811 results about "Electronic mail" patented technology

Some embodiments of the present disclosure may include a method for processing request emails using a Generative AI email platform, including receiving a request email from a sender. Some embodiments may also include identifying the sender of the request email. Some embodiments may also include determining whether the sender may be an authenticated user. Some embodiments may also include, if the sender may be not an authenticated user, generating a reply email inviting the sender to sign up. Some embodiments may also include, if the sender may be an authenticated user, determining a prompt from the request email and inputting the prompt into the AI model. Some embodiments may also include receiving an output from the AI model based on the prompt. Some embodiments may also include generating a reply email based on the output and transmitting the reply email to the sender and / or another address.

Methods, systems, and computer storage media for providing a data analysis pipeline using a data analysis pipeline engine in a data intelligence system are described. A data analysis pipeline refers to a structured sequence of data processing steps that support transforming raw data into meaningful insights or actionable outcomes. The data analysis pipeline engine is an unsupervised learning pipeline based on clustering, topic modeling, and Large Language Models (LLMs). For example, the data analysis pipeline can use advanced machine learning techniques to automatically categorize emails into semantically similar clusters, enabling the data intelligence system to quickly identify and prioritize potentially high-risk emails for further investigation. The data analysis pipeline employs AI agents for context-aware graph induction relevance assessment. The AI agents employ induction and deduction loops to build and refine a data feature hypergraph (e.g., vulnerability hypergraph) that encompasses identified relevant data providing a holistic view of a contextual landscape.

Systems and methods are described for a connected AI agent for managed multidimensional search based on an electronic message and management policies. A messaging application at a client device can send a new electronic message, such as an email, to a connector service. An attachment can be ingested and stored in a vector database. Then one or more artificial intelligence (“AI”) agents can be selected for responding to the body of the email, such as a query in the body. The responses can be formatted and sent to multiple parties, such as a sending user of the electronic message and a recipient that was copied or also sent the new electronic message. The AI agents can use different AI models, prompts, and vector databases depending on user permissions. This allows for building up vector databases with relevant content items and answering user questions based on those vector databases.

The present technology provides methods and systems for enhanced email communication by generating sender-centric responses in an email client. The email client takes sender-specific data and data used to determine the relationship between the sender and receiver. This data is then used as input for a trained receiver-specific generative AI model. The generative AI model generates a custom response for a new inbound email which is displayed on the email client.

Computerized systems and methods for automated Access Permissions Review in an organization. A method includes: (a) receiving a textual description of an Access Review Policy; (b) constructing a trigger for automatically initiating an Access Review process; (c) automatically collecting organizational data that pertains to: (i) roles and positions of users, (ii) user-specific characteristics, (iii) email messages sent and received by users, (iv) description of events in which users had accessed elements of the Organizational Resource. Upon a triggering of the trigger, the method provides to a fine-tuned Large Language Model (LLM), the Access Review Policy and augmentation data from the organizational data, and a prompt instructing the LLM to generate a proposal to revoke, modify, add or maintain the Access Permissions of a particular user, and further instructing the LLM to generate output that describes reasoning and supporting evidence for the proposal.

Systems and methods are provided for managing AI (Artificial Intelligence) agents interactions with electronic communications that are displayed at an electronic communications interface, such as an email interface. The systems parse electronic communications to determine whether they correspond to new or existing requests and actions to be performed when responding to the request(s). The systems also generate notifications identifying the set of actions with visual identifiers that visually distinguish the set of actions based on whether they have been completed or not and whether they need authorization to be completed. The systems also display selectable controls for controlling how the AI agent performs the actions.

Systems and methods are provided for implementing deep search functionality using large language models (“LLMs”). In various examples, a computing system uses at least one LLM to generate intents based on a user query, to generate alternative queries based on a selected or identified primary intent, and to generate a relevance score for each search result that is obtained from a search utility (e.g., an Internet search engine, a file storage search utility, an email search utility, or a document storage search utility) in response to a primary query (corresponding to the primary intent) and the generated alternative queries being entered into the search utility. The search results from the search utility are sorted based on the corresponding generated relevance scores, and the sorted search results are caused to be displayed to the user as a deep search response to the user query.

A system and method for privacy-preserving communication validation and multi-attribute trust scoring is disclosed. The system analyzes communication metadata to determine pattern legitimacy by comparing current communication patterns against relationship fingerprints without accessing communication content. The system validates relationship context between communicating parties using interaction graph analysis and historical communication data. Cross-network intelligence correlation compares current patterns against aggregated patterns across voice, email, and messaging services, creating a self-strengthening security framework that recognizes emerging threat patterns while validating legitimate communication behaviors. The system generates comprehensive multi-attribute trust assessments comprising individual trust attribute scores including engagement rate, reliability index, channel preference, temporal pattern, and behavioral pattern, combined into overall trust levels. Trust context is displayed through a user interface presenting simplified, intuitive, and actionable information with progressive disclosure capabilities, enabling informed user decisions while preserving privacy. Communication processing actions provide users with appropriate engagement options tailored to specific trust assessment results.

