Category: Patents

U.S. Patent Number: 12,699,741
Patent Title: Location-aware query transformation using weighted temporal models to derive user and region context
Issue Date: August 4, 2026
Inventors: Ghafourifar, et al.
Assignee: Entefy Inc.

Patent Abstract

A system and method for transforming location-based data queries into temporal domain by leveraging a location-to-time knowledge conversion graph. In some systems which contain diverse sets of data objects, only certain objects may contain explicit location data, while others may not. Therefore, queriability of this diverse data by location properties would likely yield incomplete results. In some embodiments, this method allows for the transformation and augmentation of a given data query containing location-based filtering properties into a time-region-based lookup, wherein a given location has been assigned to a time region in the given data graph and all data events within that time region may be augmented with location metadata automatically in the knowledge graph. Over time, a system utilizing these embodiments can offer comprehensive location-based data services and insights with a diverse set of data objects that exists and not all objects contain explicit location information.

USPTO Technical Field

This disclosure relates generally to converting a location-based query to a time-based query.

Background

Many data items are generated with location information embedded as metadata. For example, an image file may include global positioning system (GPS) data indicating where the image file was created. Location data associated with data items may be used for a variety of purposes. For example, an individual may query a system that tracks data items to determine which data items the individual generated while on a trip to Europe. However, some data items may not be associated with location data. Such data items may not be considered by systems and applications that operate on such data based on location, therein reducing the scope or efficacy of location-based queries with regard to retrieval of diverse data in a given system.

Read the full patent here.

ABOUT ENTEFY

Entefy is an enterprise AI software company. Entefy’s patented, multisensory AI technology delivers on the promise of the intelligent enterprise, at unprecedented speed and scale.

Entefy products and services help organizations transform their legacy systems and business processes—everything from knowledge management to workflows, supply chain logistics, cybersecurity, data privacy, customer engagement, quality assurance, forecasting, and more. Entefy’s customers vary in size from SMEs to large global public companies across multiple industries including financial services, healthcare, retail, and manufacturing.

To leap ahead and future proof your business with Entefy’s breakthrough AI technologies, visit www.entefy.com  or contact us at contact@entefy.com.

U.S. Patent Number: 10,135,764
Patent Title: Universal interaction platform for people, services, and devices
Issue Date: November 20, 2018
Inventors: Ghafourifar, et al.
Assignee: Entefy Inc.

Patent Abstract

A universal interaction platform that communicates with service providers and smart devices by receiving a message object that includes information indicative of a user intent for one of the service providers or smart devices to perform a function, determines the service provider or smart device that the user intends to perform the function, determines a protocol and format for communicating with the service provider or smart device, formats an instruction for the service provider or smart device, and outputs the instruction to the service provider or smart device.

USPTO Technical Field

This disclosure relates generally to apparatuses, methods, and computer readable media for interacting with people, services, and devices across multiple communications formats and protocols.

Background

A growing number of service providers allow users to request information or services from those service providers via a third party software applications. Additionally, a growing number of smart devices allow users to obtain information from and control those smart devices via a third party software application. Meanwhile, individuals communicate with each other using a variety of protocols such as email, text, social messaging, etc. In an increasingly chaotic digital world, it’s becoming increasingly difficult for users to manage their digital interactions with service providers, smart devices, and individuals. A user may have separate software applications for requesting services from a number of service providers, for controlling a number of smart devices, and for communicating with individuals. Each of these separate software applications may have different user interfaces and barriers to entry.

The subject matter of the present disclosure is directed to overcoming, or at least reducing the effects of, one or more of the problems set forth above. To address these and other issues, techniques that enable seamless, multi-format, multi-protocol communications are described herein.

Read the full patent here.

ABOUT ENTEFY

Entefy is an enterprise AI software company. Entefy’s patented, multisensory AI technology delivers on the promise of the intelligent enterprise, at unprecedented speed and scale.

Entefy products and services help organizations transform their legacy systems and business processes—everything from knowledge management to workflows, supply chain logistics, cybersecurity, data privacy, customer engagement, quality assurance, forecasting, and more. Entefy’s customers vary in size from SMEs to large global public companies across multiple industries including financial services, healthcare, retail, and manufacturing.

To leap ahead and future proof your business with Entefy’s breakthrough AI technologies, visit www.entefy.com  or contact us at contact@entefy.com.

U.S. Patent Number: 12,412,173
Patent Title: System and method for enabling autonomous artificial intelligence-enabled skills exchanges between agents over a network
Issue Date: September 9, 2025
Inventors: Ghafourifar, et al.
Assignee: Entefy Inc.

