A mechanism for providing electronic commerce data onto publisher's site. The mechanism also provides ability for a consumer to interact with that data to complete a purchase from within the publisher's website or application. A method includes retrieving merchandise data from a plurality of merchants and storing at least one group of merchandise data formed based on the merchandise data and content on a publisher site. The method also includes embedding the group of merchandise data on the content of the publisher's website and generating a merchandise frame in view of the embedment. The method further includes rendering the merchandise frame directly onto the publisher site. The method further includes rendering a universal check out frame on the publisher's site, which provides the user the ability to check out from multiple retailers within a single universal check out on a publisher's site.

A machine is configured to automatically order consumable items for an account. For example, the machine accesses image input associated with a consumable item. The image input is recorded by a camera associated with a client device. The machine identifies an account based on an identifier of the client device. The machine determines a level of consumption of the consumable item for the account based on the image input. The machine, based on the level of consumption, automatically places an order for the consumable item, for the account. The machine, in response to the automatic placing of the order, causes display of a notification describing the automatically placed order in a user interface of the client device. A selection of the notification describing the automatically placed order for the consumable item causes display of an automatically generated request to specify a schedule of future automatic orders for the consumable item.

The system and methods described herein allow users to apply for a purchase of a good from multiple providers using provider specific methodologies for generating offers for the product. For example, the system described herein may include a multi-layer architecture that includes interactive micro-services that communicate together in a bi-directional manner to create a normalized process for the purchase of a good, such as commercial goods/products (e.g. a vehicle) or real property. The micro-services may assess prequalification for a loan or financing for a good, followed by determining eligibility of the good for financing, and further followed by calculating pricing details for loans (e.g. for financing purchase of the good) that would be offered for a consumer's particular financial credentials, for each of a plurality of lenders. Prequalification and pricing may be performed on a good by good basis, or for a plurality of goods near or substantially simultaneously.

The system and methods described herein allow users to give their applicant information when seeking to submit an inquiry associated with a product provided by at least one entity, and have various lender microservices run in parallel, segregated by entity, in a jailed and self-contained, autonomous environment. The result of these microservices may be returned as a response to the inquity, being determined autonomously for each respective entity based on one or more respective rule sets or executable logic for each respective entity. Payloads for multiple entities may be combined in a single output from the jailed and self-contained environment due to outputs from the environment being encrypted in a universal format, wherein the outputs are decrypted in a user session in an application, allowing the user to see the results of the respective responses of each of the at least one entity, to their inquiry.

The information processing device 1X mainly includes an acquisition means 16Xa and a transition sequence determination means 16Xb. The acquisition means 16Xa acquires a first combination between sellers and buyers conducting transactions and a second combination between the sellers and the buyers differing from the first combination. The transition sequence determination means 16Xb determines a transition sequence of combinations between the sellers and the buyers, the transition sequence being generated in a process of making a transition, per basic operation for changing the combinations between the sellers and the buyers, from the first combination to the second combination, each combination of the transition sequence making a profit of a mediator equal to or larger than a threshold value, the mediator mediating the transactions.

Technologies are shown for automatic account generation for a transaction between two user devices. In accordance with some aspects, machine readable code is received at a first user device of a first user from a second user device of a second user. The machine readable code is associated with an item token for a transaction between the users. Responsive to receiving the machine readable code: an authentication token is received in response to authenticating the first user, and an account creation request that includes the item token and the authentication token is sent to an intermediary transaction service. The account creation request causes the intermediary transaction service: to generate a first account for the first user using information for the first user obtained using the authentication token, and to facilitate a transaction for the item between the first account and a second account of the second user.

An online concierge system uses a domain-adaptive suggestion module to score products that may be presented to a user as suggestions in response to a user's search query. The domain-adaptive suggestion module receives data that is relevant to scoring products as suggestions in response to a search query. The domain-adaptive suggestion module uses one or more domain-neutral representation models to generate a domain-neutral representation of the received data. The domain-neutral representation is a featurized representation of the received data that can be used by machine-learning models in the search domain or the suggestion domain. The domain-adaptive suggestion module then scores products by applying one or more machine-learning models to domain-neutral representations generated based on those products. By using domain-neutral representations, the domain-adaptive suggestion module can be trained based on training examples from a similar prediction task in a different domain.

A method of training a machine learning model to determine an item margin is provided. The method includes monitoring a first value for a first item having attributes and monitoring a first value for a second type of item having attributes where an attribute of the first attributes is the same as an attribute of the second attributes. The method also includes determining a first margin based on the first values. The first attributes, the second attributes, and the first margin are input as training data for the machine learning model where the machine learning model is trained with the training data. The monitoring operations for the first item and the second item are repeated to obtain a second value for the first and second items. Furthermore, the trained machine learning model is applied to the second values to determine a second margin.

A bidder buyers pool to reward bidders and owners of digital or physical assets in perpetuity through the blockchain is disclosed. A smart contract is created that takes a percentage of an auction sale price and splits that up among the bidders of an item, whether it be digital or physical. The split is determined by an algorithm that rewards bidders for higher bids. A method for conducting a transaction between an asset seller, an asset creator and one or more asset buyers is disclosed to accomplish this. The method includes providing a marketplace for the transaction to be conducted; listing on a marketplace, by the asset seller, an asset to be purchased by the asset buyers; iteratively soliciting offers from the asset buyers to purchase the asset until a pre-determined criterion is met to end the transaction; awarding the asset to a winning asset buyer of the one or more asset buyers who offered a highest offer amount for the asset at the end of the transaction; dividing up the highest offer amount among the asset seller, asset creator and the one or more asset buyers according to a pre-determined allocation process, where the asset seller receives a first amount, the asset creator receives a second amount, and the one or more asset buyers receive one or more allocated asset buyer amounts; and creating a smart contract among the one or more asset buyers, where the smart contract defines one or more conditions for ownership of the asset.

Some embodiments include apparatuses providing control over movement of motorized transport units at a retail facility, comprising: multiple self-propelled motorized transport units; a wireless communication network; and a central computer system, wherein the central computer system comprises: a transceiver; a control circuit; and a memory storing computer instructions that when executed cause the control circuit to: receive an override command, from a worker associated with the retail facility, to cause a first motorized transport unit of the multiple motorized transport units to implement one or more actions; confirm a valid authorization of the worker to override one or more operating limits of the first motorized transport unit; and override the one or more operating limits and communicate one or more instructions to the first motorized transport unit configured to cause the first motorized transport unit to implement the one or more actions in accordance with the override command.