The disclosed techniques provide improved methods of operating system (OS) search. Users are enabled to search for documents, emails, presentations, content they entered into a web form, meetings they participated in, and other interactions they had with their computing device. To accomplish this, screenshots are periodically captured and indexed. Machine learning models are used to infer embeddings for visual elements of the screenshots and / or text extracted from the screenshots. A full text index of a relational database may also be populated with text extracted from the screenshots. The embeddings and full text index may then be used to retrieve screenshots in response to a user history query. For example, screenshots of embeddings within a defined distance of an embedding of the user history query may be selected. Query results from different embedding indices and relational databases may be ordered by applying different weights to different kinds of search scores.

A system (100) for multi-channel purchase authorization with dynamic role validation, comprising: (a) a multi-channel request capture module configured to receive and standardise purchase requests initiated through a variety of communication channels, including corporate portals, mobile applications, emails and messaging platforms; (b) a role identification and contextual mapping module configured to dynamically retrieve user roles and contextual information based on real-time access management data and organizational hierarchy; c) a policy and rules module configured to evaluate purchase requests based on pre-configured and context-sensitive authorization policies, thresholds and compliance rules; (d) a dynamic role validation and escalation module configured to validate whether the requester has the authority to initiate or authorise a transaction and, if not, to automatically escalate the request to an appropriate authorised role; (e) an authorization workflow orchestration module configured to sequence approval steps, apply business logic, manage parallel or sequential workflows, and interface with external procurement systems; f) and an audit, logging and analytics module configured to record all request, validation and authorization actions in a tamper-proof log and generate real-time insights and compliance metrics, g) where the system enables real-time, role-based purchasing authorization across multiple channels with dynamic policy enforcement and escalation handling.

Implemented within a cyber security appliance, a non-transitory storage medium configured to store software that, when executed, conducts data loss prevention evaluation of an email message to protect against exfiltration of sensitive data from an enterprise. The software includes an email protection module and high availability (HA) fail-open control logic. The email protection module includes email threat detection logic to analyze content associated with an outbound or lateral email message for potential data loss characteristics. The HA fail-open control logic is configured to (i) detect operational failure of the email protection module or intake disruption of email messages via an Application Programming Interface (API) providing access to the email protection module and (ii) redirect the email messages to HA cloud infrastructure pertaining to the enterprise for temporary storage and subsequent release of the redirected email messages upon detecting the operational failure or the intake disruption.

A system and method are disclosed for enabling secure and low-friction peer-to-peer financial transactions using email communication without requiring user login. A payment server receives an email message from a responder that includes a token embedded in a mailto hyperlink. The server extracts and decodes the token to retrieve transaction data, including the responder's email address and a transaction amount. The server authenticates the responder by comparing the email address extracted from the token with the sender address of the email. Upon successful validation, the server initiates a financial transaction with a payment processing system—without requiring the responder to access a login page, enter credentials, or navigate to a website. The invention improves upon conventional browser-based payment workflows by reducing user interaction and enhancing transaction efficiency and security.

A method and system for limiting mobile device functionality when the mobile device is located in a pre-defined fixed geographic area. The mobile device may receive a local disabling signal from a disabling device, which, when detected by a Device Owner Application resident on the mobile device, limits the mobile device functionality. Alternatively, the system may use GPS based geofencing to determine that the mobile device is in a predefined geographic area, and then transmit instructions to the mobile device, where a Device Owner Application operates to restrict the mobile device functionality. Mobile device functionality may be limited by restricting the mobile device's ability to send and receive text messages, email messages and phone calls; restricting the mobile device's ability to respond to user input; restricting the mobile device's ability to utilize a web browser; and restricting the mobile device's web browser from accessing predetermined web sites.

The system obtains messages including multiple properties, such as a sender, a receiver, and content. The system creates a database to store the messages and presents the database in a user interface including a table including rows and columns. The database can be customized by including a custom column among the multiple columns. The system customizes the user interface by creating custom views of the database. The system receives an indication to create a view of the multiple messages, where the indication to create the view includes a criterion to select a subset of messages from the messages. The system creates the view including multiple layouts configured to visually provide important information associated with the subset of messages.

Features for providing a secure method of symmetric encryption for private smart contacts among multiple parties in a private peer-to-peer network. The features include a master key representing a unique blockchain ledger. The master key may be shared among multiple participants in a private peer-to-peer network. Sharing of the master key may include communicating the master key in an encrypted message (e.g., email) using public key infrastructure (PKI). In some implementations, more complex distribution features may be includes such as quantum entanglement. The features support instantiation of a smart contract using a specific master key. The request may be submitted as an entry to the ledger with appropriate metadata and / or payload information for identifying and processing the request.

