1157 results about "Electronic mail" patented technology

An AI-powered agile project management system for automatic risk assessment and mitigation, including: a risk identification module configured to extract project data from agile project management tools, including but not limited to Jira, Trello, Asana, and Monday.com, and identify potential risks using machine learning and NLP; a risk analysis module configured to assign risk scores based on probability, impact, and severity using predictive analytics, where the module uses historical data, real-time project status, and external dependencies to determine the severity and impact of risks; a real-time monitoring module configured to continuously track project conditions, detect anomalies, and generate immediate notifications via email, mobile apps, or messaging platforms when high-risk events are identified; a risk mitigation module configured to dynamically recommend and execute proactive corrective actions such as task reassignment, resource optimization, schedule adjustments, and implementation of alternative strategies using AI-driven decision-making, where the actions can be automated through predefined workflows or manually adjusted based on AI recommendations; an AI-driven task prioritization module configured to dynamically prioritize tasks based on risk factors, project deadlines, and team workload distribution; an integration module configured to ensure seamless compatibility with existing Agile project management frameworks through API-based synchronization; a learning and continuous improvement module configured to refine risk prediction models over time using machine learning and historical risk mitigation results, with AI-driven models continuously updating risk assessment mechanisms based on evolving project conditions, industry-specific risk factors, and historical performance metrics; a compliance and audit reporting module configured to automatically generate risk reports, audit logs, and compliance checklists; a customizable risk assessment configuration module configured to allow project managers to define custom risk parameters, probability thresholds, and mitigation preferences; an interactive dashboard module configured to visualize data in real time, including risk trends, effectiveness of remedial actions, and analysis of project progress; and a scalability feature configured to be used in industries such as IT, healthcare, finance, construction, and manufacturing.

A method for efficiently generating a plurality of personalized email strategies and corresponding personalized emails for campaign recipients is disclosed. Multi-dimensional data comprising account data, recipient data, and seller data is received from one or more data sources. The received multi-dimensional data is processed to extract relevant features. A dynamic feature hierarchy is generated using the extracted features. A pre-trained machine learning model is fine-tuned using the dynamic feature hierarchy to generate email strategies, wherein model parameters are adjusted based on the hierarchy during fine-tuning. A plurality of email strategies is generated for each recipient by applying the fine-tuned model's recommendations. An email strategy is selected from the plurality of strategies based on one or more factors. A personalized email corresponding to the selected email strategy is generated. The personalized email and the selected email strategy used to generate it are displayed to a user.

A machine learning-based fraud detection system (100) for financial transactions, comprising the following: a data collection and preprocessing module configured to capture transaction data from financial institutions, payment gateways and bank modules, and to perform data cleansing, normalization and format conversion; a module for creating user profiles and behavioral analyses, configured to create dynamic user profiles based on historical transaction patterns, spending habits, device usage, and geographic location; an anomaly detection and risk assessment module configured to use machine learning algorithms to detect deviations from normal transaction patterns and assign a dynamic risk rating to each transaction; a fraud detection module configured to classify transactions as legitimate or fraudulent based on supervised and unsupervised learning techniques, including decision trees, support vector machines (SVMs), and deep learning models; a rule-based and hybrid fraud detection module configured to integrate predefined rule-based fraud detection mechanisms with AI-driven anomaly detection to improve fraud detection accuracy; a real-time fraud detection and warning module configured to monitor transactions in real time and generate security alerts via SMS, email or mobile app when suspicious activity is detected; a transaction verification and multi-factor authentication (MFA) module configured to implement adaptive authentication measures, including biometric verification, one-time passwords (OTP), and challenge-response authentication for high-risk transactions; a self-learning and model-updating module configured to dynamically update fraud detection models using reinforcement learning and federated learning techniques; a data encryption and security module configured to protect transaction data using encryption techniques, including AES-256 and RSA, to prevent unauthorized access and data breaches; and A dashboard and reporting module configured to provide real-time analytics, visualizations, and fraud detection reports for financial institutions to monitor, track, and mitigate fraudulent activity.

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.

An AI-powered system for optimizing industrial workflows and predictive maintenance, which includes the following: a network of sensors configured to collect real-time data from industrial plants, including temperature, pressure, vibration, and energy consumption metrics; a central control unit configured to process and analyze the collected data using machine learning algorithms that continuously improve by learning from both historical and real-time data to increase prediction accuracy; a predictive maintenance module configured to analyze data to predict potential equipment failures, schedule proactive maintenance tasks, and prioritize maintenance activities based on the predicted impact of the failure and the criticality of the equipment; a workflow optimization module configured to dynamically adjust operating parameters to optimize the process flow, including the detection of inefficiencies and the suggestion of improvements in real time; an integration module configured to connect and interact with existing industrial control systems and ERP (Enterprise Resource Planning) software to ensure a seamless flow of data between the platforms; a user interface configured to visualize data in real time, provide alerts and customizable dashboards, and is accessible via desktop and mobile devices for remote monitoring and management; an alarm and notification module configured to deliver critical alarms and maintenance notifications via email, SMS and in-app notifications to ensure a timely response; a cloud-based architecture configured to facilitate scalable data storage, remote access, and management across multiple industrial sites; a reporting module configured to generate comprehensive reports on plant performance, maintenance history, and workflow efficiency for analysis and decision-making; A security protocol to protect data integrity and ensure secure communication between all system components.

