Hyper Labs Inc., DBA HyperScience

États‑Unis d’Amérique

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Type PI
        Marque 15
        Brevet 8
Juridiction
        États-Unis 10
        International 7
        Canada 6
Date
2025 3
2024 2
2023 8
2022 1
2021 2
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Classe IPC
G06N 3/08 - Méthodes d'apprentissage 6
G06V 30/40 - Reconnaissance des formes à partir d’images axée sur les documents 4
G06F 40/151 - Transformation 3
G06K 9/62 - Méthodes ou dispositions pour la reconnaissance utilisant des moyens électroniques 3
G06N 20/20 - Techniques d’ensemble en apprentissage automatique 3
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Classe NICE
09 - Appareils et instruments scientifiques et électriques 9
42 - Services scientifiques, technologiques et industriels, recherche et conception 9
Statut
En Instance 4
Enregistré / En vigueur 19

1.

HYPERCELL

      
Numéro d'application 1858392
Statut Enregistrée
Date de dépôt 2025-01-29
Date d'enregistrement 2025-01-29
Propriétaire Hyper Labs Inc. (USA)
Classes de Nice  ?
  • 09 - Appareils et instruments scientifiques et électriques
  • 42 - Services scientifiques, technologiques et industriels, recherche et conception

Produits et services

Providing downloadable software for automating office, business and administrative processes and procedures; providing downloadable software for the transcription of text through the use of machine learning and natural language processing; providing downloadable software for extracting data and transcription of text from images and scanned documents and identifying, collecting, and learning from human input to ensure accuracy of data extraction through the use of machine learning and natural language processing. Providing an online, non-downloadable software infrastructure platform for automating office, business and administrative processes and procedures; providing an online, non-downloadable software infrastructure platform for transcription of text through the use of machine learning and natural language processing; providing an online, non-downloadable software infrastructure platform for extracting data and transcription of text from images and scanned documents and identifying, collecting, and learning from human input to ensure accuracy of data extraction through the use of machine learning and natural language processing; technological consultancy and providing information relating to computer technology and programming relating to the management, reporting, organization, validation, and quality assurance of data in the field of artificial intelligence (AI) software customization; technological consultancy and providing information relating to computer technology and programming for training large language models in the field of artificial intelligence.

2.

REAL TIME MACHINE LEARNING FOR GUIDED DOCUMENT ANNOTATIONS

      
Numéro d'application US2024048506
Numéro de publication 2025/075853
Statut Délivré - en vigueur
Date de dépôt 2024-09-26
Date de publication 2025-04-10
Propriétaire HYPER LABS, INC. d/b/a HYPERSCIENCE (USA)
Inventeur(s)
  • Beauchesne, Jocelyn
  • Jain, Pushkar
  • Edvinsson, Johan
  • Lohchab, Akhil

Abrégé

A method for annotating documents. When a new document is received from an external device, the new document is analyzed to determine a group of documents that the new document is most similar to. Once the group of documents is determined on or more trained machined learning models that have been trained on previous documents associated with the group of documents are retrieved and used to analyze the new document. Based on the analysis the one or more trained machine learning models produce one or more annotation suggestions and present these to a user; the user may then provide one or more corrections, which are then used along with one or more validated annotation suggestions to annotate the new document as well as update the one or more trained machine learning models.

Classes IPC  ?

  • G06F 40/169 - Annotation, p. ex. données de commentaires ou notes de bas de page
  • G06F 16/93 - Systèmes de gestion de documents
  • G06N 3/045 - Combinaisons de réseaux
  • G06N 3/08 - Méthodes d'apprentissage

3.

