113 results about "Customer support" patented technology

An industrial technical support system acts as an interactive assistant that leverages generative artificial intelligence (AI) techniques to suggest solutions to industrial alarm conditions or other performance problems based on earlier documented solutions, thereby expediting the process of finding alarm resolutions. The system enhances a user's prompt with relevant contextual data retrieved from stored documentation as well as relevant past chat histories to assist the system's generative AI model in recommending accurate resolutions to alarm conditions or performance issues described by the user's prompt.

A disclosed method may include (i) transforming an original corpus of support call transcriptions for support calls received at a telecommunication provider at least in part by prompting a large language model to summarize each support call transcript in the original corpus of support call transcripts for the support calls received at the telecommunication provider to output a summary corpus of large language model generated summaries of support call transcriptions, (ii) extracting from the summary corpus of large language model generated summaries of support call transcriptions a ranked ordering of client support topics for clusters within the summary corpus of large language model generated summaries of support call transcriptions, and (iii) resolving, by the telecommunication provider, the client support topics in an actual order that is determined at least in part based on the ranked ordering of client support topics for clusters within the summary corpus.

Embodiments of the present disclosure provide methods, systems, and computer program products for assigning and dynamically managing a Customer Proficiency Rating for a specific customer for implementing enhanced customer support operations for a supported product or service. Disclosed embodiments provide an AI virtual support agent that receives a customer support request for a current problem, obtains a customer statement of understanding for the current problem and provides a set of questions, to obtain customer responses. In an embodiment, the AI virtual support agent evaluates the customer statement and customer responses, and calculates a customer proficiency rating for a specific customer for the support request to identify a customer skill level for the current problem. The AI virtual support agent routes customers to an optimal human support agent based on the customer proficiency rating.

Systems / techniques that facilitate automatic product support systems and methods via generative artificial intelligence (GAI) and customer interactions are provided. In various embodiments, a system can access an electronic interaction record pertaining to a software product. In various aspects, the system can synthesize, via execution of GAI on the electronic interaction record, first text that describes a problem afflicting the software product. In various instances, the system can determine, based on executing the GAI on the first text, whether there is an available software feature in an available software feature repository that addresses or solves the problem. In various cases, the system can, in response to a determination that there is no available software feature that addresses or solves the problem, synthesize, via execution of the GAI on the first text, a recommended design alteration to the software product that would address or solve the problem.

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 method and a system for building a knowledge base for industrial use and using the knowledge base to manage and control industrial products, processes, resources and systems. The knowledge base uses semantic processing modules and artificial intelligence tools to enable continuous extraction and entry of knowledge into the knowledge base from various sources including user inputs, operation status reports, manuals, websites, diagnosis reports, sensor data, operation sequence, and other static or ephemeral sources. The knowledge base is supported by a knowledge base management system that includes a suite of tools to support knowledge entry, update, retrieval and visualization using both natural language based queries and structured queries with predefined syntax. The system also provides tools to retrieve and assemble knowledges on-the-fly to support industrial applications including to design products, services or production lines, build production process, manage scheduling and flow, monitor and optimize operations, diagnose issues, apply business logics, procure materials and supplies, manage and train workforce, and provide customer supports.

A system is described for training a virtual agent of a listing network platform using a machine learning model. The system establishes a communication session with a virtual agent of a listing network platform and generates, by a first machine learning model, conversation data representing a customer support issue associated with the listing network platform. The system transmits, by the first machine learning model, at least a portion of the conversation data to the virtual agent via the communication session. The system receives one or more responses to the at least the portion of the conversation data from the virtual agent in the communication session and stores a simulated conversation comprising the at least the portion of the conversation data generated by the first machine learning model and the one or more responses received from the virtual agent.

An autonomous customer support Chatbot Agent utilizes a large language model to aid in implementing a workflow to solve a customer issue. A natural language workflow policy may be selected by an admin, along with tools such as API calls. The large language model determines the implementation details for the workflow based on the workflow policy and the selected tools.

The invention belongs to the technical field of customer service work order processing, and discloses an event priority ranking distribution method and system, and the method comprises the steps: converting historical multi-round dialogue data into a numeralized historical work order emotion score sequence set; the Hidden Markov model is trained by using a Boem-Weili algorithm, and core dynamic parameters of customer emotional evolution are learned; an optimal risk score threshold value after calibration is obtained through calibration; for each work order in progress, the probability distribution of each current hidden state is deduced in real time, and a forward-looking negative upgrading risk score is calculated; and when the negative upgrading risk score exceeds the calibrated risk score threshold, automatically triggering priority adjustment, and generating an updated work order record. According to the invention, a quantifiable framework based on probability prediction is provided, and customer support is converted from passive and post-response type work order processing into an active and pre-warning type risk management normal form.

