Abstract: Modular technologies for servicing telephony systems are disclosed herein. An example method includes receiving a user request to service a telephony system of a user, and transmitting a set of available session initiation protocol (SIP) providers to a user computing device for analysis by the user. Responsive to receiving a user input, the example method includes connecting the user computing device to an SIP trunk, connecting to a serviceable call location included in the user request through the SIP trunk, wherein connecting to the serviceable call location initiates a data stream, and executing a servicing task included in the user request. The example method includes recording a portion of the data stream during execution of the servicing task, storing the portion of the data stream, and causing the user computing device to display the portion of the data stream for viewing by the user.

Abstract: A machine learning task automation method includes receiving a message, preprocessing the message to generate extracted data, analyzing the extracted data to generate classification data, analyzing the extracted data to generate information extraction; and generating and transmitting a response. A computing system includes a processor, and a memory including instructions that, when executed, cause the computing system to receive a message, preprocess the message to generate extracted data, analyze the extracted data to generate classification data, analyze the extracted data to generate information extraction data; and generate and transmit a response. A non-transitory computer readable medium containing program instructions that when executed, cause a computer to receive a message, preprocess the message to generate extracted data, analyze the extracted data to generate classification data, analyze the extracted data to generate information extraction data; and generate and transmit a response.

Abstract: Artificial intelligence (AI) based technologies for improving patient intake are disclosed herein. An example method includes receiving a patient intake request from a user; initiating, based on the patient intake request, a patient intake data stream including verbal responses from the user regarding patient intake of the user; applying, while simultaneously receiving the patient intake data stream, a natural language processing (NLP) model to the verbal responses from the user to output (i) textual transcriptions and (ii) intent interpretations; generating, by a care plan generation module, a recommended care plan based on the textual transcriptions and the intent interpretations; identifying, by an intent interpretation fulfillment module, one or more recipient entities to receive the textual transcriptions and the recommended care plan; and transferring the textual transcriptions and the recommended care plan to one or more recipient entity devices of the one or more recipient entities.

Abstract: Artificial intelligence (AI) based technologies for improving patient appointment scheduling and inventory management are disclosed herein. An example method includes receiving, at a server including a natural language processing (NLP) model, an appointment request from a user. The example method further includes initiating, based on the appointment request, a patient appointment data stream including verbal responses from the user regarding an appointment of the user. The example method further includes applying, while simultaneously receiving the patient appointment data stream, the NLP model to the verbal responses from the user to output (i) textual transcriptions and (ii) intent interpretations. The example method further includes querying a scheduling database to determine a matching appointment that satisfies a distance threshold, a date threshold, a service threshold, and an inventory threshold.

Abstract: A computing system for cross-platform support and log summarization includes a language model, APIs, processors, and memories to generate queries and troubleshooting steps from log files and IR system results. A method involves obtaining log files, generating IR system queries, and creating troubleshooting steps using a language model. A non-transitory computer readable medium contains instructions for obtaining log files, generating queries, and creating troubleshooting steps based on log files and IR results.

Abstract: An account manager virtual assistant computing system includes a processor and a memory storing instructions that when executed cause the system to receive a message, process the message using a quote classification machine learning model, generate a response including price information, and process the message using an information extraction machine deep learning model; and transmit the response. A non-transitory computer readable medium includes program instructions that when executed cause a computer to receive a message, process the message using a quote classification machine learning model, generate a response including price information, and process the message using an information extraction machine deep learning model; and transmit the response.

Abstract: A computing system and method for mapping a migration to a new distributed file system is provided. A method may include receiving file system metadata from an existing distributed file system, comparing permissions for each file and each user, generating a plurality of recommended groups, recommended folders, and recommended permissions, and presenting the recommended groups, recommended folders, and recommended permissions to a user.

Abstract: A system includes a processor, and a memory containing instructions that, when executed, cause the voice control hub computing system to receive a request; receive and transmit an utterance; convert the utterance to a string; analyze the string using a machine learning model trained using a command interpreter; and receive and dispatch the intent and the entity. A method includes receiving a request; receiving and transmitting an utterance; converting the utterance to a string; analyzing the string using a machine learning model trained using a command interpreter; and receiving and dispatching the intent and the entity. A non-transitory computer readable medium containing program instructions that when executed, cause a computer to: receive a request; receive and transmit an utterance; convert the utterance to a string; analyze the string using a machine learning model trained using a command interpreter; and receive and dispatch the intent and the entity.

Abstract: A computing system includes a processor, a network interface controller (NIC) configured to communicate via multiple networks; a virtual desktop infrastructure application (VDIA) including computer-executable instructions configured to: perform operations and maintain a virtual hosting environment; remediate a finding by hardening network access; and notify a user of an issue; and an information technology service management application (ITSMA) accessible to the VDIA. A computer-implemented method includes configuring a NIC to communicate via multiple networks; accessing an ITSMA; performing operations to maintain a hosting environment; remediating a finding by hardening network access; and notifying a user of an issue.

Abstract: Systems, methods, and computer-readable medium storing instructions for generating predicted resource allocation information of an organization based on dynamically ingested data, including ingesting context information, ingesting public data, ingesting record data, normalizing the public data with the record data, determining a first set of weights corresponding to the record data and a second set of weights corresponding to the public data, generating predicted resource allocation information, and causing the predicted resource allocation information to be displayed. In some aspects, additional information may be received or ingested, including one or more of additional public data, additional private data, or feedback from a user. The additional information may be used for adjusting one or more of the first set of weights or the second set of weights.