HYPERCELL

      
Numéro d'application 240329400
Statut En instance
Date de dépôt 2025-01-29
Propriétaire Hyper Labs Inc. (USA)
Classes de Nice  ?
  • 09 - Appareils et instruments scientifiques et électriques
  • 42 - Services scientifiques, technologiques et industriels, recherche et conception

Produits et services

(1) Providing downloadable software for automating office, business and administrative processes and procedures; providing downloadable software for the transcription of text through the use of machine learning and natural language processing; providing downloadable software for extracting data and transcription of text from images and scanned documents and identifying, collecting, and learning from human input to ensure accuracy of data extraction through the use of machine learning and natural language processing. (1) Providing an online, non-downloadable software infrastructure platform for automating office, business and administrative processes and procedures; providing an online, non-downloadable software infrastructure platform for transcription of text through the use of machine learning and natural language processing; providing an online, non-downloadable software infrastructure platform for extracting data and transcription of text from images and scanned documents and identifying, collecting, and learning from human input to ensure accuracy of data extraction through the use of machine learning and natural language processing; technological consultancy and providing information relating to computer technology and programming relating to the management, reporting, organization, validation, and quality assurance of data in the field of artificial intelligence (AI) software customization; technological consultancy and providing information relating to computer technology and programming for training large language models in the field of artificial intelligence.

4.

HYPERCELL

      
Numéro de série 98710818
Statut En instance
Date de dépôt 2024-08-21
Propriétaire Hyper Labs Inc., DBA Hyperscience (USA)
Classes de Nice  ?
  • 09 - Appareils et instruments scientifiques et électriques
  • 42 - Services scientifiques, technologiques et industriels, recherche et conception

Produits et services

Downloadable software for automating office, business and administrative processes and procedures; downloadable software for the transcription of text through the use of machine learning and natural language processing; downloadable software for extracting data and transcription of text from images and scanned documents and identifying, collecting, and learning from human input to ensure accuracy of data extraction through the use of machine learning and natural language processing (Based on Use in Commerce) Providing an online, non-downloadable software infrastructure platform for automating office, business and administrative processes and procedures; Providing an online, non-downloadable software infrastructure platform for transcription of text through the use of machine learning and natural language processing; Providing an online, non-downloadable software infrastructure platform for extracting data and transcription of text from images and scanned documents and identifying, collecting, and learning from human input to ensure accuracy of data extraction through the use of machine learning and natural language processing; (Based on Intent To Use) Technical consulting and information services in the field of artificial intelligence (AI) software customization relating to the management, reporting, organization, validation, and quality assurance of data; Consulting and information services in the field of computer programing for training artificial intelligence large language models; Data automation and collection service using proprietary software for the collection, processing, and organization of large language model data in the field of artificial intelligence; Computer programming for the purpose of training large language models in the field of artificial intelligence.

5.

MACHINE LEARNING-BASED TEXT RECOGNITION SYSTEM WITH FINE-TUNING MODEL

      
Numéro d'application 18358506
Statut En instance
Date de dépôt 2023-07-25
Date de la première publication 2024-02-29
Propriétaire Hyper Labs, Inc. (USA)
Inventeur(s)
  • Stefanov, Stefan Iliev
  • Daskalov, Boris Nikolaev
  • Lohchab, Akhil

Abrégé

A non-transitory processor-readable medium stores instructions to be executed by a processor. The instructions cause the processor to receive a first trained machine learning model that generates a transcription based on a document. The instructions cause the processor to execute the first trained machine learning model and a second trained machine learning model to generate a refined transcription based on the transcription. The instructions cause the processor to execute a quality assurance program to generate a transcription score based on the document and the transcription. The instructions cause the processor to execute the quality assurance program to generate a refined transcription score based on the refined transcription and at least one of the document or the transcription. The at least one refined transcription score indicates an automation performance better than an automation performance for the at least one transcription score.

Classes IPC  ?