Patent Abstract

An improved decentralized, blockchain-driven network for artificial intelligence (AI)-enabled skills exchange between Intelligent Personal Assistants (IPAs) in a network is disclosed that is configured to perform computational tasks or services (also referred to herein as “skills”) in an optimally-efficient fashion. In some embodiments, this may comprise a first IPA paying an agreed cost to a second IPA to perform a particular skill in a more optimally-efficient fashion. In some embodiments, a skills registry is published, comprising benchmark analyses and costs for the skills offered by the various nodes on the skills exchange network. In other embodiments, a transaction ledger is maintained that provides a record of all transactions performed across the network in a tamper-proof and auditable fashion, e.g., via the use of blockchain technology. Over time, the AI-enabled nodes in the system may learn to scale, replicate, and transact with each other in an optimized—and fully autonomous—fashion.

USPTO Technical Field

This disclosure relates generally to apparatuses, methods, and computer readable media for a decentralized, secure network for artificial intelligence (AI)-enabled performance and exchange of computational tasks and services between network nodes.

Background

Intelligent personal assistant (IPA) software systems comprise software agents that can perform various functions, e.g., computational tasks or services, on behalf of an individual user or users. IPAs, as used herein, may simply be thought of as computational “containers” for certain functionalities. The functionalities that are able to be performed by a given IPA at a particular moment in time may be based on a number of factors, including: a user’s geolocation, a user’s preferences, an ability to access information from a variety of online sources, the processing power and/or current performance load of a physical instance that the IPA is currently being executed on, and the historical training/modification/customization that has been performed on the IPA. As such, current IPA software systems have fundamental limitations in terms of their capabilities and abilities to perform certain computational tasks.

For example, in some instances, a first IPA executing on a first device on a network may be able to perform a particular first computational task or service (also referred to herein as a “skill”) with a very high degree of accuracy, but may be executing on a physical instance that lacks the necessary computational power or capacity to perform the particular first computational task or service in a reasonable amount of time. Likewise, a second IPA, e.g., being executed on a device belonging to another user on the same network, may have excellent computational power and capacity, but not have been trained to perform the first computational task or service with a high degree of accuracy. As such, the particular first computational task or service is not likely to be able to be efficiently performed by either the first IPA or the second IPA, causing, in effect, an inevitable marketplace inefficiency in the overall skills network.

Such a scenario may not provide for a satisfactory (or efficient) user experience across the many users and/or nodes of the network. In the context of AI-enabled IPAs, the IPAs may be able to “learn” and improve their performance of certain computational tasks or services over time. AI-enabled IPAs may also be able to determine, over time, more efficient usages of the network’s overall computational capacity to perform computational tasks or services at a high level of performance and at a low operational cost, e.g., by ‘farming out’ certain computational tasks to other IPAs and/or nodes in the network that can perform the task in a more optimal manner.

However, in order to be able to act, react, and interoperate in an efficient manner, the various IPAs distributed across a network must have accurate information as to the current status of the various skills that the nodes on the network are able to perform (e.g., in terms of benchmarking scores, availability, and/or costs)—as well as the ability to determine the most optimal nodes that could be used to perform such skills, given computational and cost constraints.

Moreover, in order to reliably provide “value,” i.e., payment for services rendered, to other nodes in the aforementioned network for the performance of skills in an optimized manner, it is important that a secure ledger of transactions performed across the network be maintained in a tamper-proof and auditable fashion.

The subject matter of the present disclosure is directed to overcoming, or at least reducing the effects of, one or more of the problems set forth above. To address these and other issues, techniques that enable a decentralized, secure network for the AI-enabled performance and exchange of computational tasks and services between nodes on a network are described herein.

Read the full patent here.

ABOUT ENTEFY

Entefy is an enterprise AI software company. Entefy’s patented, multisensory AI technology delivers on the promise of the intelligent enterprise, at unprecedented speed and scale.

Entefy products and services help organizations transform their legacy systems and business processes—everything from knowledge management to workflows, supply chain logistics, cybersecurity, data privacy, customer engagement, quality assurance, forecasting, and more. Entefy’s customers vary in size from SMEs to large global public companies across multiple industries including financial services, healthcare, retail, and manufacturing.

To leap ahead and future proof your business with Entefy’s breakthrough AI technologies, visit www.entefy.com  or contact us at contact@entefy.com.

U.S. Patent Number: 11,366,839
Patent Title: System and method of dynamic, encrypted searching with model driven contextual correlation
Issue Date: June 21, 2022
Inventors: Ghafourifar, et al.
Assignee: Entefy Inc.

