Abstract: 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.

Abstract: A pharmacy order facilitation method includes receiving a message; training a machine learning model; generating an intent; generating a response message; and transmitting the response message. A computing system includes a processor and a memory storing instructions that, when executed by the one or more processors, cause the computing system to: receive a message; train a machine learning model; generate an intent; generate a response message; and transmit the response message. A computing system includes a mobile device; a server device configured to: train a machine learning model; analyze the inbound message; identify a customer intent; perform an action based on the customer intent; and transmit an outbound message.

Abstract: Techniques for fully or comprehensively resolving relationships within and among different data sets are disclosed. The techniques evaluate identification tags of respective transaction records to resolve transitive relationships between and among the identification tags, which vary across the different data sets. Based on this resolving, the techniques comprehensively sort the identification tags into mutually exclusive sets of related identification tags. Additionally, the techniques resolve and sort identification tags that are transitively unrelated to every other identification tag. At least these features enable comprehensive identification and intelligent sorting of related/unrelated transaction records, provide enhanced transaction tracking and security, more efficient and accurate transaction record storage (and in particular, of composite records), and enhanced tracking accuracy of accounts or types of units) as compared to known techniques.

Abstract: A method includes receiving a file, storing the file, generating a tag, receiving a scan of the tag, receiving a selection to retrieve the file, executing a tag recognition routine; and executing a content routine to present the file. A non-transitory computer readable medium includes containing program instructions that when executed, cause a server to receive a file, store the file, generate a tag, receive a scan of the tag, receive a selection to retrieve the file, execute a tag recognition routine; and execute a content routine to present the file. A system includes a processor, a printer device, and a memory including instructions that when executed cause the system to receive a file, store the file, generate a tag, receive a scan of the tag, receive a selection to retrieve the files, execute a tag recognition routine; and execute a content routine to present the file.

Abstract: 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.

Abstract: Methods and systems may incorporate voice interaction and other audio interaction to facilitate access to prescription related information and processes. Particularly, voice/audio interactions may be utilized to achieve authentication to access prescription-related information and action capabilities. Additionally, voice/audio interactions may be utilized in performance of processes such as obtaining prescription refills and receiving reminders to consume prescription products.

Abstract: Methods and systems may incorporate voice interaction and other audio interaction to facilitate access to prescription related information and processes. Particularly, voice/audio interactions may be utilized to achieve authentication to access prescription-related information and action capabilities. Additionally, voice/audio interactions may be utilized in performance of processes such as obtaining prescription refills and receiving reminders to consume prescription products.

Abstract: Systems and methods may be provided that may enable an individual to retrieve one or more prescription products (e.g., product refills) from a self-service retrieval location such as a counter, drive-thru, drop box, or kiosk. A unique-machine readable code may be associated with a particular one or more prescription products (e.g., associated with a medical prescription of a patient). The unique machine-readable code may be provided to a computing device of the individual, along with an anticipated time of preparedness of the one or more products for retrieval at the retrieval location. Identification of the unique machine-readable code may result in dispensing of the one or more prescription products associated at the retrieval location.

Abstract: A system to verify the identity of a recipient requesting fulfillment of a prescription for a pharmaceutical product includes a point-of-sale retail personal identification number entry device (pinpad) and a workstation that stop a transaction for the pharmaceutical product from proceeding in response to a request associated with a claim for dispensing the pharmaceutical product. A first input for data identifying a member of a rewards program is entered with the pinpad, and a second input for data identifying a recipient of the prescription is entered with the workstation. The workstation compares the data identifying the member of the rewards program against the data identifying the recipient of the prescription. If there is a match between the data identifying the member of the rewards program and the data identifying the recipient of the prescription, the pinpad and workstation allow the transaction for the pharmaceutical product to proceed.

Abstract: Example methods, apparatus, and articles of manufacture to estimate costs of prescriptions are disclosed herein. An example computer-implemented method, executed by a processor, to estimate a cost of a prescription for a medication includes receiving, with a processor, a prescription for a medication for a patient, receiving, with the processor from an entity, a request for an estimated cost for the prescription, processing, with a machine learning model, the prescription to determine the estimated cost of the medication for the patient, and providing, with the processor, the estimated cost to the entity.

Abstract: The present disclosure generally relates to reusable containers having a locking feature and geographic location tracking capabilities. In particular, the present disclosure relates reusable containers having a locking feature and geographic location tracking capabilities for autonomous delivery of goods.