To provide a system for efficiently collecting opinions of customers in a situation in which coordination of customer support and marketing is insufficient, for improving customer satisfaction.SOLUTION: A system comprises: means for automatically generating in any period, opinions of customers collected from a customer support; and means for analyzing a result of investigation of customer satisfaction.SELECTED DRAWING: Figure 1

Embodiments described herein provide a structured conversation summarization framework. A user interface may be provided which allows an agent to perform a conversation with a customer, for example regarding resolving a customer support issue. Utterances by both the agent and customer may be stored, and at the end of the conversation, the utterances may be used to generate a structured summary. The structured summary may include components such as a general summary, an issue summary, and a resolution summary. Using neural network models and heuristics, each component of the summary may be automatically generated.

Various embodiments provide for a unified interface for testing a system, which can include a device under test (DUT). In particular, some embodiments described herein can be used to implement a Unified Test Framework (UTF) that comprises an architecture that provides a unified (or common) software interface to one or more test methods used during a development life cycle of a system. Example test methods can include, without limitation, modeling, verification, simulation, emulation, validation, customer support, and the like.

An industrial technical support system leverages generative artificial intelligence (AI) techniques to generate technical support guidance and recommendations in response to natural language technical support requests submitted as natural language input. The system can maintain and leverage one or more sets of custom models trained with sets of domain-specific training data specific for different industrial domains. When a natural language technical support query is received, the system leverages the domain-specific training data as well as responses prompted form a generative AI model to formulate and render technical support recommendations for addressing a performance or design issue described by the query.

To provide a system.SOLUTION: A system includes automatic browser operation means, means for autonomously performing service tests, means for specifying functions which are difficult to be understood by users, means for performing improvement proposal, means for proactively providing prior support through customer support chat, means for meeting problems before the problems surface, and means for realizing improvement of user experience and business efficiency.SELECTED DRAWING: Figure 1

To improve efficiency and reduce the burden in customer support.SOLUTION: A system includes: a learning model for an automatic response system; a database for providing appropriate answers to general issues and FAQ; and an interface for receiving inquiries from users.SELECTED DRAWING: Figure 1

To provide a support by a chatbot for achieving quality improvement of customer support in a purchasing experience.SOLUTION: A system includes: means for supporting by a chatbot for achieving quality improvement of customer support in a purchasing experience; means for using proper language and making a proposal in accordance with the request of a user; and means for collecting and analyzing information regarding the purchasing experience.SELECTED DRAWING: Figure 1

The invention relates to an enterprise customer relationship management system and a management method thereof, and the method comprises the following steps: a manager inputs user information in a user management module, sets the role and the corresponding authority of a user, collects new customer information, adds the new customer information into the system, classifies customers, and stores the classified customers into a database; customer data are analyzed to know customer demands and preferences, potential sales opportunities are tracked and managed in the sales management module, customer problems, complaints and demands are recorded in the customer service and support module, and the processing progress is tracked; client support and solutions are provided, marketing activities are designed and executed in the market management module, client reports and data analysis are generated in the statistics and analysis module, and client growth, sales trends and the like are provided; according to the invention, through a comprehensive customer management tool and a data analysis function, an enterprise is helped to improve customer satisfaction, enhance customer loyalty and improve sales and marketing efficiency.

To provide a system capable of reducing inquiries, improving the efficiency of corporate counter operations, and providing an auto-reply service.SOLUTION: The system is an automation system for customer support including means of reducing inquiries; means of creating flow FAQs in counter operations at a corporation; and an auto-reply service.SELECTED DRAWING: Figure 1

A computer implemented system to assist a user includes a cognitive computation module which can speak to, listen to and / or see. The system can assist in patient care delivery, driving, providing security, customer support and identity verification. It may be configured in a processor of the computing device which receives text data input after converting speech into text. The received text data is analysed by the module using an artificial intelligence and / or decision rules modules. The modules may create a response of text output which is converted to speech data using text to speech module and sent to the communication module to speak out. It identifies posture of human body, or the face of a human or a user using computer connected camera and also receives input from other sensors or devices connected to the computer and sends input to the cognitive communication module for analysis and response.

Techniques for locking and unlocking clusters of content items are disclosed. A clustering algorithm is executed to assign content items to corresponding clusters. A lock is then applied to the clusters, ensuring that content items associated with the locked clusters will not be reassigned to a new cluster while the cluster is in a locked state. Characteristics associated with the first clustering algorithm, the set of clusters, and / or the content items are monitored for cluster unlocking criteria. After determining that cluster unlocking criteria has been met for a cluster, the cluster is unlocked. The clustering algorithm is then applied to content items from the unlocked cluster.

The Artificial Intelligence driven service outage detection and customer support ticket management system in customer support platforms includes a customer support platform that is operatively coupled to the service outage detection system. A data collector gathers input data from a product status page and a service request tracker document. A service outage detector (SRT) detects the service outage by monitoring the product status page and incoming customer support tickets raised against the products by the users. A comparator compares the details of the product status page and the SRT document to confirm the occurrence of the service outage. A customer support ticket router updates the customer support ticket routing process based on the confirmed service outage status. A response generator generates an automated, predefined response including service outage information and any expected resolution or alternative support options and notifies the user utilizing a notification module.