Patent Abstract

This disclosure relates to personalized and dynamic server-side searching techniques for encrypted data. Current so-called ‘zero-knowledge’ privacy systems (i.e., systems where the server has ‘zero-knowledge’ about the client data that it is storing) utilize servers that hold encrypted data without the decryption keys necessary to decrypt, index, and/or re-encrypt the data. As such, the servers are not able to perform any kind of meaningful server-side search process, as it would require access to the underlying decrypted data. Therefore, such prior art ‘zero-knowledge’ privacy systems provide a limited ability for a user to search through a large dataset of encrypted documents to find critical information. Disclosed herein are communications systems that offer the increased security and privacy of client-side encryption to content owners, while still providing for highly relevant server-side search-based results via the use of content correlation, predictive analysis, and augmented semantic tag clouds for the indexing of encrypted data.

USPTO Technical Field

This disclosure relates generally to systems, methods, and computer readable media for performing highly relevant, dynamic, server-side searching on encrypted data that the server does not have the ability to decrypt.

Background

The proliferation of personal computing devices in recent years, especially mobile personal computing devices, combined with a growth in the number of widely-used communications formats (e.g., text, voice, video, image) and protocols (e.g., SMTP, IMAP/POP, SMS/MMS, XMPP, etc.) has led to a communications experience that many users find fragmented and difficult to search for relevant information in. Users desire a system that will provide for ease of message threading by “stitching” together related communications and documents across multiple formats and protocols—all seamlessly from the user’s perspective. Such stitching together of communications and documents across multiple formats and protocols may occur, e.g., by: 1) direct user action in a centralized communications application (e.g., by a user clicking ‘Reply’ on a particular message); 2) using semantic matching (or other search-style message association techniques); 3) element-matching (e.g., matching on subject lines or senders/recipients/similar quoted text, etc.); and/or 4) “state-matching” (e.g., associating messages if they are specifically tagged as being related to another message, sender, etc. by a third-party service, e.g., a webmail provider or Instant Messaging (IM) service). These techniques may be employed in order to provide a more relevant “search-based threading” experience for users.

With current communications technologies, conversations remain “siloed” within particular communication formats or protocols, leading to users being unable to search uniformly across multiple communications in multiple formats or protocols and across multiple applications and across multiple other computing devices from their computing devices to find relevant communications (or even communications that a messaging system may predict to be relevant), often resulting in inefficient communication workflows—and even lost business or personal opportunities. For example, a conversation between two people may begin over text messages (e.g., SMS) and then transition to email. When such a transition happens, the entire conversation can no longer be tracked, reviewed, searched, or archived by a single source since it had ‘crossed over’ protocols. For example, if the user ran a search on their email search system for a particular topic that had come up only in the user’s SMS conversations, even when pertaining to the same subject manner and “conversation,” such a search may not turn up optimally relevant results.

Users also desire a communications system with increased security and privacy with respect to their communications and documents, for example, systems wherein highly relevant search-based results may still be provided to the user by the system—even without the system actually having the ability to decrypt and/or otherwise have access to the underlying content of the user’s encrypted communications and documents. However, current so-called ‘zero-knowledge’ privacy systems (i.e., systems where the server has ‘zero-knowledge’ about the data that it is storing) utilize servers that hold encrypted data without the decryption keys necessary to decrypt, index, and/or re-encrypt the data. As such, this disallows any sort of meaningful server-side search process, which would require access to the underlying data (e.g., in order for the data to be indexed) to be performed, such that the encrypted data could be returned in viable query result sets. Therefore, such prior art ‘zero-knowledge’ systems provide a limited ability for a user to search through a large dataset of encrypted documents to find critical information.

It should be noted that attempts (both practical and theoretical) have been made to design proper ‘zero-knowledge’ databases and systems that can support complex query operations on fully encrypted data. Such approaches include, among others, homomorphic encryption techniques which have been used to support numerical calculations and other simple aggregations, as well as somewhat accurate retrieval of private information. However, no solution currently known to the inventors enables a system or database to perform complex operations on fully-encrypted data, such as index creation for the purpose of advanced search queries. Thus, the systems and methods disclosed herein aim to provide a user with the ability to leverage truly private, advanced server-side search capabilities from any connected client interface without relying on a ‘trusted’ server authority to authenticate identity or store the necessary key(s) to decrypt the content at any time.

Read the full patent here.

ABOUT ENTEFY

Entefy is an enterprise AI software company. Entefy’s patented, multisensory AI technology delivers on the promise of the intelligent enterprise, at unprecedented speed and scale.

