Abstract: Systems and methods for transforming data for a batch-based legacy software program into data suitable for processing by a streaming-based new software program. In some aspects, the system generates an information stream for multiple threads from batch information received from the legacy software program. The system processes the information stream for the multiple threads using the new software program. If there is a mismatch between outputs of the legacy and new software programs for at least one thread, the system adjusts a data model of the new software program to address the mismatch and generates an updated information stream for processing by the new software program.

Abstract: A campaign server is disclosed which includes a multi-level queue architecture that isolates campaign processing from the delays and inconsistencies of target population information retrieval and a data streaming service system with latency and error remediation measures are disclosed, where the campaign server and the data consumption system can be part of a consolidated system. The data consumption system may include various components to process one or more offers to one or more customers and component configured to detect an error associated the preparation of the errors and/or ii) initiate a retry attempt to process the one or more offers, and and/or storing an instruction in a storage component of the streaming data system to permanently prohibit an attempt to generate the one or more offers at a subsequent time if the retry attempt expires without processing the one or more offers.

Abstract: A campaign server is disclosed which includes a multi-level queue architecture that isolates campaign processing from the delays and inconsistencies of target population information retrieval and a data streaming service system with latency and error remediation measures are disclosed, where the campaign server and the data consumption system can be part of a consolidated system. The data consumption system may include various components to process one or more offers to one or more customers and component configured to detect an error associated the preparation of the errors and/or ii) initiate a retry attempt to process the one or more offers, and/or storing an instruction in a storage component of the streaming data system to permanently prohibit an attempt to generate the one or more offers at a subsequent time if the retry attempt expires without processing the one or more offers.

Abstract: Various embodiments are directed to integrating at least data aggregation, marketing content creation, and fulfillment into a single marketing platform with security features layered in to each of the aforementioned aspects of the platform. In examples, the marketing platform may include at least four components: a data engine, a content engine, a fulfillment engine, and a real-time marketing analytics and monitoring component. The data engine may receive and process data from one or more data sources, the content engine may allow marketing content to be created and approved, and the fulfillment engine may deliver the marketing content via one or more channels. The security features may be configured such that personally identifiable information (PII) or sensitive data is handled and processed securely and appropriately.

Abstract: Disclosed embodiments provide devices, methods, and computer-readable storage media for determining information of an object from a captured image. Further, the disclosed device responds to a user input by capturing, with the camera, image data representing an object. The device then transmits, via a messaging application through a network interface to a server, the image data and a request for information relating to the object. The object information is received via the messaging application through the network from the server and is displayed on the display screen.

Abstract: Various embodiments are directed to a digital marketing rules engine. In examples, the digital marketing rules engine may receive a JavaScript Object Notation (JSON) payload, one or more portions of which can be converted into a rule. The rule may be stored and registered in a cache. The rules engine may receive customer information and determine which of the numerous rules registered in the cache are applicable to the customer. The applicable rules may then be compared against the customer information to determine whether the customer should be included or excluded from an offer. If it is determined that the customer passes or meets the requirements of all the applicable rules, the offer may be provided or presented to the customer via one or more channels.

Abstract: Disclosed embodiments provide devices, methods, and computer-readable storage media for determining information of an object from a captured image. Further, the disclosed device responds to a user input by capturing, with the camera, image data representing an object. The device then transmits, via a messaging application through a network interface to a server, the image data and a request for information relating to the object. The object information is received via the messaging application through the network from the server and is displayed on the display screen.

Abstract: Systems and methods for processing an image using machine learning are provided. The system includes a processor in communication with a client device, and a storage medium storing instructions that, when executed, cause the processor to perform operations including: receiving an image of a vehicle from the client device; extracting one or more features from the image; determining a make and a model of the vehicle based on the extracted features and using a machine learning algorithm. The operations also include: obtaining user information relating to a financing request for the vehicle; determining and transmitting to the client device a real-time quote for the vehicle based on the make, the model, and the user information.

Abstract: Systems and methods for processing an image using machine learning are provided. The system includes a processor in communication with a client device, and a storage medium storing instructions that, when executed, cause the processor to perform operations including: determining a location of the client device; receiving an image of a vehicle from the client device; matching, using a machine learning algorithm, the image to one or more images of vehicles in a database. The operations also include: retrieving vehicle information based on the matched one or more images; obtaining user information relating to a financing request for the vehicle; determining and transmitting to the client device a real-time quote for the vehicle based on the vehicle information and user information.

Abstract: A campaign server is disclosed which includes a multi-level queue architecture that isolates campaign processing from the delays and inconsistencies of target population information retrieval and a data streaming service system with latency and error remediation measures are disclosed, where the campaign server and the data consumption system can be part of a consolidated system. The data consumption system may include various components to process one or more offers to one or more customers and component configured to detect an error associated the preparation of the errors and/or ii) initiate a retry attempt to process the one or more offers, and and/or storing an instruction in a storage component of the streaming data system to permanently prohibit an attempt to generate the one or more offers at a subsequent time if the retry attempt expires without processing the one or more offers.

