Abstract: In one aspect, In one aspect, a computerized method of an automated invoice management and analysis comprising with an invoice management system, receiving a purchase order or invoice in any digital image format. The method includes using an optical character recognition system to extract plain text the from the purchase order or invoice. The method includes parsing and formatting the plain text data with a machine learning system into a specified consistent format. The method includes communicating the formatted plain text data to a third-party service to complete a specified transaction.

Abstract: In an aspect a computer-implemented method is described. The method may include: causing a point-of-sale terminal processing a transaction to display a machine-readable code, the machine-readable code encoding a web address; receiving a request from a device that scanned the machine-readable code, the request received at the web address and the request including data; determining, based on data encoded in the machine-readable code and data included in the request, that the transaction may be processed using a value-added service; and in response to determining that the transaction may be processed using the value-added service, enabling completion of the transaction using the value-added service.

Abstract: Systems and methods of constructing and managing virtual planograms are presented. Contemplated systems allow for construction of a virtual planogram, which can be used to present consumers virtual inventory items as being available for purchase via a display device. The display device can include an electronic billboard within an establishment, a mall for example, or include a user's smart device, a cell phone or tablet for example.

Abstract: Various examples are directed to systems and methods for processing offline payments from a mobile wallet. A computing system may receive, from a financial institution system, an authentication request message comprising a first offline token. The computing system may determine that the mobile wallet application is not online and determine that the first offline toke comprises first offline token data that matches the first offline token reference data. The computing system may send to the financial institution system a first authentication message indicating that the first offline token is associated with the mobile wallet application.

Abstract: Systems and methods for dynamic creation of virtual-cart enabled purchasing in an in-store environment and automated product recommendation are disclosed herein. Virtual cart enabled purchasing can include receiving a user identifier and creating a mirror-cart linked with the received user identifier. An entry in the mirror-cart can be generated corresponding to a physical item selected for purchase by the user, and an invoice including pricing information for to items in the virtual-cart can be generated. A request for the invoice can be received, and the invoice can be transferred to the point of sale terminal. A payment confirmation can be received indicating completion of transacting of payment for the items in the virtual-cart and tracked in the invoice.

Abstract: Disclosed is an example approach in which news alerts are scanned in real-time or near real-time, relevant alerts identified through a topic extraction model, and associated actors identified through an entity extraction model. An entity resolution model may be applied to determine which actors are clients. The topic extraction, entity extraction, and/or entity resolution models may apply, for example, natural language processing models. The alert may be enriched by being packaged with client and transactional data to generate an enriched alert. A predictive model may be applied to the enriched alert to identify events with a high probability of law enforcement referral, and the enriched alert may be automatically transmitted to certain identified devices. The predictive model is trained using a combination of news alerts and data on clients and transactions, yielding enhanced predictions.

Abstract: A computer-implemented method for predicting interchange charges includes: retrieving a historical transactions set, where each completed transaction in the set includes transaction features, a bank identification number (BIN), and a corresponding true interchange code; transforming all BINs in the set into a corresponding plurality of BIN features that comprise probabilities; creating a first training set including all transaction features, all pluralities of BIN features, and all true interchange codes associated with the historical transactions set; training a random forest model using the first training set and generating a second training set including rounded BIN features, rounded transaction features, discrete ones of the transaction features, and the true interchange codes; training the random forest model using the second training set to generate a trained random forest model for prediction of the interchange codes; and executing the trained random forest model for new transactions to generate corres

Abstract: A system for processing a transaction by a user at a transaction point comprising: a data processing module configured to generate a transaction signal when an initiation of the transaction at a POST device of a transaction point by the user using a transaction initiator is detected, wherein the transaction signal comprises a transaction data; a data delivery module configured to transmit the transaction data from the POS device to a remote processor and optionally to a secondary computer based device of the user; a tagging module configured to enable the user to tag the transaction data when a prompt is displayed on the hand held computer based device; and a report generation module configured to generate a report corresponding to any client selected by the user through the hand held computer based device of the user.

Abstract: Systems and methods presented herein provide a server that receives a drawing. The server matches assembly types to elements in the drawing and inserts a symbol overlay into the drawing. The symbol overlay includes metadata identifying the assembly types in the drawing. The assembly types are matched to assemblies, including kits, based on user-identified criteria, such as vendor and building codes. The system can then determine logistics for delivering the kits, automatically staggering shipment where dictated by build order of the kits.

Abstract: An out-of-stock indicator is received that indicates a product is out-of-stock or believed to be out-of-stock. Information about the features of the products and store are obtained or determined. The features are applied to a first machine learning model, which yields a probability that the item is out-of-stock. The obtained probability is compared to a threshold, and if the probability value is above a threshold, then the PI value is adjusted. If not above the threshold, then scans are monitored for out-of-stock conditions, and some time later the features will be applied to a different model, and the above-process repeated. In aspects, this process occurs over a certain time period or until the PI is adjusted.

