Walgreen Company

Oliver Derza

Adam Robert Snopek

Renata Lurye

Based on a detection that a customer has arrived at an enterprise location to pick up a previously-placed order, an intelligent automated customer dialogue system generates an interface via which an intelligent customer dialogue application dialogues with the customer. The application generates and initially offers, at the interface using natural language, content which is contextual to one or more items of the order, e.g., by using a specially trained intelligent dialogue machine learning model. The application may intelligently respond to the customer's natural language responses and/or requests to refine, augment, or redirect subsequently-offered content and/or dialogue, e.g., by using the model. Offered content (e.g., product information, services, coupons, suggestions, recommendations, etc.) generally provides value-add to the customer as well as maintains customer engagement. The system may be implemented at least partially by using a chatbot upon curbside pick-up, for example, as well as through other electronic customer facing channels.

Intelligent automated order-based customer dialogue system

Techniques for automatically initializing customer assistance in a retail store based on video analysis are provided. An exemplary method includes retrieving video data from a database and extracting one or more features from the video data. The method also includes identifying a product is missing on a store shelf based on the one or more features. The method includes training an artificial intelligence model using the one or more features to identify a customer needs assistance, and applying the trained artificial intelligence model to predict a customer needs assistance at a particular location in the store. The method includes sending a notification to a computing device of a customer service representative, wherein the notification identifies the customer, the customer's location, and information about the missing product.

Automatic initialization of customer assistance based on computer vision analysis

Methods and systems may support dynamic, real-time or near-real-time processing, analysis, and processing of data to automatically identify and obtain coupons corresponding to consumer products such that, in response to receiving a request to purchase one or more products, qualifying coupons may be automatically identified, retrieved, and applied to the purchase.

Systems and methods for autonomous management of manufacturer coupons

To extract information from a customer's insurance card, an insurance policy recordation system obtains a scanned image of an insurance card and analyzes text in the insurance card image to identify labels describing insurance policy characteristics and insurance policy values corresponding to the insurance policy characteristics. The insurance policy recordation system compares the identified insurance policy values to a set of stored identifiers associated with various insurance plans. If the insurance policy values match one or more of the identifiers, the insurance policy recordation system may determine that the insurance policy values are valid and that the customer has the matching insurance plan. The insurance policy recordation system may obtain additional insurance policy information for the customer based on the stored information in association with the matching insurance plan. Then the insurance policy recordation system may update the customer's record with the insurance policy values and/or additional insurance policy information.

Systems and methods for automatic recording of insurance card information

Methods and systems disclosed herein can assess electronic messages exchanged between messaging applications, by receiving a first version of an electronic message generated by a messaging application for review by an automated agent messaging application prior to delivery of the electronic message to an electronic device operated by a customer, the electronic message having textual content intended for the customer from an agent associated with the enterprise; automatically generating, by the automated agent messaging application, a second version of the electronic message using one or more machine learning-based models, wherein the second version of the electronic message is an adaptation of the textual content of the first version of the electronic message while maintaining an intent of the first version of the electronic message; and transmitting, to a computing device via a network, the second version of the electronic message.

Automated agent messaging system

A pharmacy management system includes a processor and a memory storing instructions that, when executed by processor, cause the pharmacy management system to train a machine learning model; receive a sig code utterance; analyze the sig code utterance using the trained machine learning model; and generate an output. A computer-implemented method includes training a machine learning model; receiving a sig code utterance; analyzing the sig code utterance using the trained machine learning model; and generating an output. A non-transitory computer readable medium includes program instructions that when executed, cause a computer to train a machine learning model; receive a sig code utterance; analyze the sig code utterance using the trained machine learning model; and generate an output.

Automated SIG code translation using machine learning

Techniques for automatically initializing customer assistance in a retail store based on video analysis are provided. An exemplary method includes collecting training data including historical video data and training a computer vision model using the training data to identify at least one customer movement associated with customers in need of assistance. The method also includes receiving video data of a customer in a retail store, the video data captured by a camera, and applying the computer vision model to the video data to determine whether the customer has performed the at least one customer movement. The method still further includes, in response to determining that the customer has performed the at least one customer movement, determining the customer is in need of assistance and engaging the customer using at least one computing device.

A pharmacy management system for automated sig code translation using machine learning includes a processor and a memory storing instructions that, when executed by the one or more processors, cause the pharmacy management system to train a machine learning model to analyze sig codes, receive a sig code, analyze the sig code utterance and generate an output corresponding to the sig code utterance. A computer-implemented method includes training a machine learning model to analyze sig codes, receiving a sig code, analyzing the sig code utterance, and generating an output corresponding to the sig code utterance. A non-transitory computer readable medium containing program instructions that when executed, cause a computer to: train a machine learning model to analyze sig codes, receive a sig code, analyze the sig code utterance, and generate an output corresponding to the sig code utterance.

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Willowbrook, IL, United States of America

Oliver Derza