  • G06V 10/82 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant les réseaux neuronaux
  • G06F 40/151 - Transformation
  • G06N 3/08 - Méthodes d'apprentissage
  • G06N 5/01 - Techniques de recherche dynamiqueHeuristiquesArbres dynamiquesSéparation et évaluation
  • G06N 20/20 - Techniques d’ensemble en apprentissage automatique
  • G06V 30/19 - Reconnaissance utilisant des moyens électroniques
  • G06V 30/40 - Reconnaissance des formes à partir d’images axée sur les documents

6.

(H[S])

      
Numéro d'application 1762062
Statut Enregistrée
Date de dépôt 2023-10-05
Date d'enregistrement 2023-10-05
Propriétaire Hyper Labs Inc. (USA)
Classes de Nice  ? 42 - Services scientifiques, technologiques et industriels, recherche et conception

Produits et services

Software as a service (SAAS) services featuring software for automating office, business and administrative processes and procedures; software as a service (SAAS) services featuring software featuring natural language processing, image recognition and machine learning functionality; software as a service (SAAS) services featuring computer vision, machine learning, and natural language processing software for document processing, namely, extracting data from images and scanned documents and identifying, collecting, and learning from human input to ensure accuracy of data extraction.

7.

HYPERSCIENCE

      
Numéro d'application 1762061
Statut Enregistrée
Date de dépôt 2023-10-05
Date d'enregistrement 2023-10-05
Propriétaire Hyper Labs Inc. (USA)
Classes de Nice  ? 42 - Services scientifiques, technologiques et industriels, recherche et conception

Produits et services

Software as a service (SAAS) services featuring software for automating office, business and administrative processes and procedures; software as a service (SAAS) services featuring software featuring natural language processing, image recognition and machine learning functionality; software as a service (SAAS) services featuring computer vision, machine learning, and natural language processing software for document processing, namely, extracting data from images and scanned documents and identifying, collecting, and learning from human input to ensure accuracy of data extraction.

8.

(H[S])

      
Numéro d'application 229460300
Statut Enregistrée
Date de dépôt 2023-10-05
Date d'enregistrement 2026-03-02
Propriétaire Hyper Labs Inc. (USA)
Classes de Nice  ? 42 - Services scientifiques, technologiques et industriels, recherche et conception

Produits et services

(1) Software as a service (SAAS) services featuring software for automating office, business and administrative processes and procedures namely for automating document management, document, text, and image processing and extraction, data management and processing, data entry of accounts receivable and account collections and for providing related accounting, word processing and integrated email support, for searching and retrieving information across a computer network, for the analysis of business data and information, for optical character recognition, for converting document images into electronic format, for automating data extraction, collation of data and classification of data from documents, for processing logic and data validation, and for improving automation through database lookups; Software as a service (SAAS) services featuring software featuring natural language processing, image recognition and machine learning functionality for automating document management, document, text, and image processing and extraction, data management and processing, data entry of accounts receivable and account collections and for providing related accounting, word processing and integrated email support, for searching and retrieving information across a computer network, for the analysis of business data and information, for converting natural language into machine executable commands, for evaluating customer behaviour in online shops, for optical character recognition, for converting document images into electronic format, for automating data extraction, collation of data and classification of data from documents, for processing logic and data validation, and for improving automation through database lookups; Software as a service (SAAS) services featuring computer vision, machine learning, and natural language processing software for document, text, and image processing, namely, extracting business data from images and scanned documents and identifying, collecting, and learning from human input to ensure accuracy of document, text, and image data extraction

9.

HYPERSCIENCE

      
Numéro d'application 229459600
Statut Enregistrée
Date de dépôt 2023-10-05
Date d'enregistrement 2026-03-02
Propriétaire Hyper Labs Inc. (USA)
Classes de Nice  ? 42 - Services scientifiques, technologiques et industriels, recherche et conception