Abstract: A system and method for sensor-enabled automated inventory stocking management that can include: operating a computer vision monitoring system comprising collecting image data, and identifying, by processing the image data, products and shelf space locations of the products; maintaining a shelving property map based on the products and shelf space locations identified through the computer vision monitoring system; in association with at least one request, allocating a shelf space usage option within a shelf space management database system, wherein each shelf space usage option specifies fulfillment parameters including at least one product identity and a set of shelf space placement parameters; confirming, based on processing of updated image data from the computer vision monitoring system, fulfillment of conditions defined through the fulfillment parameters of the a shelf space usage option and, in response, performing reactionary actions in the computing system.

Abstract: A boarding pass can be employed as a financial instrument to make payments and other financial transactions. A passenger name record, a standardized computer reservation system protocol, can be associated with one or more financial accounts. When a point of sale device scans the boarding pass, either on a mobile device, or a traditional paper boarding pass, the passenger name record can be used to find a travel itinerary associated with the customer. By matching the travel itinerary to the location of the point of sale device, and the time, payments can be authorized and then initiated using financial account information associated with the passenger name record. Likewise, a mismatch can provide a basis for denying authorization and subsequent payment.

Abstract: Aspects of the technology provide systems, devices and methods for filling design voids within an assembled electronic device with tamper solids in order to prevent and/or detect a tampering with the electronic device to gain unauthorized access to the electronic device to steal information.

Abstract: Systems and methods of managing payments for services or products are disclosed. Billing system data is extracted or accessed to provide business intelligence and. Visit charges from multiple billing systems can be aggregated to guarantor accounts within or across multiple billing systems and provide a single statement of charges for a given time period. Accounts are accessible online. Accounts can be linked to delegate management authority of a first guarantor's account to a second (manager) guarantor. Visit charges for linked accounts are included in the manager guarantor's statement an online access. Open charges balances can be brokered or transferred to a new asset holder. Pre-determined payment options can be configured by a provider, asset holder, and/or potential asset holder. The pre-determined payment options can include an option for financing a balance. A configurable financing option may enable a guarantor to request terms and receive automatic approval, subject to authorized terms.

Abstract: Methods, apparatuses, and systems associated with inventory management are described. Examples can include receiving at a processor first signaling from a first sensor device configured to monitor the interior of a first enclosure and receiving at the processor second signaling from a second sensor device configured to monitor the interior of a second enclosure. Examples can include writing from the processor to a storage device coupled to the processor data that is based at least in part on a combination of the first and second signaling, identifying a quantity or amount of at least one item in the first enclosure and at least one item in the second enclosure, and transmitting third signaling when the quantity or amount of the at least one item in the first enclosure or the at least one item in the second enclosure is less than a threshold value.

Abstract: Electronic transaction data and/or electronic payment data therefor is routed to disparate payment networks for a multitude of transactions. A software-programmed computer type circuit receives and processes point-of-sale transaction data to select two disparate payment networks for processing electronic payment for the transaction data. Transaction and/or payment data is routed to each of the disparate payment networks, to respectively debit and credit payment accounts, to provide payment to a seller on behalf of a buyer involved in the transaction.

Abstract: A beverage operations control system of an establishment such as a bar communicates with numerous wireless beverage control devices that monitor and control the pouring of beverages. The system provides monitoring and predictive analysis based on the monitoring, including real-time modifications to the operations of the beverage control devices.

Abstract: In one embodiment a method includes storing in non-volatile memory a library of equipment configuration code files, each equipment configuration code file including configuration code for configuration and control of a work vehicle, for configuration and control of an attachment to be carried or towed by the work vehicle, or for combined configuration and control of both the work vehicle and the attachment in combination, receiving an altered version of at least one equipment configuration code file, the altered version including OEM data provided by or altered by an original equipment manufacturer of the work vehicle or the attachment, dealer or distributor data provided by or altered by a dealer or distributor of the work vehicle or the attachment, and user data provided by or altered by a user of the work vehicle or attachment, and storing the altered version in the non-volatile memory of the library.

Abstract: A system and method for automated machine learning supply chain planning having a computer with a processor and memory and configured to receive a first supply chain network model having one or more material constraints for operations of a first supply chain network. Embodiments include transforming the first supply chain network model into a digital image, training an auto-encoder model to reduce the dimensionality of an input vector, and locating one or more items in the first supply chain network.

Abstract: A system and method are disclosed to train machine learning models, generate software agents, and evaluate, via reinforcement learning, the actions of the software agents in a simulated ecosystem. Embodiments include a computer comprising a processor and memory and configured to train one or more machine learning models to generate one or more software agents, wherein each software agent comprises an autonomous software program designed to execute a task in a supply chain network. Embodiments generate a first software agent and a second software agent, and a simulated supply chain ecosystem representing a hierarchical structure of supply chain network tasks. Embodiments simulate one or more tasks executed by the software agents in the simulated supply chain ecosystem, review the tasks according to one or more defined objectives, and apply reinforcement incentives to the software agents.