Entefy products and services help organizations transform their legacy systems and business processes—everything from knowledge management to workflows, supply chain logistics, cybersecurity, data privacy, customer engagement, quality assurance, forecasting, and more. Entefy’s customers vary in size from SMEs to large global public companies across multiple industries including financial services, healthcare, retail, and manufacturing.

To leap ahead and future proof your business with Entefy’s breakthrough AI technologies, visit www.entefy.com  or contact us at contact@entefy.com.

U.S. Patent Number: 10,761,910
Patent Title: Application program interface analyzer for a universal interaction platform
Issue Date: September 01, 2020
Inventors: Ghafourifar, et al.
Assignee: Entefy Inc.

Patent Abstract

An application program interface (API) analyzer that determines protocols and formats to interact with a service provider or smart device. The API analyzer identifies an API endpoint or websites for the service provider or smart device, determines a service category or device category, selects a category-specific corpus, forms a service-specific or device-specific corpus by appending information regarding the service provider or smart device to the category-specific corpus, and parses API documentation or the websites.

USPTO Technical Field

This disclosure relates generally to apparatuses, methods, and computer readable media for interacting with people, services, and devices across multiple communications formats and protocols.

Background

A growing number of service providers allow users to request information or services from those service providers via a third party software applications. Additionally, a growing number of smart devices allow users to obtain information from and control those smart devices via a third party software application. Meanwhile, individuals communicate with each other using a variety of protocols such as email, text, social messaging, etc. In an increasingly chaotic digital world, it’s becoming increasingly difficult for users to manage their digital interactions with service providers, smart devices, and individuals. A user may have separate software applications for requesting services from a number of service providers, for controlling a number of smart devices, and for communicating with individuals. Each of these separate software applications may have different user interfaces and barriers to entry.

The subject matter of the present disclosure is directed to overcoming, or at least reducing the effects of, one or more of the problems set forth above. To address these and other issues, techniques that enable seamless, multi-format, multi-protocol communications are described herein.

Read the full patent here.

ABOUT ENTEFY

Entefy is an enterprise AI software company. Entefy’s patented, multisensory AI technology delivers on the promise of the intelligent enterprise, at unprecedented speed and scale.

Entefy products and services help organizations transform their legacy systems and business processes—everything from knowledge management to workflows, supply chain logistics, cybersecurity, data privacy, customer engagement, quality assurance, forecasting, and more. Entefy’s customers vary in size from SMEs to large global public companies across multiple industries including financial services, healthcare, retail, and manufacturing.

To leap ahead and future proof your business with Entefy’s breakthrough AI technologies, visit www.entefy.com  or contact us at contact@entefy.com.

U.S. Patent Number: 10,394,966
Patent Title: Systems and methods for multi-protocol, multi-format universal searching
Issue Date: August 27, 2019
Inventors: Ghafourifar, et al.
Assignee: Entefy Inc.

Patent Abstract

This disclosure relates to systems, methods, and computer readable media for performing multi-format, multi-protocol personalized searching in a manner that is most beneficial for the individual user. Personalized searching can be achieved by obtaining a plurality of data objects for a first user. The data objects can exist in a wide variety of formats and can be received via a number of protocols. One or more message objects can be created for each of the data objects, according to a standardized format and stored. The universal message objects can be indexed in a manner that is personal to the user, and in accordance with one or more parameters that can be updated on an ongoing or periodic basis, in accordance with the actions of the user, or any combination thereof.

USPTO Technical Field

This disclosure relates generally to systems, methods, and computer readable media for enhanced document and/or message searching across multiple communications formats and protocols.

Background

The proliferation of personal computing devices in recent years, especially mobile personal computing devices, combined with a growth in the number of widely-used communications formats (e.g., text, voice, video, image) and protocols (e.g., SMTP, IMAP/POP, SMS/MMS, MPP, etc.) has led to a communications experience that many users find fragmented and difficult to search for relevant information in. Users desire a system that will provide searching across different data object types, across multiple formats and protocols, with ease and accuracy.

With current communications and searching technologies, different types of messages and other different types of data objects tend to be “siloed” within particular formats or protocols, causing users to be unable to search uniformly across multiple communications and other data objects in multiple formats or protocols, across multiple applications and across multiple other computing devices from their computing devices to find relevant search results. This can be time consuming, inefficient and frustrating. For example, a user may have to search for emails in an email system, and search for a video file in a different location. Moreover, due to the passage of time, the user may be unaware that a topic searched with regard to one data object type (e.g., emails) might have yielded relevant results if a different type (e.g., image files) had been searched.

