Provided is an agent robot control system comprising an acquisition unit which acquires a purchasing master list which shows a user's purchase merchandise candidates, and a control unit which generates a purchasing execution list for recommending, from the purchasing master list, purchases for select merchandise to be performed at real storefronts and for recommending purchases for other merchandise to be performed at online storefronts.

A computer-implemented method may include receiving customer information, the customer information including: at least one preference of a customer, the at least one preference including product identification information indicative of the at least one preference of the customer, and a loan prequalification of the customer. The method may also include receiving a request to provide the customer information to a merchant device, transmitting a communication to a merchant management system, the communication including an access code, and providing at least some of the customer information to the merchant device based on the access code received by the merchant device.

A system described herein may provide for the verification of payment information associated with a particular user request. The payment information may be verified by a third party and provide verification information to the call center processing the order request. Some information may be provided by the call center processing through the request by receiving information regarding the particular user from a repository.

Systems, methods, devices, and non-transitory processor readable media of the various embodiments enable in store voice picking systems. In various embodiments, an end-to-end voice ordering and fulfillment system for a retail store may enable a customer to place an order over the phone, a personal shopper to be directed to fill the order via voice commands, and the order to be made available for pickup at the retail store by the customer or delivered to the customer from the retail store.

A system for trading goods over a computer network based on image processing includes an image processor that analyzes a picture received from a user to build a description of entities in the picture and correlations among the entities, a description interpreter that analyzes the description to determine an underlying message in the picture and detect information regarding the user's interests, emotions and affinities to goods and services, wherein the information is stored with the user's profile, the user's list of items to trade, and the user's past transaction history, and a trade matching component that uses the user's profile and produces a ranked list of other users with items to trade, or intermediary trade steps, when another user initiates a new trading transaction.

A method and apparatus for a commerce platform coordinating a purchase of a product sold by a merchant system through a third party application are described. The method may include receiving a notification from the third party application requesting to purchase a product from within the third party application, wherein the notification comprises an identifier for the product and an identifier for the merchant system that sells the product. The method may also include a product checkout interface having an appearance consistent with an appearance of a user interface of the third party application, and transmitting the product checkout interface generated by the commerce platform to a user device executing the third party application causing the third party application to render the product checkout interface within at least a portion of the user interface of the third party application.

Methods, systems, and computer programs are presented for facilitating user engagement with a bot. One example method includes receiving, by a dialogue manager server, a sequence specification for a user activity that identifies a type of interaction between a user and a network service, the sequence specification including instructions for implementing a trigger action in the event of a negative user input into the bot. The negative user input in the sequence of interactions is detected and the trigger action is implemented in response to detecting the negative user input.

An agent selection component that selects and activates artificial agents for interacting with a user on behalf of various entity based on user interaction with a real environment. The agent selection component detects user interaction with the real environment, and evaluates the detected user interaction. Based on that evaluation, the agent selection component selects an artificial agent that acts for an entity from amongst multiple artificial agents that act for different entities (e.g., to answer questions, to place orders, to schedule, or the like). The agent selection component then causes the selected artificial agent to activate to interact with the entity. Thus, different interactions with a real environment may result in the agent selection component permitting the user to interface with artificial agents for different entities.

Samyata ecosystem provides a new and efficient retail commerce platform and ecosystem to bring stores, shoppers and personal shoppers together in a geographical area.

Systems and methods managing interaction between one of a plurality of advisors and a client. Client intent is determined based upon request details indicating a category of interest to the client. One of a plurality of advisors is selected to advise the client based, at least in part, upon the category and the client intent. The client is added to a sales pipeline of the selected advisor, and the selected advisor is prompted, at intervals, to interact with the client. The workload of each advisor is managed. The selected advisor is also prompted to generate and send a curation to the client. The systems and methods also provides e-commerce card fraud protection using conventional transaction processing methodology by including a random code in a pending transaction for the card and finalizing the transaction with the card provider when the code is correctly returned by the client.