Produits et services

(1) Software as a service (SAAS) services featuring software for automating office, business and administrative processes and procedures namely for automating document management, document, text, and image processing and extraction, data management and processing, data entry of accounts receivable and account collections and for providing related accounting, word processing and integrated email support, for searching and retrieving information across a computer network, for the analysis of business data and information, for optical character recognition, for converting document images into electronic format, for automating data extraction, collation of data and classification of data from documents, for processing logic and data validation, and for improving automation through database lookups; Software as a service (SAAS) services featuring software featuring natural language processing, image recognition and machine learning functionality for automating document management, document, text, and image processing and extraction, data management and processing, data entry of accounts receivable and account collections and for providing related accounting, word processing and integrated email support, for searching and retrieving information across a computer network, for the analysis of business data and information, for converting natural language into machine executable commands, for evaluating customer behaviour in online shops, for optical character recognition, for converting document images into electronic format, for automating data extraction, collation of data and classification of data from documents, for processing logic and data validation, and for improving automation through database lookups; Software as a service (SAAS) services featuring computer vision, machine learning, and natural language processing software for document, text, and image processing, namely, extracting business data from images and scanned documents and identifying, collecting, and learning from human input to ensure accuracy of document, text, and image data extraction

10.

HYPERSCIENCE

      
Numéro de série 97937681
Statut Enregistrée
Date de dépôt 2023-05-15
Date d'enregistrement 2024-09-03
Propriétaire Hyper Labs Inc., DBA Hyperscience ()
Classes de Nice  ? 42 - Services scientifiques, technologiques et industriels, recherche et conception

Produits et services

Software as a service (SAAS) services featuring software for automating office, business and administrative processes and procedures; Software as a service (SAAS) services featuring software for natural language processing, image recognition, and machine learning; Software as a service (SAAS) services featuring software for extracting data from images and scanned documents and identifying, collecting, and learning from human input to ensure accuracy of data extraction through the use of machine learning and natural language processing

11.

(H[S])

      
Numéro de série 97937684
Statut Enregistrée
Date de dépôt 2023-05-15
Date d'enregistrement 2024-09-03
Propriétaire Hyper Labs Inc., DBA Hyperscience ()
Classes de Nice  ? 42 - Services scientifiques, technologiques et industriels, recherche et conception

Produits et services

Software as a service (SAAS) services featuring software for automating office, business and administrative processes and procedures; Software as a service (SAAS) services featuring software for natural language processing, image recognition, and machine learning; Software as a service (SAAS) services featuring software for extracting data from images and scanned documents and identifying, collecting, and learning from human input to ensure accuracy of data extraction through the use of machine learning and natural language processing

12.

Apparatuses, methods, and systems for 3-channel dynamic contextual script recognition using neural network image analytics and 4-tuple machine learning with enhanced templates and context data

      
Numéro d'application 16889151
Numéro de brevet 11610084
Statut Délivré - en vigueur
Date de dépôt 2020-06-01
Date de la première publication 2023-03-21
Date d'octroi 2023-03-21
Propriétaire Hyper Labs, Inc. (USA)
Inventeur(s)
  • Daskalov, Boris Nikolaev
  • Balchev, Daniel Biser

Abrégé

In some embodiments, a method includes training a first machine learning model based on multiple documents and multiple templates associated with the multiple documents. The method further includes executing the first machine learning model to generate multiple relevancy masks, the multiple relevancy masks to remove a visual structure of the multiple templates from a visual structure of the multiple documents. The method further includes generating multiple multichannel field images to include the multiple relevancy masks and at least one of the multiple documents or the multiple templates. The method further includes training a second machine learning model based on the multiple multichannel field images and multiple non-native texts associated with the multiple documents. The method further includes executing the second machine learning model to generate multiple non-native texts from the multiple multichannel field images.

Classes IPC  ?

  • G06K 9/62 - Méthodes ou dispositions pour la reconnaissance utilisant des moyens électroniques
  • G06N 3/04 - Architecture, p. ex. topologie d'interconnexion
  • G06N 3/08 - Méthodes d'apprentissage
  • G06V 10/40 - Extraction de caractéristiques d’images ou de vidéos
  • G06V 30/10 - Reconnaissance de caractères

13.