Techniques for an email-security detection system to analyze incoming emails for Business Email Comprise (BEC) attacks of targeted new email users in an enterprise based on peer models of email recipients in an enterprise and the conversation history of recipients. A method is disclosed that includes analyzing an incoming email and identifying one or more recipients of the incoming email in an enterprise network; analyzing contextual information in the incoming email for the email intent, and associating the email with a target recipient; applying a relational model associated with peers of the target recipient for detecting whether the incoming email is a business email compromise (BEC) attack directed to the target recipient; applying a relationship model of other recipients of the incoming email for detecting whether the BEC attack is associated with the target recipient; and determining, whether the incoming email is a BEC attack.

A task management system detects condition(s) are satisfied with respect to task record(s), and triggers action(s) at least in part by substituting information from the task record(s) into placeholder(s) of user-modifiable template(s) to prompt large language model(s) for generating narrative(s) about how the condition(s) were satisfied. The triggered action(s) retrieve information from identified task record(s), substitute value(s) from the record(s) into the placeholder(s) of the user-modifiable template(s), and trigger(s) call(s) to large language model(s) to generate task completion narrative(s) or other narrative(s) for the task record(s). The narrative(s) may be stored in narrative field(s) of the record(s) for use in displaying the narrative(s) on a user interface, email notification, or other message.

System and method for managing information compliance and relevance using autonomous artificial intelligence (AI) agents in data transfer and communication environments. Some embodiments may include a core orchestration engine with multiple autonomous AI agents configured to manage and evaluate the compliance and relevance of information in communication and data transfer environments. The system may use weighted metrics to assess if information and actions comply with regulations and are pertinent to recipients, monitor email and data transfer, ensure regulatory compliance, and enhance information and knowledge sharing within organizations. The system may use semantic embeddings, part-of-speech analysis, and language models to extract and apply regulatory rules efficiently. These features may significantly reduce search space, computational overhead, and manual effort while improving security and accuracy.

The invention provides a context-based deep mail password strength measurement method, which comprises the following steps of: introducing user context information such as an e-mail, a name and a birthday on a basic password measurement model framework, and realizing information fusion through a multi-head self-attention mechanism; and a password sequence probability calculation model is constructed in combination with a character-level long-short-term memory network (LSTM). An evaluation system taking guess times as a core index is established to quantify the performance difference of different models under the condition that whether user context information exists or not. Experiments show that the method can more truly reflect the cracking capability of an attacker when the attacker masters the context information of the user.

Cybercriminals are using advanced techniques to access information not only inside a company network but outside of a company network in the ecosystem of company communications with customers, suppliers, partners, and professional advisors. There are many ways cybercriminals gain access to this information, often by compromising email accounts, archives, and document management systems outside of a company's own control and / or outside of their control to manage security of those external accounts. This invention provides an apparatus that will proactively detect when a cybercriminal has accessed or is attempting to access a document attached to an email, a document stored in a repository, a link to an e-signature transaction, a link to a file download (“Files”), and pre-emptively auto-lock the attempted-to-be-eavesdropped on Files and alert the File owner of a high risk information breach in progress, even if that breach is outside their network or information perimeter.

The present invention is a system and method to help with resolving the pervasive issue of unauthorized external service accounts and subscriptions created by employees within an organization. The present invention seeks to provide users with a system that strategically analyzes organizational email communications, which serve as a rich data source for identifying unauthorized external accounts and services. The system accesses each email account under an organizational domain, wherein each email is cleared of unnecessary content. Additionally, an LLM analysis performs various cross checks, and an AI integrity check verifies all LLM responses. Finally, the system and method documents and report all findings to the organization.

Operating effectively in an increasingly prolific Internet of Things environment, one needs the ability to message, whether device status, actions taken, recommendations for actions or other information to those with a need to know and support responses to actionable messages. Texts and e-mail are limited; they can neither provide other outputs, be targeted in intelligent fashion nor selectively relayed or contain execution instructions for target devices. The present invention is an Extended-Capability Messaging Appliance (ECMA) that communicates with other IoT devices that provides these capabilities and can include AI. ECMA and non-ECMA AI elements can constitute a Hybrid AI Backbone. The Hybrid AI Integrator receives results from multiple A elements and develops one or more conclusions. An ECMA may be configured as a Body-Area Network for individuals or a Business-Area Network for industry and other commercial applications with an AI Agent called BANDIT that processes requests from a user.

