Patents by Inventor Marc AMPHLETT

Marc AMPHLETT has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Patent number: 11394674
    Abstract: A system that transforms electronic messages into annotated messages that include contextual information to aid a recipient in utilizing the electronic message, understanding its meaning, and responding to the message. Annotations are additions or modifications to the original message with contextual information that is related to the features and contents of the original message. Message features are extracted and used to search one or more sources of contextual information. Relevant items are retrieved and added to the message, for example as attachments, hyperlinks, or inline notes. Machine learning techniques may be used to generate or refine modules for feature extraction and information selection. Feedback components may be used to track the usage and value of annotations, in order to iteratively improve the annotation system.
    Type: Grant
    Filed: April 17, 2017
    Date of Patent: July 19, 2022
    Assignee: Mimecast Services Ltd.
    Inventors: Nathaniel Borenstein, Marc Amphlett, Clive Jordan, Max Linscott, Niall O'Malley, Jacqueline Osborne, Luke Pentreath, Oliver Scott, Rahul Sharma
  • Publication number: 20170289080
    Abstract: A system that transforms electronic messages into annotated messages that include contextual information to aid a recipient in utilizing the electronic message, understanding its meaning, and responding to the message. Annotations are additions or modifications to the original message with contextual information that is related to the features and contents of the original message. Message features are extracted and used to search one or more sources of contextual information. Relevant items are retrieved and added to the message, for example as attachments, hyperlinks, or inline notes. Machine learning techniques may be used to generate or refine modules for feature extraction and information selection. Feedback components may be used to track the usage and value of annotations, in order to iteratively improve the annotation system.
    Type: Application
    Filed: April 17, 2017
    Publication date: October 5, 2017
    Inventors: Nathaniel Borenstein, Marc Amphlett, Clive Jordan, Max Linscott, Niall O'Malley, Jacqueline Osborne, Luke Pentreath, Oliver Scott, Rahul Sharma
  • Patent number: 9628419
    Abstract: A system that transforms electronic messages into annotated messages that include contextual information to aid a recipient in utilizing the electronic message, understanding its meaning, and responding to the message. Annotations are additions or modifications to the original message with contextual information that is related to the features and contents of the original message. Message features are extracted and used to search one or more sources of contextual information. Relevant items are retrieved and added to the message, for example as attachments, hyperlinks, or inline notes. Machine learning techniques may be used to generate or refine modules for feature extraction and information selection. Feedback components may be used to track the usage and value of annotations, in order to iteratively improve the annotation system.
    Type: Grant
    Filed: July 29, 2015
    Date of Patent: April 18, 2017
    Assignee: MIMECAST NORTH AMERICA, INC.
    Inventors: Nathaniel Borenstein, Marc Amphlett, Clive Jordan, Max Linscott, Niall O'Malley, Jacqueline Osborne, Luke Pentreath, Oliver Scott, Rahul Sharma
  • Publication number: 20170034087
    Abstract: A system that transforms electronic messages into annotated messages that include contextual information to aid a recipient in utilizing the electronic message, understanding its meaning, and responding to the message. Annotations are additions or modifications to the original message with contextual information that is related to the features and contents of the original message. Message features are extracted and used to search one or more sources of contextual information. Relevant items are retrieved and added to the message, for example as attachments, hyperlinks, or inline notes. Machine learning techniques may be used to generate or refine modules for feature extraction and information selection. Feedback components may be used to track the usage and value of annotations, in order to iteratively improve the annotation system.
    Type: Application
    Filed: July 29, 2015
    Publication date: February 2, 2017
    Applicant: MIMECAST NORTH AMERICA, INC.
    Inventors: Nathaniel BORENSTEIN, Marc AMPHLETT, Clive JORDAN, Max LINSCOTT, Niall O'MALLEY, Jacqueline OSBORNE, Luke PENTREATH, Oliver SCOTT, Rahul SHARMA