Machine learning-based text recognition system with fine-tuning model

      
Numéro d'application 17969817
Numéro de brevet 11854251
Statut Délivré - en vigueur
Date de dépôt 2022-10-20
Date de la première publication 2023-02-16
Date d'octroi 2023-12-26
Propriétaire Hyper Labs, Inc. (USA)
Inventeur(s)
  • Stefanov, Stefan Iliev
  • Daskalov, Boris Nikolaev
  • Lohchab, Akhil

Abrégé

A non-transitory processor-readable medium stores instructions to be executed by a processor. The instructions cause the processor to receive a first trained machine learning model that generates a transcription based on a document. The instructions cause the processor to execute the first trained machine learning model and a second trained machine learning model to generate a refined transcription based on the transcription. The instructions cause the processor to execute a quality assurance program to generate a transcription score based on the document and the transcription. The instructions cause the processor to execute the quality assurance program to generate a refined transcription score based on the refined transcription and at least one of the document or the transcription. The at least one refined transcription score indicates an automation performance better than an automation performance for the at least one transcription score.

Classes IPC  ?

  • G06N 20/20 - Techniques d’ensemble en apprentissage automatique
  • G06V 10/82 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant les réseaux neuronaux
  • G06F 40/151 - Transformation
  • G06N 3/08 - Méthodes d'apprentissage
  • G06N 5/01 - Techniques de recherche dynamiqueHeuristiquesArbres dynamiquesSéparation et évaluation
  • G06V 30/19 - Reconnaissance utilisant des moyens électroniques
  • G06V 30/40 - Reconnaissance des formes à partir d’images axée sur les documents
  • G06V 30/10 - Reconnaissance de caractères

14.

MACHINE LEARNING-BASED TEXT RECOGNITION SYSTEM WITH FINE-TUNING MODEL

      
Numéro de document 03168231
Statut En instance
Date de dépôt 2021-01-15
Date de disponibilité au public 2022-07-22
Propriétaire HYPER LABS, INC. (USA)
Inventeur(s)
  • Stefanov, Stefan
  • Daskalov, Boris
  • Lohchab, Akhil

Abrégé

A non-transitory processor-readable medium stores instructions to be executed by a processor. The instructions cause the processor to receive a first trained machine learning model that generates a transcription based on a document. The instructions cause the processor to execute the first trained machine learning model and a second trained machine learning model to generate a refined transcription based on the transcription. The instructions cause the processor to execute a quality assurance program to generate a transcription score based on the document and the transcription. The instructions cause the processor to execute the quality assurance program to generate a refined transcription score based on the refined transcription and at least one of the document or the transcription. The at least one refined transcription score indicates an automation performance better than an automation performance for the at least one transcription score.

Classes IPC  ?

  • G06N 20/00 - Apprentissage automatique
  • G06V 30/10 - Reconnaissance de caractères
  • G06V 30/40 - Reconnaissance des formes à partir d’images axée sur les documents

15.

Machine learning-based text recognition system with fine-tuning model

      
Numéro d'application 16744550
Numéro de brevet 11481691
Statut Délivré - en vigueur
Date de dépôt 2020-01-16
Date de la première publication 2021-07-22
Date d'octroi 2022-10-25
Propriétaire Hyper Labs, Inc. (USA)
Inventeur(s)
  • Stefanov, Stefan Iliev
  • Daskalov, Boris Nikolaev
  • Lohchab, Akhil

Abrégé

A non-transitory processor-readable medium stores instructions to be executed by a processor. The instructions cause the processor to receive a first trained machine learning model that generates a transcription based on a document. The instructions cause the processor to execute the first trained machine learning model and a second trained machine learning model to generate a refined transcription based on the transcription. The instructions cause the processor to execute a quality assurance program to generate a transcription score based on the document and the transcription. The instructions cause the processor to execute the quality assurance program to generate a refined transcription score based on the refined transcription and at least one of the document or the transcription. The at least one refined transcription score indicates an automation performance better than an automation performance for the at least one transcription score.