Customers of a software platform, such as a unified communications as a service platform, are enabled to control their own encryption keys used to encrypt and decrypt data from various communication services in the software platform. A key connector service is used to coordinate communications with a key management server for generating plaintext keys for data encryption and encrypted keys based on the plain text keys, and with a key broker server for storing and retrieving copies of the encrypted keys. A context identifier may be associated with an encrypted key and used to track which data has been encrypted with an underlying plaintext key. Examples of data encrypted may include conference recordings, webinar recordings, phone call recordings, voicemails, emails, and calendar tokens.

Implementations described herein relate to an application and / or automated assistant that can identify arrangement operations to perform for arranging text during speech-to-text operations—without a user having to expressly identify the arrangement operations. In some instances, a user that is dictating a document (e.g., an email, a text message, etc.) can provide a spoken utterance to an application in order to incorporate textual content. However, in some of these instances, certain corresponding arrangements are needed for the textual content in the document. The textual content that is derived from the spoken utterance can be arranged by the application based on an intent, vocalization features, and / or contextual features associated with the spoken utterance and / or a type of the application associated with the document, without the user expressly identifying the corresponding arrangements. In this way, the application can infer content arrangement operations from a spoken utterance that only specifies the textual content.

Systems and methods for automated linkage of enriched transaction data to a record of charge are provided. Electronic enriched transaction data, such as receipt information, provided by merchants, merchant aggregators, or third parties may be automatically associated with the corresponding transaction, and transmitted after the sale, or after authorization of the transaction, without user intervention. The enriched transaction data may be automatically associated with the record of charge at the acquirer or issuer end. Transaction account holders are able to view and / or download the electronic enriched transaction data with the record of charge, without the need for manually initiating emailing or attaching or the electronic enriched transaction data.

Systems and methods provide for automating the conversion of email orders into structured order entries using generative AI, leveraging an integrated architecture comprising a Real-Time Data Mesh (RTDM), Advanced Analytic and Machine Learning (AAML) Module, and Single Pane of Glass (SPoG) User Interface. The system includes an Email Parser that extracts order information from emails, an Order Generation Engine that converts this information into structured entries, and an Integration Gateway that synchronizes the entries with external systems. The RTDM manages data flow and transformation, while the AAML provides predictive analytics and process automation. The SPOG UI performs real-time data visualization and user interaction. The system enhances order processing efficiency, accuracy, and scalability, enabling businesses to process email orders with minimal manual effort and greater precision.

The system obtains multiple views associated with a first multiplicity of messages, where a view among the multiple views includes a criterion, a visual appearance, and an action. The criterion defines a message to include in the view, and the action is configured to trigger automatically when the message is included in the view. The system applies the view to the second multiplicity of messages by: selecting a subset of messages among the second multiplicity of messages according to the criterion; presenting the subset of messages to the user according to the visual appearance associated with the view; and performing the action on the subset of messages.

A method of rating a phishing email's human phishing detection difficulty includes identifying cues in content of the email tending to indicate that the email is a phishing email; assigning weights to identified cues; assessing a relative severity based on the weighted cues; determining an overall human detection difficulty of the email based on the relative severity of the weighted cues and a total number of the identified cues determining a target audience for the phishing email; determining a plurality of sub-groups of the target audience; and determining a plurality of respective premise alignments of the email by characterizing respective pertinences of a message premise of the email with respect to each respective sub-group of the target audience; wherein the step of determining an overall human detection difficulty of the email is additionally based on the respective premise alignments of the email.

The present disclosure describes a customized voice messaging platform. The customized voice message placement can enhance engagement using personalized audio content. The platform can generate authentic-sounding voice messages using Al-driven processes, including text-to-speech (TTS) technology and audio concatenation, to create personalized audio content. The platform supports various delivery channels such as SMS, email, podcasts, and streaming services. The platform can incorporation visual elements like brand logos and animations into personalized messages. The platform can provide campaign creation functionality, enabling users to create campaigns deliver customized messages across multiple channels. The platform can provide message suggestions, automated testing, and other features. The platform can support rules for determining when to send messages and / or the content of messages.

Example solutions for reducing the likelihood of hallucinations by large language models (LLMs) and improving the relevance of generated text are disclosed. A set of multiple of machine learning (ML) models, each custom-trained to identify a different specific topic within text, dynamically generate multiple topic-specific prompts from a received email in an email thread. A user, responding to the prompts, produces material that is used in conjunction with customer relations management (CRM) data and enterprise suite data (e.g., calendar / schedule information) to dynamically generate an LLM prompt. An LLM, using the prompt, generates output text suitable for a business correspondence, such as a reply email, to the sender of the email. The combination of the responses to the multiple topic-specific prompts and the CRM and enterprise suite data in the LLM prompt both ensures relevance of the reply correspondence and minimizes the risk of hallucinations.