Abstract: Security flaps for use with cash trays and cash trays including such security flaps are disclosed. An apparatus includes a cash tray having a base and a plurality of walls that extend from the base and define a plurality of paper-currency compartments. A plurality of distal edges of the walls define openings of the paper-currency compartments. A spring-biased security flap is coupled to the cash tray and adapted to engage or be immediately adjacent the distal edges of the walls of at least one of the paper-currency compartments to cover the corresponding opening.

Abstract: Systems and methods are provided for identifying and communicating with a user through the user's mobile device. One example method includes receiving, from the mobile device, a user identifier associated with the user and an entity identifier associated with an entity location, the entity identifier being obtained by the mobile device from a wireless transmitter located adjacent to an entrance of the entity location; retrieving user profile data associated with the user identifier from a user database, the user profile data including a user qualifier; providing the user profile data to a display device at the entity location, the display device configured to display the user profile data, including the user qualifier; and sending at least one notification to the mobile device for display thereon, the at least one notification comprising at least one of information related to the entity location and a portion of the user profile data.

Abstract: A computer-implemented method includes downloading respective instances of an enterprise mobile application to a plurality of mobile devices. The instances of the enterprise mobile applications, while executing on respective mobile devices, capture, for each session, a session log that includes indications of ordered user actions occurring during the session, and optionally time intervals between user actions and/or user attributes. Captured session logs stored at and are mined by one or more servers to discover a particular pattern or sequence of user actions that occurred across multiple, different user sessions. If the number and/or rate of occurrences of the particular pattern is greater than a threshold, a new test case corresponding to the pattern is automatically generated and added to a suite of test cases for the UI functionality of the enterprise mobile application. The updated test suite may be automatically executed on a test version of the enterprise mobile application.

Abstract: Systems and methods for product imaging and provisioning include a mobile application (app) installed on an imaging device, where the mobile app activates the imaging device to generate an image of a product tag associated with an unavailable product at a first location. The mobile app determines, based on the image, a product indicator associated with the unavailable product. A provisioning app, executing on a remote device, receives the product indicator associated with the unavailable product. The provisioning app also receives a user indicator associated with a first user and executes one or more product provisioning rules that determine, based on a product availability database and the user indicator, an availability result. The availability result indicates whether the unavailable product will be available to the first user. The provisioning app is further operable to send the availability result to the imaging device for presentation by the imaging device.

Abstract: 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.

Abstract: Systems and methods for using machine learning models to predict risks posed to patients having various respiratory conditions. According to certain aspects, an electronic device may generate a machine learning model using training data indicating various patient and medication data. The electronic device may access a set of real-world patient data and input the real-world patient data into the machine learning model. An output of the machine learning model may indicate a likelihood of the patients needing intervention care, and the electronic device may facilitate outreach efforts to certain patients in an attempt to decrease this likelihood.

Abstract: The following relates generally to facilitating delivery of prescription medication. In some embodiments, a pharmacy computer system: (i) receives a prescription, (ii) reviews the prescription, and (iii) sends the prescription to an intermediate cloud layer. The intermediate cloud layer may then determine a warehouse to send the prescription to based on at least one criteria. The at least one criteria may comprise at least one of: (i) a health insurance plan; (ii) whether the medication comprises a controlled substance; (iii) whether the medication must be refrigerated during shipping; (iv) a warehouse shipping address; or (v) a fulfillment cap of a warehouse.

Abstract: A method and system may provide an automated pharmacy processing system which automatically processes an electronic prescription by converting the electronic prescription into a pharmacy prescription record. In this way, an electronic prescription can be filled by a pharmacist without manual data entry. The systems, methods, and apparatuses may generate confirmation and verification requests based on electronic prescription data.

Abstract: An offer decay generation model determines, for a particular customer, a personalized optimal offer decay curve of an incentive corresponding to a product provided by an enterprise, where the offer decay curve defines a set of decreasing incentive values and respective time intervals during which each incentive value is valid. The offer decay generation model is trained on historical data indicative of customers, customer interactions, offered incentives, resulting outcomes of the incentives, and time intervals elapsing between incentives and resulting outcomes. As such, the optimized offer decay curve is structured to maximize a probability that the particular customer is motivated to accept the incentive offer, purchase a product, and/or further interact with the enterprise during the lifetime of the offer decay curve. The offer decay curve may unique to the individual customer, and may be further customized based on other parameters such as location, time/day/date, inventories, etc.