Systems and methods are disclosed for providing a product to consumers by receiving the product from a manufacturer located in a first country; matching the products with a seller in the second country; managing delivery logistics by matching available third-party truckers and third-party warehouses in a second country based on proximity; forecasting demand using one or more neural networks for the manufacturer, the logistics organization, and the warehouses; and managing logistics for the manufacturer through a dashboard populated by the forecasted demand from the one or more neural networks.

In an approach, a processor receives a request to purchase an item from a retailer, where the request includes a location. A processor receives a request to purchase an item from a retailer, where the request includes location information associated with a buyer. A processor identifies that the item is unavailable from the retailer. A processor determines a plurality of users predicted to have a surplus quantity of the item beyond each respective user's estimated needs at a time of the request. A processor sends an offer to the plurality of users to transfer the item in accordance with the request. A processor, responsive to receiving an acceptance of the offer, selects at least one accepting user, of the plurality of users, based on geographic proximity to the location information. A processor coordinates fulfillment of the request by the at least one user.

The present invention relates to a system (100) and a method of a common market place for technology creators. The system (100) of the present invention includes a technology creator computing device (102), an enterprise buyer computing device (104), an expert agent computing device (106), and a cloud server (108). The cloud server (108) executes computer-readable instruction that provides a common digital platform for the technology creators, the enterprise buyers, and the expert agents to interact with each through the technology creator computing device (102), the enterprise buyer computing device (104) and the expert agent computing device (106) respectively. Further, the technology creators, the enterprise buyers and the expert agents create their profile on the common digital. Herein, the cloud server (108) executes computer-readable instructions to help the technology creators to search for the enterprise buyers and the expert agents based on the technology set of the technology creators.

In an assisted living platform, users are provided with a dashboard for capturing their personal details, preferences and service needs, and service providers can provide details about themselves and the services they are able to provide.

In accordance with the present invention, an information management application that provides users with the ability to create and customize matrix displays of information relating to a particular product or service for navigation by other users is provided.

A system for providing and sourcing local groceries is disclosed, comprising a provider database storing provider information, a product database storing product information, and a consumer database storing consumer information. A user interface module displays the provider information, the product information, and the consumer information on the display of a computing device. A search engine permits the consumer to input search parameters, wherein the user interface module displays a plurality of search results corresponding to the search parameters.

A process for selecting and efficient retailer to purchase goods, such as groceries, includes generating a list of multiple items to be purchased from any of several optional retailers. The system gathers publicly available pricing information to calculate the total cost to purchase all goods at each of the selected retailers. The system allows the user to compare the total cost of purchasing all the goods out any individual retailer with the location of that retailer. The shopper can then elect to shop a particular retailer based on the convenience of their location and the cost to by all items on the list. This takes into account the value of the shoppers the time as well as the cost of the individual items purchased.

Systems and methods including one or more processing modules and one or more non-transitory storage modules storing computing instructions configured to run on the one or more processing modules and perform acts of determining a prospective product for a user to add to an cart, identifying a prospective cart merchant group that includes prospective merchants that offer the prospective product, determining a prospectively-unlocked product group that includes a plurality of products offered by the prospective merchants that are discounted if the prospective product is added to the electronic cart, determining a savings score for the prospectively-unlocked product group, and coordinating displaying to the user on the website of the online retailer (1) the prospective product and (2) the savings score of the prospectively-unlocked product group.

Systems and methods are described for playing a game using a gestural gaming device. In an embodiment, the gestural gaming device includes a processor, a sensor, a communications transceiver, and a plurality of lighting elements. An application may be executed on a mobile device in communication with the gestural gaming device via the communications transceiver. The system may also include a back-end server in communication with the application over a network. The game may be played using the gestural gaming device in conjunction with one or more gestures, the game being managed by the application using the plurality of lighting elements. A winner of the game may be awarded a reward in response to winning the game from the back-end server via the gestural gaming device.

Examples of the disclosure provide a system and method for entity-specific value optimization. An elasticity estimation module receives a data request for an item associated with an individual entity, and identifies a value response curve for the item associated with the individual entity. The elasticity estimation module determines an elasticity measure for the item associated with the individual entity. A value optimization module dynamically adjusts the identified value response curve for the item associated with the individual entity as new data corresponding to the item and the individual entity is received, and generates a value optimization recommendation based on the dynamic adjustment.