Abstract: Systems and methods for production readiness verification and monitoring are disclosed. A set of compliance requirements including one or more cloud-specific requirements and status information regarding a status of each of a plurality of clouds within a cloud environment is received. The status information includes availability of one or more servers within each of the plurality of clouds. The status information for each of the plurality of clouds is compared to the one or more cloud-specific requirements and the cloud environment as identified as one of compliant or non-compliant. The cloud environment is identified as compliant when each of the one or more cloud-specific requirements are satisfied and non-compliant when at least one of the one or more cloud-specific requirements are not satisfied.

Abstract: An automated warehouse storage system including a multilevel storage array is provided. Each aisle has a set of storage levels and each level has storage locations distributed along the aisle. The guideway network extending through the multilevel storage array is configured for autonomous vehicles to move along the guideway network within the multilevel storage array. The guideway network including an inter-aisle guideway spanning at least two of the multiple aisles and a set of guideway levels extending in an aisle of the multiple aisles and disposed so that each guideway level is at a different one of the storage levels and the vehicles on the guideway level can access the storage locations distributed along the aisle. Each set of guideway levels is connected to the inter-aisle guideway forming a common guideway path so that a vehicle can move between inter-aisle guideway and each guideway level along the common guideway path.

Abstract: A system comprising one or more processors and one or more non-transitory computer-readable media storing computing instructions that, when executed on the one or more processors, cause the one or more processors to perform operations comprising: evaluating, using a price band determination model, degrees of expensiveness of items relative to each other in item type categories; generating, using the price band determination model, price bands associated with item type categories; assigning each of the items to a respective one of the price bands associated with a respective one of the item type categories; and presenting, to one or more end-user applications, at least one other item corresponding to at least one of the price bands associated with at least one of the item type categories. Other embodiments are disclosed.

Abstract: Systems and methods described herein are optimized for cutting sealing elements on packages using optical radiation. Packages can pass through a cutting device that applies the optical radiation to damage, vaporize, or cut the sealing element (e.g., tape) on the package. The systems and methods control several aspects of the cutting process to adjust throughput, improve efficiency, and reduce line stoppages. Systems can include an in-feed conveyor that orients packages and rejects packages that are out of specification, which can lead to issues such as jamming or damage to the equipment. Systems can include a variable-speed cut conveyor controlled by a computing system to dynamically adjust the speed of packages based upon historical cut quality, environmental measurement data, and height data related to a vertical dimension of the package.

Abstract: This application relates to apparatus and methods for automatically determining item relevancy based on textual information. In some examples, a computing device receives a search query, and a plurality of items corresponding to the search query. The computing device may identify one or more features of the search query. The computing device may generate relevancy values for each of the items based on the features of the search query, and features of each of the plurality of items. For example, the computing device may generate, for each of the items, a plurality of relevance values, each relevance value generated based on a feature of the search query and corresponding features of the item. The computing device may transmit the generated relevancy values for the plurality of items. In some examples, the computing device may rank the plurality of items based on the generated relevancy values.

Abstract: Systems and methods for item price assignment. A line recommendation engine receives unassigned records from a queue and stores one or more line recommendations for the unassigned item record in a recommendation database. The line recommendation engine can determine a new line should be recommended, and/or which existing lines the unassigned item record could be assigned to. A user interface can display the one or more line recommendations for the unassigned item record to a user and receive an input indicating a selected line identifier for the unassigned item record. A machine learning engine can modify a parameter of the line recommendation engine based on the selected line identifier.

Abstract: In some embodiments, systems and methods are provided to recognize retail products, comprising: a model training system configured to: identify a customer; access an associated customer profile; access and apply a set of filtering rules to a product database based on customer data; generate a listing of products specific to the customer; access and apply a model training set of rules to train a machine learning model based on the listing of products and corresponding image data for each of the products in the listing of products; and communicate the trained model to the portable user device associated with first customer.

Abstract: Systems, apparatuses, and methods for order fulfillment by community delivery. A method for product delivery comprises detecting a presence of a user device of a store customer associated with a customer profile at a location associated with a store location based on a location sensor, identifying a delivery community associated with the customer profile from a plurality of delivery communities in the community database, identifying available community delivery orders associated with other members of the delivery community in an order database, instructing a pickup order fulfillment system to prepare the one or more community delivery orders for pickup by the store customer, and providing delivery instructions for the one or more community delivery orders.

Abstract: In some embodiments, purchase systems and methods are provided. Some embodiments comprise one or more processors configured to receive, at a point of sale device, a request to use self-checkout through a user computing device; couple the point of sale device with the user computing device by: display by the point of sale device a coupling code configured to be scanned by the user computing device; receive the coupling code by a server system; and interpret, at the server system, the coupling code to identify the point of sale device; cause contents of an electronic shopping cart associated with a transaction to be transmitted to the identified point of sale device; receive a customer identifier associated with the transaction; and conclude, on the point of sale device, the transaction based on the coupling of the point of sale device with the user computing device.

Abstract: A system and method are disclosed for supplying one or more goods to a physical store location. The goods may be received at a distribution center (DC). At the DC, the goods may be decanted from their shipping containers into one or more sub-totes, which are contained within one or more product totes. The sub-totes may be transferred from the one or more product totes to one or more order totes based on a velocity of movement of the plurality of goods at the physical store location.

