|
|
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
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23.
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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 ()
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| Classes de Nice ? |
09 - Appareils et instruments scientifiques et électriques
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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
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