An intelligent interface responds to text messages, which in a particular embodiment are addressed to a landline phone number. An IP network interface receives requests including a source phone number, message content and the destination phone number. The intelligent interface includes access to a serialized intent file created by a vectorizer. An intent classifier determines one intent from the serialized intent file based on the received message content. A response is generated according to the one intent. A reply generator generates a reply including the source phone number as a destination, the landline phone number as a source and the response.

A server may assign a temporary phone number and an extension number to a shipment. The temporary phone number may be based on a geographic location of where the shipment is to be delivered. The extension number is associated with the shipment. The temporary phone number and extension number may be included on a shipping label rather than the user's phone number. During the delivery of the shipment, a delivery person may encounter a delivery issue, such as needing directions. The delivery person may call the temporary phone number and extension number and be connected to a user device. The delivery person may communicate the delivery issue, such as asking for directions to the user's residence. Upon delivery of the shipment, the server disassociates the temporary phone number and the extension number from the shipment.

A system and method for automating the process of renewing prescriptions on behalf of patients using machine navigation of Interactive Voice Response (IVR) trees used for the refilling of prescriptions used by most local pharmacies.

An intelligent interface responds to text messages, which in a particular embodiment are addressed to a landline phone number. An IP network interface receives requests including a source phone number, message content and the destination phone number. The intelligent interface includes access to a serialized intent file created by a vectorizer. An intent classifier determines one intent from the serialized intent file based on the received message content. A response is generated according to the one intent. A reply generator generates a reply including the source phone number as a destination, the landline phone number as a source and the response.

Methods and systems are disclosed for enabling the generation of a token corresponding to a tone generated by a telephony system, comprising receiving one or more dual tone multi-frequency (DTMF) tones generated by a telephony system, generating a token based on the one or more DTMF tones; and transmitting the generated token to a merchant system.

The present invention provides a method and a system utilizing an AI entity for confirming an agreement has been entered between a first entity and a second entity during a verbal communication, capturing the portions of the communication that constitute the elements of an agreement and storing the portions for later verification of the agreement.

Methods and systems are disclosed for enabling the generation of a token corresponding to a tone generated by a telephony system, comprising receiving one or more dual tone multi-frequency (DTMF) tones generated by a telephony system, generating a token based on the one or more DTMF tones; and transmitting the generated token to a merchant system.

To provide a mechanism to improve convenience of a user who uses an automatic order service of consumer products and the like. An apparatus having a capability of receiving a consumable product automatic order service acquires first information indicating presence/absence of registration for using the automatic order service. Then, in a case where access information on a site relating to the consumable product is output based on the acquired first information, access information on a site different between a case where registration to the automatic order service is completed and a case where registration is not completed is output.

Systems and methods for monitoring a user's insurance activities and generating an insurance agency IVR menu customized for each user are presented. In some embodiments, one or more items of interest to an insurance policyholder may be identified by analyzing past activity that the insurance policyholder has engaged in. A weighting may be assigned to the one or more identified items of interest based on the type of activity that the insurance policyholder has been engaged in. A plurality of natural language IVR menu options may be generated such that each IVR menu option corresponds to each of the one or more identified items of interest. The plurality of natural language IVR menu options may be provided to the insurance policyholder in an order that corresponds to the weighting of each identified item of interest corresponding to each of the plurality of natural language IVR menu options.

A device may receive real time audio data associated with a call between an agent and a customer, and may receive customer data identifying historical interactions with the customer. The device may receive chat data associated with the customer or interactive voice response (IVR) data associated with the customer, and may generate, based on the real time audio data, transcript data identifying a real time transcript of the call with the customer. The device may process the real time audio data, the customer data, the chat data or the IVR data, and the transcript data, with a machine learning model, to determine a customer intent and one or more actions to perform based on the customer intent; and may perform the one or more actions.