An ambient listening system, includes: an ambient device configure to listen to a conversation between a customer and a sales agent regarding at least one of a desired service and a desired product, and generate an audio stream of the conversation and a unique identifier for the customer; a voice biometrics service module configure to perform at least one of i) identification of the customer based on the audio stream, and ii) voiceprint enrollment of the customer's voice based on the audio stream and the unique identifier for the customer; a business logic module configured to generate at least one business logic output based on at least one of customer's intent and entity extracted from the audio stream; and an automation platform configured to automate, based on the business logic output, the sales agent's workflow related to at least one of customer record, the desired service and the desired product.

The invention relates to a method, a system, a computer program product and a service for providing up-to-date and verified information of a label product-specific sustainability indicator. The method comprises receiving a first input data (102, 202, 302) including internal information on the label product, receiving a second input data (104, 204, 304) including external information on raw material(s) used for the label product, processing at least the first input data (102, 202, 302) according to a life cycle assessment method in order to produce a label product-specific life cycle parameter, transmitting at least the second input data (104, 204, 304) to an external verification body (106, 306) for processing, receiving a label product-specific sustainability parameter as a response from the external verification body (106, 306), providing a label product-specific sustainability indicator (108) comprising the label product-specific life cycle parameter and the label product-specific sustainability parameter, and associating the label product-specific sustainability indicator (108) for the label product.

Aspects described herein may allow for generating a customized price rating using a machine learning algorithm. This may have the effect of improving the display of information about merchants by including customized, personalized price ratings that better reflect the tastes and preferences of a user or group of users. According to some aspects, these and other benefits may be achieved by using a machine learning model, trained to receive input corresponding to both user data and merchant data and output an indication of a customized price rating for the merchant that is specific to the user, and then to generate information about the merchant for display that includes the customized price rating.

An online system provides options for selection by a user. The online system receives a query entered on a client device. The online system queries an item database to retrieve a set of items related to the query and assigns each item to a product category in a predefined taxonomy that maps items to product categories. The online system inputs each item into a prediction model trained to predict a probability that an item is available at a warehouse location. The online system determines that a first product category has low availability based on predicted probabilities for items in the first product category. Responsive to determining that a first product category has low availability, the online system generates a generic item for the first product category and sends a list of items including the generic item to the client device for display responsive to the query.

A computer-implemented method for providing a user interface to a user includes receiving wearable article data describing wearable articles for physical shipment to users via electronic interactions; generating a user interface for an electronic transactions platform based at least on the received wearable article data; causing display of the user interface depicting one or more of the wearable articles; receiving a selection of a wearable article of the displayed one or more wearable articles via the user interface; determining a condition of the selected wearable article at least based on the received wearable article data in response to the selection; reserving the selected wearable article for a predetermined period of time in response to the selection; updating and causing display of the user interface depicting the selected wearable article and the determined condition; and determining whether the selected wearable article is purchased or borrowed during the predetermined period of time.

Various embodiments relate generally to computer science, data science, software, and computer program and platform architectures, including receiving from a device geolocation data and input data, parsing the input data, evaluating the event data and the location data to generate shipment data, parsing the account to identify subscription data, selecting a sample associated with another item, the sample being selected by an adaptive distribution platform, transmitting other data to the device that renders an electronically-displayed message on an interface on the device, calling one or more data services to retrieve item data associated with the item, and generating a retrieval option associated with the item if the threshold, the query, and the additional input data indicates the device is within a numerical range of the first location or an alternative location and retrieval of the item from the first location is indicated.

Disclosed are methods, systems, and non-transitory computer-readable medium for dynamically assorting merchandise. For example, a method may include receiving or generating a plurality of cells defined by one or more dimensions, receiving a total number of resources for allocation to the plurality of cells, allocating the total number of resources among the plurality of cells, determining one or more stock keeping units for each cell, determining a quantity of each of the one or more stock keeping units in each cell, assigning one or more launch dates for each of the one or more stock keeping units for each cell, and stocking the one or more inventories with one or more articles corresponding to the stock keeping units in each cell, based on the determined quantity and the assigned one or more launch dates of each of the stock keeping units in each cell.

A system and method for providing payments is disclosed. A method can include establishing a wireless link between a mobile device and a merchant device. After an instruction is displayed on the mobile device, a combination of a first type of input and a second type of input are received on the mobile device, first type of input including at least one button press of a physical button and the second type of input received from a user to confirm a payment for the purchase. Based on the inputs, payment data is retrieved from a memory of the mobile device. The method includes receiving the payment data at the merchant device to make the purchase, wherein receiving the payment data, via the wireless link, at the merchant device to make the purchase is performed according to a protocol for communicating the payment data to the merchant device.

A computerized system is provided for facilitating direct communication between a real estate agent who has listed a property for sale and a potential real estate buyer. The system allows a user to receive the listing agent contact information within the user interface of the computerized system, thereby streamlining the user interface experience and keeping the user engaged with the online platform.

Techniques are provided for identifying objects (such as products within a physical store) within a captured video scene and indicating which of object in the captured scene matches a desired object requested by a user. The matching object is then displayed in an accentuated manner to the user in real-time (via augmented reality). Object identification is carried out via a multimodal methodology. Objects within the captured video scene are identified using a neural network trained to identify different types of objects. The identified objects can then be compared against a database of pre-stored images of the desired product to determine if a close match is found. Additionally, text on the identified objects is analyzed and compared to the text of the desired object. Based on either or both identification methods, the desired object is indicated to the user on their display, via an augmented reality graphic.