Abstract: A campaign server is disclosed which includes a multi-level queue architecture that isolates campaign processing from the delays and inconsistencies of target population information retrieval. Each queue level may be intelligently controlled to provide backpressure in accordance with both processing demands of coupled messaging agents and available resources. Queues may be controlled to speed up or slow down customer information retrieval in accordance with the progress of campaign processing. Customer information is combined with campaign content by a set of messaging agents, each of which independently process a campaign for a target. Because messaging agents operate independently of each other, the potential for bottlenecks often encountered during campaign processing is removed. The set of messaging agents may be dynamically modified during operation to add or remove messaging agents in accordance with the processing needs of a campaign and the available resources of the campaign server.

Abstract: A monitoring system includes a non-transitory computer readable medium and a processor. The processor receives, in real time, information of an observable item emitted by each stack layer of an observable system according to an observability specification. The observability specification defines the observable item of each stack layer of the observable system to be monitored. The non-transitory computer readable medium stores the received information of the observable item emitted by each stack layer of the observable system. A graphical user interface displays in real time the received information of the observable item emitted by each stack layer of the observable system.

Abstract: Embodiments disclosed herein generally relate to a system and method for personalization of advertisement content. A computing system receives an HTTP request to access a webpage. The HTTP request includes a visitor identifier. The computing system parses the HTTP request to identify the visitor identifier contained therein. The computing system transfers the visitor identifier to a remote advertisement server. The computing system receives an advertisement call from a web browser executing on the remote computing system. The advertisement call includes the visitor identifier. The computing system generates a customized advertisement based at least on content accessed by the remote computing system on the webpage. The computing system transmits the customized advertisement to the web browser for display with the website on the remote computing system. The website is hosted by the third-party web server.

Abstract: The present disclosure relates to systems and methods for processing an image including a vehicle using machine learning. The system may include a processor in communication with a client device, and a storage medium storing instructions that, when executed, cause the processor to perform operations including: determining a location of the client device; receiving an image of a vehicle from the client device; matching, using a machine learning algorithm, the image to one or more images of vehicles in a database, the database listing vehicles located at the determined location and including images of the vehicles; retrieving vehicle information from the database based on the matched one or more images in the database; obtaining user information relating to a financing request for the vehicle; determining a real-time quote for the vehicle based on the vehicle information and user information; and transmitting the real-time quote for display on the client device.

Abstract: The present disclosure relates to systems and methods for processing an image including a vehicle using machine learning. The system may include a processor in communication with a client device, and a storage medium storing instructions that, when executed, cause the processor to perform operations including: receiving an image of a vehicle from the client device; extracting one or more features from the image; based on the extracted features and using a machine learning algorithm, determining a make and a model of the vehicle; obtaining user information relating to a financing request for the vehicle; determining a real-time quote for the vehicle based on the make, the model, and the user information; and transmitting the real-time quote for display on the client device.

Abstract: A system for processing an image including a vehicle using machine learning can include a processor in communication with a client device, and a storage medium storing instructions that, when executed, cause the processor to perform operations including: receiving an image of a vehicle from the client device; extracting one or more features from the image; based on the extracted features and using a machine learning algorithm, determining a make and a model of the vehicle; obtaining user information relating to a financing request for the vehicle; determining a real-time quote for the vehicle based on the make, the model, and the user information; and transmitting the real-time quote for display on the client device.

Abstract: Disclosed embodiments provide devices, methods, and computer-readable storage media for determining information of an object from a captured image. Further, the disclosed device responds to a user input by capturing, with the camera, image data representing an object. The device then transmits, via a messaging application through a network interface to a server, the image data and a request for information relating to the object. The object information is received via the messaging application through the network from the server and is displayed on the display screen.

Abstract: A system for processing an image including a vehicle using machine learning can include a processor in communication with a client device, and a storage medium storing instructions that, when executed, cause the processor to perform operations including: receiving an image of a vehicle from the client device; extracting one or more features from the image; based on the extracted features and using a machine learning algorithm, determining a make and a model of the vehicle; obtaining user information relating to a financing request for the vehicle; determining a real-time quote for the vehicle based on the make, the model, and the user information; and transmitting the real-time quote for display on the client device.

Abstract: A system for processing an image including a vehicle using machine learning can include a processor in communication with a client device, and a storage medium storing instructions that, when executed, cause the processor to perform operations including: determining a location of the client device; receiving an image of a vehicle from the client device; matching, using a machine learning algorithm, the image to one or more images of vehicles in a database, the database listing vehicles located at the determined location and including images of the vehicles; retrieving vehicle information from the database based on the matched one or more images in the database; obtaining user information relating to a financing request for the vehicle; determining a real-time quote for the vehicle based on the vehicle information and user information; and transmitting the real-time quote for display on the client device.