Abstract: A system and a method are disclosed herein for machine-learned detection of outliers within payload requests. An entity management system uses machine learning to cluster data characterizing requests from entities to route payloads, and determines one or more data clusters that are outliers. The system receives a request to route a payload to a destination, and applies a supervised machine learning model to size and type information indicated by the payload. The supervised machine learning model applies a label to the payload data (e.g., indicating that the payload routing request is an outlier). This outlier detection may drive a validation process to address detected outliers. The system may receive an indication to perform a validation function and transmit the payload to a validation destination. The system may leverage payload data and feedback received from an entity to optimize machine learning techniques to the entity.

Abstract: A document management system manages documents of an enterprise. The documents are managed in a secure manner such that access to entries included in the documents may be restricted according to a security policy associated with the documents. The document management system may secure documents such that entries are still provided to users that request the documents, but sensitive data included in the entries is masked according to the security policies for the documents.

Abstract: A management system operates in conjunction with an automotive dealership to improve customer engagement with the automotive dealership. The management system creates customer profiles of the automotive dealership systems' customers using features of the customers obtained via various sources. The management system assigns a customer category to a customer based on the features included in the customer profile and may generate a customized recommendation of a product and/or service for the customer to purchase at the dealership based at least in part on the customer category.

Abstract: A physical lock interface system facilitates secure and remote control of assignment and enablement of physical lock systems. The system receives a request to enable a user to disable a physical lock during a particular range of time. The lock is associated with a geofence boundary defined by a geofence. During the range of time, the system monitors for a presence of the user within the geofence. In response to determining that the user is within the geofence during the range of time, the system transmits a communication to an application of a client device of the user. The application is configured to interact electronically with the physical lock and to cause the client device to display information identifying the physical lock based on the communication. The system detects an electronic signal initiated by the application while the user is within the geofence and disables the physical lock.

Abstract: A system and a method are disclosed for receiving an entry, the entry comprising first content and a metadata tag corresponding to a classification, the first content populated by a first source. A rules engine determines that the first content comprises a data field associated with at least one of a plurality of reconciliation policies. Responsive to determining that the first content comprises a data field associated with at least one of the plurality of reconciliation policies, the rules engine selects a reconciliation policy based on the metadata tag. The rules engine retrieves, from a second source, second content associated with the data field, inputs the first content and the second content into a model, the model selected based on the reconciliation policy, the model generating an output, and performs a remediation action based on the output.

Abstract: A system formats and normalizes data stored in received files. A data processing engine identifies a filetype and format of the file based on samples of the file contents. The system detects a schema of the file to determine the datatypes and locations of data within the file. The schema detection process may depend on the identified filetype of the file. Once a filetype and schema have been determined, the system can reformat data stored within different sections of the file in view of the datatypes. The formatted file is stored in a data lake with other files received by the system. The formatting process can involve normalization of certain datatypes, which facilitates access of the data later by a user querying the data stored in files at the data lake.

Abstract: A document management system manages documents. The documents are managed such that the documents may be shared with one or more users during an online sharing session for electronic signing. During the online sharing session, one or more documents are collaboratively reviewed by one or more participants of the online sharing session. The one or more documents are e-signed at least one of the participants of the online sharing session.

Abstract: A system and a method are disclosed for receiving, from a source of a plurality of candidate sources, a payload comprising content and metadata. The system selects a destination to which to route the payload based on the source and the content, and generates an entry at the destination based on the content. The system inputs the metadata into a classification engine, and receives, as output from the classification engine, one or more classifications for the payload. The system applies a metadata tag to the entry, the metadata tag indicating the one or more classifications. The system receives a search request from a client device specifying at least one of the one or more classifications, and, in response to receiving the search request, provides the entry to the client device based on a matching classification.

Abstract: In one aspect, a computerized method useful for three-dimensional (3D) model data rendering and information capturing during a vehicle inspection check-in process for service comprising includes the step of providing a vehicle for a check-in inspection. The computerized method includes the step of obtaining a vehicle identification number (VIN) of the vehicle. The computerized method includes the step of, based on the VIN of the vehicle, obtaining a 3D vehicle model data. The 3D vehicle model data matches a type of the vehicle. The 3D vehicle model data is generated from a manufacturer's three-dimensional (3D) computer-aided design (CAD) model data of the type of the vehicle.