Classes IPC  ?

  • G06N 20/20 - Techniques d’ensemble en apprentissage automatique
  • G06F 40/151 - Transformation
  • G06N 3/08 - Méthodes d'apprentissage
  • G06N 5/00 - Agencements informatiques utilisant des modèles fondés sur la connaissance
  • G06V 30/40 - Reconnaissance des formes à partir d’images axée sur les documents

16.

MACHINE LEARNING-BASED TEXT RECOGNITION SYSTEM WITH FINE-TUNING MODEL

      
Numéro d'application US2021013580
Numéro de publication 2021/146524
Statut Délivré - en vigueur
Date de dépôt 2021-01-15
Date de publication 2021-07-22
Propriétaire HYPER LABS, INC. (USA)
Inventeur(s)
  • Stefanov, Stefan
  • Daskalov, Boris
  • Lohchab, Akhil

Abrégé

A non-transitory processor-readable medium stores instructions to be executed by a processor. The instructions cause the processor to receive a first trained machine learning model that generates a transcription based on a document. The instructions cause the processor to execute the first trained machine learning model and a second trained machine learning model to generate a refined transcription based on the transcription. The instructions cause the processor to execute a quality assurance program to generate a transcription score based on the document and the transcription. The instructions cause the processor to execute the quality assurance program to generate a refined transcription score based on the refined transcription and at least one of the document or the transcription. The at least one refined transcription score indicates an automation performance better than an automation performance for the at least one transcription score.

Classes IPC  ?

  • G06K 9/62 - Méthodes ou dispositions pour la reconnaissance utilisant des moyens électroniques

17.

Apparatuses, methods, and systems for 3-channel dynamic contextual script recognition using neural network image analytics and 4-tuple machine learning with enhanced templates and context data

      
Numéro d'application 16674324
Numéro de brevet 10671892
Statut Délivré - en vigueur
Date de dépôt 2019-11-05
Date de la première publication 2020-06-02
Date d'octroi 2020-06-02
Propriétaire Hyper Labs, Inc. (USA)
Inventeur(s)
  • Daskalov, Boris Nikolaev
  • Balchev, Daniel Biser

Abrégé

In some embodiments, a method includes training a first machine learning model based on multiple documents and multiple templates associated with the multiple documents. The method further includes executing the first machine learning model to generate multiple relevancy masks, the multiple relevancy masks to remove a visual structure of the multiple templates from a visual structure of the multiple documents. The method further includes generating multiple multichannel field images to include the multiple relevancy masks and at least one of the multiple documents or the multiple templates. The method further includes training a second machine learning model based on the multiple multichannel field images and multiple non-native texts associated with the multiple documents. The method further includes executing the second machine learning model to generate multiple non-native texts from the multiple multichannel field images.

Classes IPC  ?

  • G06K 9/62 - Méthodes ou dispositions pour la reconnaissance utilisant des moyens électroniques
  • G06N 3/04 - Architecture, p. ex. topologie d'interconnexion
  • G06K 9/46 - Extraction d'éléments ou de caractéristiques de l'image
  • G06N 3/08 - Méthodes d'apprentissage

18.

(h[s])

      
Numéro d'application 1518689
Statut Enregistrée
Date de dépôt 2020-01-15
Date d'enregistrement 2020-01-15
Propriétaire Hyper Labs Inc. (USA)
Classes de Nice  ? 09 - Appareils et instruments scientifiques et électriques

Produits et services

Automated systems, namely, downloadable software for automating office, business and administrative processes and procedures; software featuring natural language processing, image recognition and machine learning functionality.

19.