Abstract: An internet end-user device includes a processor, a network interface controller; and a memory including instructions that, when executed by the one or more processors cause the end-user device to configure the end-user device to use a red network and perform dependency verification of the end-user device. A method includes configuring an end-user device to use a red network; and performing dependency verification of the end-user device. A non-transitory computer readable medium includes program instructions that when executed, cause an internet end-user device for use by end users to configure the end-user device to use a red network and perform dependency verification of the end-user device.

Abstract: A computing system includes a processor; an electronic network; and a memory having stored thereon computer-executable instructions that, when executed, cause the computing system to receive hyperscaler cloud computing data; process the cloud computing data to determine status information; compare the status information rules; and generate cloud maturity scores. A method includes receiving hyperscaler cloud computing data; processing the cloud computing data to determine status information; comparing the status information rules; and generating cloud maturity scores. A computer-readable medium includes computer-executable instructions that, when executed, cause a computer to: receive hyperscaler cloud computing data; process the cloud computing data to determine status information; compare the status information rules; and generate cloud maturity scores.

Abstract: A computer-implemented method for intelligent collection and selective sharing of information technology asset inventory over a managed services platform is disclosed herein. An exemplary method may include receiving, from a customer, a selection of one or more information technology services of an information technology service provider. The exemplary method may further include receiving, via a network tunnel between a machine avatar in a computing environment and a base management node, network traffic of the customer addressed to the one or more information technology services; and storing a portion of the network traffic. The exemplary method may further include generating a service notification for the customer based on the portion of the network traffic; and transmitting the service notification to the machine avatar through the network tunnel.

Abstract: Techniques for providing natural language understanding (NLU) services to contact centers are disclosed herein. An example method includes receiving, at a cloud NLU connector, a data stream from a contact center that includes an audio stream, extracting the audio stream from the data stream, and transmitting the audio stream through a secure network to a cloud-based NLU hub. The cloud-based NLU hub is communicatively coupled to a plurality of cloud-based NLU service providers and stores a plurality of user NLU profiles that each designate one or more cloud-based NLU service providers to provide NLU services. The example method further includes determining one or more designated cloud-based NLU service providers to provide at least one NLU service corresponding to the audio stream, and causing the one or more designated cloud-based NLU service providers to process the audio stream in accordance with the at least one NLU service.

Abstract: A computer-implemented method includes processing input packets; generating indexed logs, packets of network traffic, and system monitoring information; generating analytics or visualizations; and transmitting the analytics or the visualizations. A computing system includes a processor, a network interface controller; and a memory including instructions that, when executed cause the system to: process input packets; ingest system monitoring information; generate indexed logs, packets of the network traffic, and system monitoring information; generate analytics or visualizations; and transmit the analytics or the visualizations. A non-transitory computer readable medium includes computer-executable instructions that when executed, cause a computer to: process input packets; ingest system monitoring information; generate indexed logs, packets of the network traffic, and system monitoring information; generate analytics or visualizations; and transmit the analytics or the visualizations.

Abstract: A method for delegating conference rooms using room presence detection includes identifying a human in a digital image using a trained machine learning model; updating room presence information; and determining a next-available conference room. A room presence computing system includes a processor; and a memory storing instructions that, when executed by the processor, cause the system to: identify a human in a digital image using a trained machine learning model; update room presence information; and determine, by analyzing the room presence information, a next-available conference room. A non-transitory computer readable medium includes program instructions that when executed, cause a computer to: identify a human in a digital image using a trained machine learning model update room presence information; and determine, by analyzing the room presence information, a next-available conference room.

Abstract: A computing system includes a processor; an input device; and a memory containing instructions that, when executed, cause the computing system to receive a data description corresponding to a graphical user interface control; identify the graphical user interface control using a trained convolutional neural network; and display an action palette. A non-transitory computer readable medium includes program instructions that when executed, cause a computer to: receive a data description corresponding to a graphical user interface control; identify the graphical user interface control using a trained convolutional neural network; and display an action palette. A computer-implemented method includes receiving a data description corresponding to a graphical user interface control; identifying the graphical user interface control using a trained convolutional neural network; and displaying an action palette.

Abstract: Artificial intelligence (AI) based technologies for improving patient intake are disclosed herein. An example method includes receiving a patient intake request from a user; initiating, based on the patient intake request, a patient intake data stream including verbal responses from the user regarding patient intake of the user; applying, while simultaneously receiving the patient intake data stream, a natural language processing (NLP) model to the verbal responses from the user to output (i) textual transcriptions and (ii) intent interpretations; generating, by a care plan generation module, a recommended care plan based on the textual transcriptions and the intent interpretations; identifying, by an intent interpretation fulfillment module, one or more recipient entities to receive the textual transcriptions and the recommended care plan; and transferring the textual transcriptions and the recommended care plan to one or more recipient entity devices of the one or more recipient entities.

Abstract: Artificial intelligence (AI) based technologies for improving patient appointment scheduling and inventory management are disclosed herein. An example method includes receiving, at a server including a natural language processing (NLP) model, an appointment request from a user. The example method further includes initiating, based on the appointment request, a patient appointment data stream including verbal responses from the user regarding an appointment of the user. The example method further includes applying, while simultaneously receiving the patient appointment data stream, the NLP model to the verbal responses from the user to output (i) textual transcriptions and (ii) intent interpretations. The example method further includes querying a scheduling database to determine a matching appointment that satisfies a distance threshold, a date threshold, a service threshold, and an inventory threshold.

Abstract: A computing system includes a processor, a network interface controller configured to communicate via a black network, a gray network and a red network; a virtual desktop infrastructure application including computer-executable instructions configured to: perform systematic monitoring; remediate a network vulnerability finding; and notify a user; and a service management application. A computer-implemented method includes configuring a network interface controller to communicate via a black network, a gray network and a red network; accessing a service management application; performing systematic monitoring; remediating a network vulnerability finding; and notifying a user.