Abstract: Systems and methods including one or more processors and one or more non-transitory media storing computing instructions that, when executed on the one or more processors, cause the one or more processors to perform: storing one or more notifications in a data store; receiving a new notification; determining a respective number of notifications in each respective segment of a plurality of approximately equal segments; using the respective number of notifications in each respective segment of the plurality of approximately equal segments to determine a number of the one or more notifications; when the number of the one or more notifications is equal to or greater than a maximum number of notifications, removing at least one notification of the one or more notifications; and before or after removing the at least one notification, storing the new notification in the data store.

Abstract: This application relates to apparatus and methods for identifying fraudulent payment transfers. In some examples, a computing device determines payment transfer initiation features, and payment transfer reception features, based on previous payment transfer data. The computing device may train a machine learning fraud detection model with the payment transfer initiation features, and may train a machine learning fraud detection model with the payment transfer reception features. Once trained, the computing device may employ the machine learning fraud detection models to identify fraudulent payment transfers. For example, the computing device may determine whether a payment transfer is fraudulent when the payment transfer is initiated. Assuming the payment transfer is allowed, the computing device may determine whether the payment transfer is fraudulent when the payment is being received.

Abstract: A magnetic shelving fence that provides stabilization of retail products on merchandised shelving during shelving relocation. The includes an elongate multi-surfaced structure and one or more magnets. The elongate structure includes a vertical front plate, a horizontal mount plate, and an edge surround portion. The vertical front plate provides a planar barrier to merchandized product movement. The horizontal mount plate is disposed in a generally perpendicular orientation with respect to the vertical front plate. The edge surround portion connects the lower edge of the front plate to the horizontal mount plate and defines a channel shaped to surround a front edge of shelving. The magnets of the magnetic shelving fence are fixedly coupled to the horizontal mount plate. Further, the magnets are oriented to secure the elongate multi-surfaced structure with a bottom face of metal shelving via temporary and non-destructive attachment.

Abstract: A system including one or more processors and one or more non-transitory computer-readable media storing computing instructions that, when executed on the one or more processors, cause the one or more processors to perform certain acts. The acts can include determining an estimated arrival time of a user at a physical store. The acts also can include generating an estimated wait time using a machine learning model and based on input data comprising the estimated arrival time and dynamic wait time data for the physical store. The acts additionally can include sending the estimated wait time to at least one of the physical store or a mobile device of the user. Other embodiments are disclosed.

Abstract: Examples provide a single-command menu option for initiating security scanning of source code without user interaction with the security scan component performing the security scan. The single-command menu option can include a single-click menu option in a graphical user interface, a command-line utility or a web interface for performing web service calls to the security scanning service(s). A user selects source code for scanning. A zip file is created for the selected source code. The zip file is placed in a target directory or scan queue for upload to the security scan component. A user ID appended to the source code is utilized to return a summary report of the scan results to the user without user credentials or login to the system.

Abstract: A system can include one or more processors and one or more non-transitory computer-readable media storing computing instructions that, when executed on the one or more processors, cause the one or more processors to perform operations including: (1) determining, by a predictive algorithm via a machine learning model, one or more predicted bids for one or more keywords in one or more campaigns; (2) adjusting the one or more predicted bids for the one or more keywords in the one or more campaigns; (3) pacing the one or more predicted bids for the one or more keywords by multiplying the one or more predicted bids by a pacing factor; iteratively adding real-time data to a training data set for the predictive algorithm; and iterating (1)-(3) at one or more periodic intervals as the real-time data is added to the training data set. Other embodiments are disclosed herein.

Abstract: This application relates to apparatus and methods for automatically servicing item data requests in data management systems, such as in retail management systems. The apparatus and methods employ a throttling technique to service data requests from one or more entities. In some examples, a computing device initializes assigns a counter for each entity, and initializes each counter with an initial value. The computing device also occasionally (e.g., periodically) resets each counter to the initial value. The computing device may receive a data request from one of the entities, and determines whether the counter corresponding to the entity identifies a count that is beyond a threshold. If the counter identifies a count beyond the threshold, the computing device adjusts the counter, and processes the data request. If the counter does not identify a count beyond the threshold, the computing device responds to the entity with an error.

Abstract: Systems and methods for e-commerce systems using natural language understanding are described. A computing device is configured receive a user utterance including at least one identified semantic component and at least one missing semantic component and generate a context stack including a set of context entries. Each of the context entries includes a root intent element, an entity list element, and a dialogue stack and each context entry in the set of context entries is associated with one of a user utterance or a system utterance. The computing device is further configured to review at least one context entry in the set of context entries to locate the at least one missing semantic element within the dialogue stack and generate an intent flow execution request including the at least one semantic element from the first speech data and the missing semantic element.

Abstract: This application relates to apparatus and methods for automatically determining and providing digital recommendations including discounted items with associated savings. In some examples, a computing device obtains savings data including savings items. In response to obtaining the savings data, the computing device obtains a plurality of clusters. Each cluster of the plurality of clusters includes a set of product types. The computing device obtains user data associated with a user, and based on the savings data and the plurality of clusters, determines a set of initial items for recommendation. The set of initial items includes a subset of the savings items. The computing device also determines final recommendation items for the user based on the set of initial items and the user data.