In one embodiment, the method of processing telephony sessions includes: communicating with an application server using an application layer protocol; processing telephony instructions with a call router; and creating call router resources accessible through a call router Application Programming Interface (API). In another embodiment, the system for processing telephony sessions includes: a call router, a URI for an application server, a telephony instruction executed by the call router, and a call router API resource.

A system for a vehicle includes a modem and a telematics controller. The modem is configured to operate in a normal service mode in which the modem connects to a mobile network whenever possible according to a subscriber identity module (SIM) configuration of the modem, and in an emulated limited service mode in which the modem emulates network conditions of a limited service mode by refraining from providing data or voice connectivity outside of emergency services. The telematics controller is programmed to responsive to receipt of an indication to transition from the normal service mode to the limited service mode, wait for any active data or voice connections to the mobile network to terminate, and responsive to termination of any active data or voice connections to the mobile network, transition the modem from the normal mode to the emulated limited service mode.

Methods and systems for detecting an answering machine/voicemail system using a machine learning model are provided herein. In some embodiments, a method for detecting an answering machine/voicemail system using a machine learning model comprises receiving an audio stream from a telecommunication session; parsing the audio stream into a plurality of audio files; converting each of the plurality of audio files into an image; inputting each of the converted images into the machine learning model; receiving a prediction from the machine learning model; sending an indication that an answering machine/voicemail system is detected when the received prediction is a beep.

A unified platform for managing telephone number (TN) ordering and procurement lifecycles is provided. The unified platform provides or interacts with functionality for reservations, porting, conflict checks, testing, and industry notification functionality. An associated graphical user interface provides the functionality to a variety of users including customers, salespeople, and order managers.

When a customer initiates an interaction with an interactive voice response (“IVR”) system, the customer may need to be transferred to a live agent. Apparatus and methods may formulate timing information for integrating a live agent into an interaction controlled by an artificial intelligence (“AI”) engine. The system may integrate machine generated responses into a customer interaction controlled by a live agent. The system may formulate timing information for intercepting the live agent with responses generated by the AI engine. The system may formulate the timing information using interactional analytics and preferences of a specific customer.

In one embodiment, the method of processing telephony sessions includes: communicating with an application server using an application layer protocol; processing telephony instructions with a call router; and creating call router resources accessible through a call router Application Programming Interface (API). In another embodiment, the system for processing telephony sessions includes: a call router, a URI for an application server, a telephony instruction executed by the call router, and a call router API resource.

Enablement of a voice channel being established between an IoT device and a controller through the use of a voice-line service system.

When a caller initiates an interaction with an interactive voice response (IVR) system, the caller may be transferred to a live agent. Apparatus and methods are provided for integrating automated tools into the interaction after the caller been transferred to the agent. The agent may determine which AI responses are appropriate for the caller. AI may be leveraged to suggest responses for both caller and agent while they are interacting with each other. Such human-computer interaction may shorten response time of human agents and improve efficiency of IVR systems.

A Virtual agent that is a fully automated computer software solution that can engage with real people, customers, clients and even other agents. Virtual agents have personality with animation and engage with the customer via text or voice or a combination of both as an actual person. Virtual agents are able to answer customer questions and provide information to address their issues. Virtual agents transfer calls to live agents if they cannot address customer issues.

Described herein are systems, devices, methods, and media for connecting a user for providing emergency assistance based on emergency alerts from triggering devices such as voice or sound triggered emergency alerts. In some cases, the location of the emergency is provided.