Furthermore, with searching technologies, searching methods tend to be uniform—“one size fits all”—regardless of the preferences and individual characteristics of the person who is doing the searching.

The subject matter of the present disclosure is directed to overcoming, or at least reducing the effects of, one or more of the problems set forth above. To address these and other issues, techniques that enable seamless, multi-format, multi-protocol storage, searching and retrieval are described herein.

Read the full patent here.

ABOUT ENTEFY

Entefy is an enterprise AI software company. Entefy’s patented, multisensory AI technology delivers on the promise of the intelligent enterprise, at unprecedented speed and scale.

Entefy products and services help organizations transform their legacy systems and business processes—everything from knowledge management to workflows, supply chain logistics, cybersecurity, data privacy, customer engagement, quality assurance, forecasting, and more. Entefy’s customers vary in size from SMEs to large global public companies across multiple industries including financial services, healthcare, retail, and manufacturing.

To leap ahead and future proof your business with Entefy’s breakthrough AI technologies, visit www.entefy.com  or contact us at contact@entefy.com.

U.S. Patent Number: 11,366,838
Patent Title: System and method of context-based predictive content tagging for encrypted data
Issue Date: June 21, 2022
Inventors: Ghafourifar, et al.
Assignee: Entefy Inc.

Patent Abstract

This disclosure relates to systems, methods, and computer readable media for performing multi-format, multi-protocol message threading in a way that is most beneficial for the individual user. Users desire a system that will provide for ease of message threading by “stitching” together related communications in a manner that is seamless from the user’s perspective. Such stitching together of communications across multiple formats and protocols may occur, e.g., by: 1) direct user action in a centralized communications application (e.g., by a user clicking ‘Reply’ on a particular message); 2) using semantic matching (or other search-style message association techniques); 3) element-matching (e.g., matching on subject lines or senders/recipients/similar quoted text, etc.); and 4) “state-matching” (e.g., associating messages if they are specifically tagged as being related to another message, sender, etc. by a third-party service, e.g., a webmail provider or Instant Messaging (IM) service).

USPTO Technical Field

This disclosure relates generally to systems, methods, and computer readable media for message threading across multiple communications formats and protocols.

Background

The proliferation of personal computing devices in recent years, especially mobile personal computing devices, combined with a growth in the number of widely-used communications formats (e.g., text, voice, video, image) and protocols (e.g., SMTP, IMAP/POP, SMS/MMS, XMPP, YMSG, etc.) has led to a communications experience that many users find fragmented and difficult to search for relevant information in. Users desire a system that will provide for ease of message threading by “stitching” together related communications across multiple formats and protocols—all seamlessly from the user’s perspective. Such stitching together of communications across multiple formats and protocols may occur, e.g., by: 1) direct user action in a centralized communications application (e.g., by a user clicking ‘Reply’ on a particular message); 2) using semantic matching (or other search-style message association techniques); 3) element-matching (e.g., matching on subject lines or senders/recipients/similar quoted text, etc.); and 4) “state-matching” (e.g., associating messages if they are specifically tagged as being related to another message, sender, etc. by a third-party service, e.g., a webmail provider or Instant Messaging (IM) service.

With current communications technologies, conversations remain “siloed” within particular communication formats or protocols, leading to users being unable to search across multiple communications in multiple formats or protocols and across multiple applications on their computing devices to find relevant communications (or even communications that a messaging system may predict to be relevant), often resulting in inefficient communication workflows—and even lost business or personal opportunities. For example, a conversation between two people may begin over text messages (e.g., SMS) and then transition to email. When such a transition happens, the entire conversation can no longer be tracked, reviewed, searched, or archived by a single source since it had ‘crossed over’ protocols. For example, if the user ran a search on their email search system for a particular topic that had come up only in the user’s SMS conversations, such a search may not turn up optimally relevant results.

Further, a multi-format, multi-protocol, communication threading system, such as is disclosed herein, may also provide for the semantic analysis of conversations. For example, for a given set of communications between two users, there may be only a dozen or so keywords that are relevant and related to the subject matter of the communications. These dozen or so keywords may be used to generate an “initial tag cloud” to associate with the communication(s) being indexed. The initial tag cloud can be created based on multiple factors, such as the uniqueness of the word, the number of times a word is repeated, phrase detection, etc. These initial tag clouds may then themselves be used to generate further an expanded “predictive tag cloud,” based on the use of Markov chains or other predictive analytics based on established language theory techniques and data derived from existing communications data in a centralized communications server. These initial tag clouds and predictive tag clouds may be used to improve message indexing and provide enhanced relevancy in search results. In doing so, the centralized communications server may establish connections between individual messages that were sent/received using one or multiple communication formats or protocols and that may contain information relevant to the user’s initial search query.