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.

The technology disclosed allows for leveraging decentralized credentials to achieve bidirectional authentication between two actors leveraging a messaging platform / system, such as email or another text-based system, verifiable credentials (VCs), and secure web endpoints. It empowers one party (“Sender”) to send a message enclosed with a Verifiable Presentation which allows another party (“Recipient”) to authenticate the message's provenance and the identity of the sender. Moreover, the message contains a link to a secure web endpoint, where the recipient can submit a response signed by their own Verifiable Presentation, allowing the Sender to authenticate the identity of the Recipient. In this way, both participants are able to authenticate each other's identities with an additional factor of authentication, with neither participant being required to share a single service.

Methods, apparatuses, and systems are described for generating customized content such as pitch communications, tailored pitch emails, press releases, customized user biographies, and posts, such as blog posts, byline posts, and social media posts. A content platform may be configured to use one or more machine learning models to generate the customized content based one or more user inputs and send the customized content to one or more target recipients.

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.

An AI-powered dispute triage and classification system (100) that includes: (a) a dispute input module configured to receive dispute inputs from multiple communication channels, including text, voice, email and chatbot interfaces; b) a Natural Language Understanding (NLU) module that uses machine learning models to extract intent, sentiment and contextual metadata from the dispute content; (c) a classification and prioritization module configured to categorize disputes into predefined taxonomies and assign priority levels based on predefined rules and AI-based predictions; (d) an intelligent routing module that routes disputes to specific human agents, automated systems or escalation paths based on classification results and organizational policies; (e) a solution assistance module configured to suggest or autonomously execute solution actions using AI-generated answers or predefined templates; and (f) a continuous learning module configured to retrain AI models using feedback data from dispute outcomes, user interactions and resolution performance, enabling automatic triage and classification of disputes in real time to optimise resolution time, accuracy and resource utilisation.

To provide a system.SOLUTION: A system comprises: means for analyzing the content of a junk mail; means for analyzing the transmission mail address of the junk mail; and means for blocking the junk mail on the basis of the analysis result.SELECTED DRAWING: Figure 1

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.

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.

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.

To solve a problem of local minor enterprises being unable to secure excellent workers due to population decline.SOLUTION: A system for providing a solution for local minor enterprises that enables as good responses and operations as in metropolitan areas, in a situation where excellent worker cannot be secured due to population decline, includes: means for supporting responses in connection with personnel recruitment; means for handling customer support (means for creating the content of e-mail, etc.), advising means in connection with the development of new products; and means for creating materials (means not only for creating text but also for using the latest template).SELECTED DRAWING: Figure 1

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.

This disclosure describes techniques for prioritizing the scanning and delivery of messages based on an account status and / or activity pattern. A messaging service provider may receive a message that is to be delivered to a user of the messaging service. A message processing service of the service provider may also receive and / or extract metadata from the email that enables the message processing service to determine an account status of the user of the messaging service. The message processing service of the service provider may also receive and / or extract account utilization data that enables the message processing service to identify an activity pattern of the user of the messaging service. Using the account status and / or the activity pattern, the message processing service may assign a certain priority to the message, and accordingly place the message in a queue to be scanned. The email may then be scanned to identify email-based threats.

In one embodiment, a method includes rendering each of a plurality of emails to generate a plurality of images and processing each of the plurality of images to generate a plurality of processed images. The method also includes extracting a plurality of features from each of the plurality of processed images and encoding the plurality of features into a vector for each of the plurality of processed images to generate a plurality of vectors. The method further includes determining whether two or more of the plurality of vectors are visually similar.

To create a security communication mediation system that allows users to contact each other only when necessary, without disclosing their real names, phone numbers, or email addresses.SOLUTION: When a call or e-mail is made between a mobile phone terminal of a security user who accepts a pre-registered security request and a mobile phone terminal of a bodyguard who provides security support to the security user, or a security supporter who is pre-registered with attribute information, when the intention of a security user to request monitoring is confirmed, the communication is controlled such that communication can be performed using a code that is pre-registered and can be used only by this system.SELECTED DRAWING: Figure 1

Aspects of the disclosure provide a method for categorization and generative analysis of electronic mail. The method may include receiving, from the email system, a plurality of email messages based at least in part on the journaling email address. The method may further include processing one or more email messages of the plurality of email messages. Each of the one or more email messages may be processed into a plurality of email message data objects. The method may further include determining one or more data insight parameters for each of the one or more email messages based at least in part on the plurality of email message data objects. Additionally, the method may include providing data insight analysis information. The data insight analysis information may be based at least in part on the one or more data insight parameters, the plurality of email message data objects, or both.