(H[S])

      
Numéro d'application 201565300
Statut Enregistrée
Date de dépôt 2020-01-15
Date d'enregistrement 2022-06-01
Propriétaire Hyper Labs Inc. (USA)
Classes de Nice  ? 09 - Appareils et instruments scientifiques et électriques

Produits et services

(1) Automated systems, namely downloadable software for automating office, business and administrative processes and procedures, namely for automating document management, document, text, and image processing and extraction, data management and processing, data entry of accounts receivable and account collections and for providing related accounting, word processing and integrated email support, for searching and retrieving information across a computer network, for the analysis of business data and information, for optical character recognition, for converting document images into electronic format, for automating data extraction, collation of data and classification of data from documents, for processing logic and data validation, and for improving automation through database lookups; software featuring natural language processing, image recognition and machine learning functionality for automating document management, document, text, and image processing and extraction, data management and processing, data entry of accounts receivable and account collections and for providing related accounting, word processing and integrated email support, for searching and retrieving information across a computer network, for the analysis of business data and information, for converting natural language into machine executable commands, for evaluating customer behaviour in online shops, for optical character recognition, for converting document images into electronic format, for automating data extraction, collation of data and classification of data from documents, for processing logic and data validation, and for improving automation through database lookups

20.

HS

      
Numéro de série 88514140
Statut Enregistrée
Date de dépôt 2019-07-15
Date d'enregistrement 2020-01-28
Propriétaire Hyper Labs Inc., DBA HyperScience ()
Classes de Nice  ? 09 - Appareils et instruments scientifiques et électriques

Produits et services

Automated systems, namely, downloadable software for automating office, business and administrative processes and procedures; software featuring natural language processing, image recognition and machine learning functionality

21.

HYPERSCIENCE

      
Numéro d'application 1437907
Statut Enregistrée
Date de dépôt 2018-10-30
Date d'enregistrement 2018-10-30
Propriétaire Hyper Labs Inc. (USA)
Classes de Nice  ? 09 - Appareils et instruments scientifiques et électriques

Produits et services

Automated systems, namely, downloadable software and hardware for automating office, business and administrative processes and procedures; software featuring natural language processing, image recognition and machine learning functionality.

22.

HYPERSCIENCE

      
Numéro d'application 192809400
Statut Enregistrée
Date de dépôt 2018-10-31
Date d'enregistrement 2023-02-07
Propriétaire Hyper Labs Inc. (USA)
Classes de Nice  ? 09 - Appareils et instruments scientifiques et électriques

Produits et services

(1) Automated systems, namely downloadable software for automating office, business and administrative processes and procedures, namely for automating document management, document, text, and image processing and extraction, data management and processing, data entry of accounts receivable and account collections and for providing related accounting, word processing and integrated email support, for searching and retrieving information across a computer network, for the analysis of business data and information, for optical character recognition, for converting document images into electronic format, for automating data extraction, collation of data and classification of data from documents, for processing logic and data validation, and for improving automation through database lookups; software featuring natural language processing, image recognition and machine learning functionality for automating document management, document, text, and image processing and extraction, data management and processing, data entry of accounts receivable and account collections and for providing related accounting, word processing and integrated email support, for searching and retrieving information across a computer network, for the analysis of business data and information, for converting natural language into machine executable commands, for evaluating customer behaviour in online shops, for optical character recognition, for converting document images into electronic format, for automating data extraction, collation of data and classification of data from documents, for processing logic and data validation, and for improving automation through database lookups

23.

HYPERSCIENCE

      
Numéro de série 87937258
Statut Enregistrée
Date de dépôt 2018-05-25
Date d'enregistrement 2019-07-23
Propriétaire Hyper Labs Inc., DBA HyperScience ()
Classes de Nice  ? 09 - Appareils et instruments scientifiques et électriques

Produits et services

Automated systems, namely, downloadable software for automating office, business and administrative processes and procedures; software featuring natural language processing, image recognition and machine learning functionality