The subject matter of the present disclosure is directed to overcoming, or at least reducing the effects of, one or more of the problems set forth above. To address these and other issues, techniques that enable seamless, multi-format, multi-protocol communication threading are described herein.

Read the full patent here.

ABOUT ENTEFY

Entefy is an enterprise AI software company. Entefy’s patented, multisensory AI technology delivers on the promise of the intelligent enterprise, at unprecedented speed and scale.

Entefy products and services help organizations transform their legacy systems and business processes—everything from knowledge management to workflows, supply chain logistics, cybersecurity, data privacy, customer engagement, quality assurance, forecasting, and more. Entefy’s customers vary in size from SMEs to large global public companies across multiple industries including financial services, healthcare, retail, and manufacturing.

To leap ahead and future proof your business with Entefy’s breakthrough AI technologies, visit www.entefy.com  or contact us at contact@entefy.com.

U.S. Patent Number: 10,587,585
Patent Title: System and method of presenting dynamically-rendered content in structured documents
Issue Date: March 10, 2020
Inventors: Alston Ghafourifar
Assignee: Entefy Inc.

Patent Abstract

Users desire a system that provides for the setting of custom, content-agnostic, permissions at a message, document, and/or sub-document-level through a communications network. Such a system may also allow the user to apply customized privacy settings and encryption keys differently to particular parts of a document. Customized encryption keys may be applied to particular parties (or groups of parties) to enhance the security of the permissions settings. In the case of structured document file types, dynamically-rendered content can present a challenge to accurately display to viewers, because one or more of the document’s values referred to by the dynamically-rendered content may be encrypted or otherwise unavailable to the recipient—even though the dynamically-rendered content itself is viewable by the recipient. Systems are presented herein to handle the presentation of dynamically-rendered content in structured documents, while preserving the sender’s intent to not disclose certain underlying or related information in the document.

USPTO Technical Field

This disclosure relates generally to systems, methods, and computer readable media for determining user-defined, content-agnostic document and message permissions through a network, and especially for structured documents (e.g., documents that may be represented using a markup language), which may contain both dynamically-rendered content and statically-rendered content.

Background

The proliferation of personal computing devices in recent years, especially mobile personal computing devices, combined with a growth in the number of widely-used communications formats (e.g., text, voice, video, image) and protocols (e.g., SMTP, IMAP/POP, SMS/MMS, XMPP, YMSG, etc.) has led to increased concerns regarding the safety and security of documents and messages that are sent over networks. Users desire a system that provides for the setting of custom, e.g., user-defined, content-agnostic permissions at a message-, document-, and/or sub-document—(i.e., a part of the document that comprises less than the entire document) level through a communications network. Such a system would allow customized privacy settings to be specified at various levels of social distance from the user sending the document or message (e.g., public, private, followers, groups, Level-1 contacts, Level-2 contacts, Level-3 contacts, etc.). Such a system may also allow the user to apply customized privacy settings and encryption keys differently to particular parts of a document, e.g., making a first part of a document available only to a first class of users and other parts of the document available to the first class of users and a second class of users.

Thus, a system for providing Adaptive Privacy Controls (APC) is described herein. APC comprises a user-controllable or system-generated, intelligent privacy system that can limit viewing, editing, and re-sharing privileges for files and other digital objects of all types stored in a compatible system (e.g., message objects, user profile fields, documents, etc.). APC allows users to share whatever information they want with whomever they want, while keeping others from accessing such information via assorted rights management techniques and/or encryption processes that can be initiated by user command or via system intelligence on entire objects or portions of objects. APC techniques may be applied to individuals, pre-defined groups, and/or ad-hoc groups. Customized encryption keys may further be applied to particular parties or groups of parties to enhance the security of the permissions settings.

APC may also be used to apply privacy settings to only particular parts of a document. For example, User A in an organization may need to see the entire content of the organization’s annual report drafts, but other users in the organization may only need to see a version that has sensitive financial/pro-forma data redacted. For example, pages 1-20 of the annual report would be available to User A, but only pages 1-19 would be available to the other users.

Thus, according to some embodiments, the network-based, user-defined, content-agnostic (i.e., agnostic as to both format and subject matter) document and message permissions systems, methods, and computer readable media described herein may provide a seamless, intuitive user interface (e.g., using touch gestures or mouse input) allowing a user to block out particular areas of interest in a document or message from particular recipients or groups of recipients, as well as to specify privacy and permissions settings for a single document or message—or across all documents owned by the user.