To provide a system.SOLUTION: A system includes: means to accumulate sales activity to a client, attempts to realize success of the client using an in-house product and an in-house service, a corresponding log for customer support, a progress situation for a contract with the client, and information including the contract content to client relationship management (CRM) system; creation means for creating a health score which is a digitized index of a health state and satisfaction of the client; extraction means for extracting a company where the health score is a constant threshold or less and a company with which a constant period has passed from an immediate contract renewal as company groups with specific conditions; means for creating a list of clients selected based on a specific condition targeting a customer success manager (CSM) who is a person to carry out a roll for supporting the success of a client; means for distributing the list; a setting unit for setting timing for a next contact to the client when transmission of reference material to the client is completed; an engine for recognizing emotions of the client; and means for digitizing the emotions.SELECTED DRAWING: Figure 1

We provide the system. [Solution] A means of collecting employees' closing talks as data, A method for converting collected data into text data and cleansing it, A method for training a generative AI using cleansed data, A means of providing real-time customer support using trained AI models, A means of providing employees with a simulation environment to learn closing techniques, A system that includes this.

A system is provided.SOLUTION: A system comprising: means for learning contents of an inquiry for support and generating an illustration as trouble parts for visually expressing the contents; means for distributing the generated illustration to a user terminal and providing an interface through which a user can visually select a problem; means for automatically generating an appropriate inquiry sentence based on illustration information selected by the user; means for providing an interface through which the user can finely adjust the generated inquiry sentence; and means for transmitting a final inquiry sentence adjusted by the user to customer support.SELECTED DRAWING: Figure 1

Embodiments described herein are generally related to data analytics environments, and are particularly directed to systems and methods for use with a data analytics environment to enable use of AI in providing customer support. Machine learning AI models are trained based on one or more previous service request lifecycles of service requests of a customer to determine latent emotions of the customer based on determined customer problem data. A customer service prioritization signal related to a current service request of the customer is generated by a predictive analytics application that includes the models. The customer service prioritization signal is indicative of a need to prioritize a current service request of the customer based on the determined latent emotions of the customer and is generated during and prior to the end of the lifecycle of the current service request whereby escalation of the current service request may be deferred or prevented.

To provide a system.SOLUTION: A system comprises means for reading past chat support logs, FAQs, and the like; means for performing voice-based customer support based on such information; means for adjusting conversation speed and font size according to customer age category; and means for delivering customer service using a character tailored to individual customer preferences.SELECTED DRAWING: Figure 1

The present disclosure relates to detecting and extracting text entities within customer requests using a machine learning model. In one example, a method includes: receiving a customer request via a communication channel; displaying in a customer support user interface the customer request; processing the customer request with a machine learning model; determining: position data related to at least one text entity within the customer request; and entity type data corresponding to the at least one text entity; modifying the at least one text entity displayed in the customer support user interface based on the determined position data related to the at least one text entity; and displaying in an entity modification user interface element in the customer support user interface: a type of the at least one text entity based on the determined entity type data; and one or more user interface elements each configured to implement a corresponding action.

To perform guidance at a customer window contacted by a user even when it is difficult to acquire information necessary for performing guidance for solution from the user.SOLUTION: An image forming apparatus 100 includes a reception unit 31 that receives abnormality information indicating that an operation of the image forming apparatus 100 is abnormal, a related log extraction unit 33 that extracts related log information determined in advance to be highly related to the abnormality information received by the reception unit 31 from log information included in the image forming apparatus 100, a feature extraction unit 34 that extracts a feature by performing pattern matching on the related log information extracted by the related log extraction unit 33, and an output unit 36 that outputs a log summary generated from the feature extracted by the feature extraction unit 34.SELECTED DRAWING: Figure 3

This technology reduces the burden on users and improves engineers' ability to quickly resolve critical errors. [Solution] The computer system includes: a collection unit that monitors network connections between multiple computer peripherals and collects usage information and error information; a storage unit that stores error information describing the occurrence of an error in a database in response to the detection of an error in a computer peripheral; a code generation unit that generates a support code and stores the support code in the database in association with the error information; a code display unit that transmits the support code to the computer peripheral for display; a reading unit that reads the error information from the database in response to the receipt of a support code from a user device; and an error information display unit that displays the error information on the user interface of a customer support technician.

A computer system is configured to remotely manage technical support for a plurality of computer peripherals, by performing the steps of: monitoring network connections between the computer system and the plurality of computer peripherals to collect usage information and error information; and in response to detecting that a first error occurred in a computer peripheral of the plurality of computer peripherals: storing, in an entry of a database, error information describing an occurrence of the first error; generating a first support code and storing the first support code in the entry of the database in association with the error information; transmitting the first support code to the computer peripheral to be displayed thereby; reading the error information from the entry of the database in response to receiving the first support code from a user device; and displaying the error information on a user interface (UI) of a customer support technician.