Jean Joseph Belanger, James Cvetan Stojanov, Christopher Michael Coovrey, Pranav Mahesh Makhijani, Gregory Klose, Max Changchun Huang, Mounib Mohamad Ismail, Michael Henry Engeling, Hongshi Li
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Patent number: 11386295Abstract: Provided is a process that includes sharing information among two or more parties or systems for modeling and decision-making purposes, while limiting the exposure of details either too sensitive to share, or whose sharing is controlled by laws, regulations, or business needs.Type: GrantFiled: October 3, 2018Date of Patent: July 12, 2022Assignee: Cerebri AI Inc.Inventors: Gabriel Mauricio Silberman, Alain Charles Briancon, Lee David Harper, Luke Philip Reding, David Alexander Curry, Jean Joseph Belanger, Michael Thomas Wegan, Thejas Narayana Prasad
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Patent number: 11082409Abstract: Disclosed herein are methods, systems, and processes for distributed logging for securing non-repudiable transactions. Credentials, request information, response information, and action items generated and received by a requesting computing system and a responding computing system, and transmitted between the requesting computing system and the responding computing system are separately recorded and stored in a requestor log maintained by the requesting computing system and in a responder log maintained by the responding computing system.Type: GrantFiled: October 17, 2019Date of Patent: August 3, 2021Assignee: Cerebri AI Inc.Inventors: Gabriel M. Silberman, Jean Belanger, Karen Bennet, Michael L. Roberts, Jay M. Williams