Abstract: A document management system manages documents of an entity. The document management system monitors for entries in a document that are suspicious. Entries in the document are classified by the document management system as a “suspicious entry” or a “non-suspicious entry.” In one embodiment, a suspicious entry is indicative of potentially suspicious activity at the entity.

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: Embodiments relate to a document parser module that can receive a document template from a producing entity, parse the template, and generate a mapping between the template and identifiers of the transaction entity. Using the mapping and parsed information, a document generator module may generate a document that includes the required identifier data and meets the submission standards of the producing entity. A configuration file may be saved so that a document can be generated and submitted every reporting period with little or no additional modification by the transaction entity.

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: Embodiments relate to a document parser module that can receive a document template from a producing entity, parse the template, and generate a mapping between the template and identifiers of the transaction entity. Using the mapping and parsed information, a document generator module may generate a document that includes the required identifier data and meets the submission standards of the producing entity. A configuration file may be saved so that a document can be generated and submitted every reporting period with little or no additional modification by the transaction entity.

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: 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 document management system manages documents of an entity. The document management system monitors for entries in a document that are suspicious. Entries in the document are classified by the document management system as a “suspicious entry” or a “non-suspicious entry.” In one embodiment, a suspicious entry is indicative of potentially suspicious activity at the entity.

Abstract: A document management system manages documents of an entity. The document management system monitors for entries in a document that are suspicious. Entries in the document are classified by the document management system as a “suspicious entry” or a “non-suspicious entry.” In one embodiment, a suspicious entry is indicative of potentially suspicious activity at the entity.

Abstract: A system and a method are disclosed herein for machine-learned detection of outliers within entity functions. An entity management system uses machine learning to cluster data characterizing functions performed by entities, and determines one or more data clusters that are outliers. The system receives entity function data indicating a metric and a type, and provides the received data into a supervised machine learning model. The model is trained to apply a label to the entity function data, where the label indicates a classification of the data into a cluster (e.g., an outlier cluster). This outlier detection may inform the system's generation of a function monitor to guide rectifying action that addresses the detected outliers. The system may receive user input affirming or rejection the classification of the data into a particular cluster. The system may leverage the user input to retrain the supervised machine learning model.

Abstract: Embodiments relate to a document parser module that can receive a document template from a producing entity, parse the template, and generate a mapping between the template and identifiers of the transaction entity. Using the mapping and parsed information, a document generator module may generate a document that includes the required identifier data and meets the submission standards of the producing entity. A configuration file may be saved so that a document can be generated and submitted every reporting period with little or no additional modification by the transaction entity.

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: 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 and a method are disclosed herein for machine-learned detection of outliers within entity functions. An entity management system uses machine learning to cluster data characterizing functions performed by entities, and determines one or more data clusters that are outliers. The system receives entity function data indicating a metric and a type, and provides the received data into a supervised machine learning model. The model is trained to apply a label to the entity function data, where the label indicates a classification of the data into a cluster (e.g., an outlier cluster). This outlier detection may inform the system's generation of a function monitor to guide rectifying action that addresses the detected outliers. The system may receive user input affirming or rejection the classification of the data into a particular cluster. The system may leverage the user input to retrain the supervised machine learning model.

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 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 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.