The protections offered by APC techniques may, however, be complicated when applied to structured document file formats and/or file types that may, e.g., be represented by a markup language. In the case of spreadsheet documents or other Extensible Markup Language (XML)-based file types, dynamically calculated content can present a challenge to accurately display to unauthorized or ‘out-of-system’ viewers, because APC’s encryption of document content at the individual cell- or value-level can create corrupted regions within formulas, charts, features, or other dynamically-rendered content that relies on or refers to the encrypted content’s value(s) in order to be rendered correctly. For example, if APC protection techniques are applied to one or multiple spreadsheet cells that are referenced in a formula of a second spreadsheet cell, the second cell’s formula output will likely contain a Reference Error when viewed by an unauthorized or ‘out-of-system’ viewer and thus appear invalid—even if the sender had actually intended the recipient to be able to see the value of the second cell (i.e., the value of the second cell at least as of the time the sender sent the document to the recipient).

The subject matter of the present disclosure is directed to overcoming, or at least reducing the effects of, one or more of the problems set forth above. To address these and other issues, techniques that enable the setting of user-defined, content-agnostic permissions at a message-, document-, and/or sub-document-level through a communications network—including for structured document file types that may contain both dynamically-rendered content and statically-rendered content—are described herein.

Read the full patent here.

ABOUT ENTEFY

Entefy is an enterprise AI software company. Entefy’s patented, multisensory AI technology delivers on the promise of the intelligent enterprise, at unprecedented speed and scale.

Entefy products and services help organizations transform their legacy systems and business processes—everything from knowledge management to workflows, supply chain logistics, cybersecurity, data privacy, customer engagement, quality assurance, forecasting, and more. Entefy’s customers vary in size from SMEs to large global public companies across multiple industries including financial services, healthcare, retail, and manufacturing.

To leap ahead and future proof your business with Entefy’s breakthrough AI technologies, visit www.entefy.com  or contact us at contact@entefy.com.

U.S. Patent Number: 10,606,871
Patent Title: System and method of message threading for a multi-format, multi-protocol communication system
Issue Date: March 31, 2020
Inventors: Ghafourifar, et al.
Assignee: Entefy Inc.

Patent Abstract

This disclosure relates to systems, methods, and computer readable media for performing multi-format, multi-protocol message threading in a way that is most beneficial for the individual user. Users desire a system that will provide for ease of message threading by “stitching” together related communications in a manner that is seamless from the user’s perspective. Such stitching together of communications across multiple formats and protocols may occur, e.g., by: 1) direct user action in a centralized communications application (e.g., by a user clicking ‘Reply’ on a particular message); 2) using semantic matching (or other search-style message association techniques); 3) element-matching (e.g., matching on subject lines or senders/recipients/similar quoted text, etc.); and 4) “state-matching” (e.g., associating messages if they are specifically tagged as being related to another message, sender, etc. by a third-party service, e.g., a webmail provider or Instant Messaging (IM) service).

USPTO Technical Field

This disclosure relates generally to systems, methods, and computer readable media for message threading across multiple communications formats and protocols.

Background

The proliferation of personal computing devices in recent years, especially mobile personal computing devices, combined with a growth in the number of widely-used communications formats (e.g., text, voice, video, image) and protocols (e.g., SMTP, IMAP/POP, SMS/MMS, XMPP, YMSG, etc.) has led to a communications experience that many users find fragmented and difficult to search for relevant information in. Users desire a system that will provide for ease of message threading by “stitching” together related communications across multiple formats and protocols—all seamlessly from the user’s perspective. Such stitching together of communications across multiple formats and protocols may occur, e.g., by: 1) direct user action in a centralized communications application (e.g., by a user clicking ‘Reply’ on a particular message); 2) using semantic matching (or other search-style message association techniques); 3) element-matching (e.g., matching on subject lines or senders/recipients/similar quoted text, etc.); and 4) “state-matching” (e.g., associating messages if they are specifically tagged as being related to another message, sender, etc. by a third-party service, e.g., a webmail provider or Instant Messaging (IM) service.

With current communications technologies, conversations remain “siloed” within particular communication formats or protocols, leading to users being unable to search across multiple communications in multiple formats or protocols and across multiple applications on their computing devices to find relevant communications (or even communications that a messaging system may predict to be relevant), often resulting in inefficient communication workflows—and even lost business or personal opportunities. For example, a conversation between two people may begin over text messages (e.g., SMS) and then transition to email. When such a transition happens, the entire conversation can no longer be tracked, reviewed, searched, or archived by a single source since it had ‘crossed over’ protocols. For example, if the user ran a search on their email search system for a particular topic that had come up only in the user’s SMS conversations, such a search may not turn up optimally relevant results.

