Asapp, Inc.

Gustavo Sapoznik

Shawn Henry

Joseph Ellsworth Hackman

Vicky Sehrawat

Jason Shaev

Hui Dai

Punyashloka Biswal

Brian Dillmann

Rachel Knaster

Shang Wei Wang

A third-party service may be used to assist entities in responding to requests of users by determining a suggested response to a received communication. The third party service may receive a request from a first entity, such as via an application programming interface request, that includes a message in a conversation. A conversation feature vector may be computed by processing the message with a first neural network. A suggested respond to the message may be determined by processing the conversation feature vector with a second neural network. The third-party service may then return the suggested response for use in the conversation. The third-party service may similarly be used to assist other entities in responding to requests of users.

Third-party service for suggesting a response to a received message

An intent classifier may be used to increase the efficiency of a communications system. A company may provide assistance to a first user using automated processing or by a second user manually responding to the first user. To reduce costs, the company may prefer to use automated processing for assistance where it is available. While a second user is assisting a user, a message from the first user may be processed with an intent classifier to determine that automated support is available to assist the first user, and a suggestion may be presented to the second user to transfer the first user to the automated processing, such as by presenting a button to the second user to transfer the first user to the automated processing. The second user may then transfer the first user to the automated processing and assist other users.

Automating communications using an intent classifier

The third-party company may provide a user interface to a customer to submit a customer support request regarding a first company. The third-party company may receive a customer identifier from the first device and may request prediction data from the first company using the customer identifier. The third-party company may process the prediction data to predict a customer support request of the customer and generate user interface data corresponding to the predicted customer support request. The user interface data may be transmitted to the user interface before a customer support request from the customer is received.

Predicting customer support requests

A user may respond to a request of another user by entering text, such as a customer service representative responding to a customer. As the user enters text, a suggested completion of the text may be suggested to the user so that the user may select the suggested completion instead of continuing to enter text. Previous messages between the two users and other information may be used to determine an appropriate suggested completion to the entered text. A neural network language model and a search graph may be used to select a suggested completion from a search graph of possible suggested completions.

Automatically suggesting completions of text

A third-party service may be used to assist entities in responding to requests of users. A third-party service may receive, directly or indirectly, a request of a first user for assistance from a first entity. The third-party service may request information about the first user by sending a request to a computer of the first entity. The third-party service may use the request of the first user and the information about the first user to automatically generate a response to the request of the first user. The third-party service may then transmit, directly or indirectly, the response to the first user.

Assisting entities in responding to a request of a user

A third-party company may assist other companies in providing customer support to their customers. The third-party company may provide software to a computer of a customer service representative to present a user interface to assist the customer service representative in responding to customer requests. Third-party company may also send update data to the computer of the customer service representative to cause a portion of the user interface to be updated, where the update data is determined using an intent of a message received from a customer. A message received from the customer may be processed to determine the intent of the message, a template may be obtained using the intent, and the update data may be generated by rendering the selected template. The update data may then be transmitted to the computer of the customer service representative to cause a portion of the user interface to be updated.

Using semantic processing for customer support

A user may respond to a request of another user by entering text, such as a customer service representative responding to a customer. Suggestions of resources may be provided to the responding user to assist the responding user in providing a response. For example, a resource may provide information to the responding user or allow the responding user to perform an action. Previous messages between the two users and other information may be used to select a resource. A conversation feature vector may be determined from previous messages, and feature vectors may be determined from the resources. The conversation feature vector and the feature vectors determined from the resource may be used to select a resource to suggest to the responding user.

Automatically suggesting resources for responding to a request

A user may respond to a request of another user by entering text, such as a customer service representative responding to a customer. As the responding user enters text, a completion of the text may be suggested to the responding user so that the responding user may select the completion instead of continuing to enter text. Previous messages between the two users and other information may be used to determine an appropriate completion to the entered text. A topic vector may be determined from previous messages, and a feature vector may be determined from the entered text. The topic vector and the feature vector may be used to identify characters that may follow the entered text.

A user may respond to a request of another user by entering text, such as a customer service representative responding to a customer. Suggestions of responses may be provided to the responding user so that the responding user may use a suggested response instead of entering text to provide a response. Previous messages between the two users and other information may be used to determine an appropriate suggested response. A conversation feature vector may be determined from previous messages, and response feature vectors may be determined from the conversation feature vector. The response feature vectors may be used to determine an appropriate suggested response.

Automatically suggesting responses to a received message

A user may request assistance or information using natural language, such as by speaking or entering a text. A response may be automatically determined to the request of the user be performing semantic processing to understand the request and formulate an appropriate response. A response may be automatically determined, be computing features from the request, using the features to select a node of a graph corresponding to the request, and then causing an action to be performed to provide a response to the user. For example, the action may include providing information to the user, requesting further information from the user, or connecting the user with a customer service representative.

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Miami, FL, United States of America

Gustavo Sapoznik