Further, a multi-format, multi-protocol, communication threading system, such as is disclosed herein, may also provide for the semantic analysis of conversations. For example, for a given set of communications between two users, there may be only a dozen or so keywords that are relevant and related to the subject matter of the communications. These dozen or so keywords may be used to generate an “initial tag cloud” to associate with the communication(s) being indexed. The initial tag cloud can be created based on multiple factors, such as the uniqueness of the word, the number of times a word is repeated, phrase detection, etc. These initial tag clouds may then themselves be used to generate further an expanded “predictive tag cloud,” based on the use of Markov chains or other predictive analytics based on established language theory techniques and data derived from existing communications data in a centralized communications server. These initial tag clouds and predictive tag clouds may be used to improve message indexing and provide enhanced relevancy in search results. In doing so, the centralized communications server may establish connections between individual messages that were sent/received using one or multiple communication formats or protocols and that may contain information relevant to the user’s initial search query.

The subject matter of the present disclosure is directed to overcoming, or at least reducing the effects of, one or more of the problems set forth above. To address these and other issues, techniques that enable seamless, multi-format, multi-protocol communication threading are described herein.

Read the full patent here.

ABOUT ENTEFY

Entefy is an enterprise AI software company. Entefy’s patented, multisensory AI technology delivers on the promise of the intelligent enterprise, at unprecedented speed and scale.

Entefy products and services help organizations transform their legacy systems and business processes—everything from knowledge management to workflows, supply chain logistics, cybersecurity, data privacy, customer engagement, quality assurance, forecasting, and more. Entefy’s customers vary in size from SMEs to large global public companies across multiple industries including financial services, healthcare, retail, and manufacturing.

To leap ahead and future proof your business with Entefy’s breakthrough AI technologies, visit www.entefy.com  or contact us at contact@entefy.com.

U.S. Patent Number: 10,410,000
Patent Title: System and method of applying adaptive privacy control regions to bitstream data
Issue Date: September 10, 2019
Inventors: Ghafourifar, et al.
Assignee: Entefy Inc.

Patent Abstract

Disclosed are systems to apply customized permission settings to protect particular portions of a document, and, in particular, documents that are of bitstream datatypes, encoded or not encoded, e.g., an audio filetype such as the MP3 audio format. The custom access permission settings may be implemented by obfuscating the protected portions of the original bitstream and then embedding “secret,” e.g., hidden and/or encrypted, versions of the obfuscated portions in parts of the data structure of the original file, e.g., in the form of “layers” that are held within audio stream containers such as channels. The content of the individual encrypted audio stream containers may then be decrypted according to each recipient’s permissions and layered on top of the obfuscated portions of the encoded media file before being rendered to the recipient.

USPTO Technical Field

This disclosure relates generally to systems, methods, and computer readable media for concealing information within encoded media files which may be distributed over a network and playable by recipients in a wide array of standardized software applications. More particularly, this disclosure is relates to Adaptive Privacy Controls for concealing information within audio files and audio bitstreams. Access permission settings for such audio files may be implemented by embedding one or more “secret,” e.g., hidden and/or encrypted, information portions in such encoded media file types, e.g., in the form of layers of audio information.

Background

The proliferation of personal computing devices in recent years, especially mobile personal computing devices, combined with a growth in the number of widely-used communications formats (e.g., text, voice, video, image) and protocols (e.g., SMTP, IMAP/POP, SMS/MMS, XMPP, etc.) has led to increased concerns regarding the safety and security of documents and messages that are sent over networks. Users desire a system that provides for the setting of custom, e.g., user-defined, access permissions for all or part of a file, including audio files that may or may not have been encoded using compression techniques.

Read the full patent here.

ABOUT ENTEFY

Entefy is an enterprise AI software company. Entefy’s patented, multisensory AI technology delivers on the promise of the intelligent enterprise, at unprecedented speed and scale.

Entefy products and services help organizations transform their legacy systems and business processes—everything from knowledge management to workflows, supply chain logistics, cybersecurity, data privacy, customer engagement, quality assurance, forecasting, and more. Entefy’s customers vary in size from SMEs to large global public companies across multiple industries including financial services, healthcare, retail, and manufacturing.

To leap ahead and future proof your business with Entefy’s breakthrough AI technologies, visit www.entefy.com  or contact us at contact@entefy.com.