Abstract: A method or a system accesses an envelope stored in a first database. The envelope includes a set of secure electronic documents, a workflow of tasks, and one or more events associated with the tasks. The system also accesses a second database that stores a credential of an entity associated with the envelope. In response to authenticating the credential, the system receives and caches an access token in a third database. Further, the system monitors the events associated with the tasks in the workflow. In response to detecting an occurrence of at least one event, the system generates and sends a message with the cached access token to a webhook listener. After authentication of the entity using the access token, the webhook listener is caused to generate and send a notification to an administrator of the entity.

Abstract: A document management system utilizes document models for querying, validating, and customizing electronic agreement documents. Document models can be a data structure including document attributes that represent an agreement document. Examples of document attributes include customizable data values, conditions related to the operation of the agreement document and satisfiable by certain values of the customized data values, and rendering parameters for the appearance of the electronic agreement document. The document management system enables a user to create custom document models for generating electronic agreement documents that can be queried, validated, and customized through querying, validating, and customizing the corresponding document models.

Abstract: An online document system can allow users to upload a document packages containing multiple individual document files. The online document system then automatically identifies and separates the component documents within an uploaded document package based on a package template for that type of document package. Based on the documents included in the document package, the online document system can automatically take action on the identified documents. The online document system may recognize component documents within a document package using a set of rules defining potential component documents that may appear within the received document package and one or more methods of recognizing each type of component document. In some embodiments, the online document system can improve package templates and recognition of component documents over time using feedback from the importing users through updates to the document identification rules and/or a supplementary probabilistic recognition system.

Abstract: A document management system performs optical character recognition (OCR) on a high resolution version of an image of a document, obtaining a first set of text representative of the text of the document. The document management system applies a machine-learned model on a low-resolution version of the image of the document, producing a denoised image that is of a higher resolution than that input into the machine-learned model. The document management system performs OCR on the denoised image, obtaining a second set of text representative of the text of the document. The document management system compares the first and second sets of text in the form of an objective loss function. The document management system subsequently generates a feature vector from the comparison of the sets of text and retrains the machine-learned model with the generated feature vector.

Abstract: A document management system generates a document template within which a user can embed document tags. Each document tag represents a term of the document. The user selects a document tag and identifies a location for the document tag within the document template. The embedded document tag adheres to formatting rules of the document template. The document management system accesses a data value corresponding to the selected document tag and generates a modified document. The modified document includes the accessed data value at the identified location, and is subject to the formatting rules of the document template.

Abstract: A system and a method are disclosed for generating recipient notification recommendations using a machine-learned model for a sending entity sending a set of documents to an acting entity and a subset of the set of documents to a receiving entity. The receiving user is subscribed to a notification service of a document management system to receive push notifications regarding statuses of inbound documents. The notifications for the receiving entity are generated based on recipient notification definition provided by the sending entity. The document management system trains a machine-learned model to generate recipient notification recommendations for the sending entity selecting event criteria that indicate when to generate the notifications and types of data to include in the notifications. The machine-learned model is trained based on data associated with historical notification definitions provided by historical sending entities.

Abstract: A highlighting engine modifies a target document by identifying and highlighting a set of text passages. The highlighting engine receives a training set of data including documents that each include a set of highlighted text passages. The highlighting engine trains a machine learned model using the training set of data. The trained machine learned model, when applied to subsequent identified candidate sets of text passages within the target document, identifies the set of text passages to highlight. The highlighting engine modifies the target document with the highlighted set of text passages and provides the modified target document for display via an interface. The highlighted set of text passages enable a user to quickly read and understand the target document.

Abstract: A document management system trains a machine learned model configured to facilitate contract generation. The document management system generates a training set for the machine learned model using user input. From a first set of agreement documents, the document management system identifies a first set of sentences relevant to clause terms input by the user. The document management system identifies, from a second set of agreement documents, a second set of sentences similar to the first set of sentences. In response to user feedback about the second set of sentences, the document management system updates the training set. The document management system retrains the machine learned model using the updated training set.

Abstract: Techniques are described for a system document management comprising one or more processors having access to a memory. The system is configured to open an electronic document that is to be electronically signed, the electronic document having an active component connected to an external data source. The system is further configured to, while the electronic document is open, execute the active component to retrieve data from the external data source. The system is further configured to insert the data retrieved from the external data source into a field of the electronic document. The system is further configured to output, for display, a graphical user interface that presents the content of the electronic document to a user device.

Abstract: Various embodiments support or provide for an extensible electronic claim verification system that offers extensible support for electronic verification by one or more external electronic claim verification services that are external to the extensible electronic claim verification system. For some embodiments, the extensible claim verification system is readily configurable (e.g., by a user) to add or remove access to one or more external claim verification services available for use through the extensible electronic claim verification system by a client device. Some embodiments implement the extensible support by using a unified protocol for interfacing with different external claim verification services. By use of the unified protocol, various embodiments enable an external claim verification service to plug into an extensible claim verification system, thereby permitting a user to extend support of the extensible claim verification system to different types of external claim verification services.

Abstract: A centralized document system generates a document package in response to a request by an originating entity. The document package includes at least one document for execution by a first receiving entity. The first receiving entity can specify a set of permissions for a second receiving entity to perform actions to documents within the package on behalf of the first receiving entity. Accordingly, the system may provide the document package to both the first and second receiving entities for the first receiving entity to execute the at least one document. Before providing the document to the second receiving entity, system may determine whether there is a sensitive document in the package and whether to delegate the document to the second entity. Accordingly, the system may prevent a sensitive document package from being provided to the second receiving entity for execution.

Abstract: A computing system remotely trains a public ensemble model of an artificial intelligence model management system. The system receives, by the model management system, an encrypted representation of a private data value from a client system. The encrypted representation includes annotation information provided by the client system. The system determines, using the encrypted representation and the annotation information, a data value cluster that corresponds to the private data value. Data value clusters are generated using encrypted representations of a private data values provided by client systems. The system obtains, based on the assigned data value cluster, an encrypted representation of a model. The model is trained remotely by the client system using the private data value. The system adds the encrypted representation of the model to the public ensemble model. The public ensemble model is generated using a plurality of encrypted representations of models remotely trained by the client systems.

Abstract: A system and method for managing an electronic contract for hybrid runtime execution, which includes a contract execution service that comprises an internal runtime environment and a set of integrations to external resources with at least one integration to an on-chain runtime, wherein the contract execution service comprises configuration to: establish the electronic contract, wherein the electronic contract comprises a set of executable programmable components and a set of natural language components; change the state of the electronic contract and generate a contract event; and in response to the contract event: extend execution of the electronic contract to an on-chain environment, when the contract event includes an associated on-chain integration; and extend execution of the electronic contract to an external application resource, when the contract event includes an associated external service integration.

Abstract: A system receives a set of rules associated with a document type from a supplier entity. Each rule identifies a set of conditions and a set of actions to be taken after a document of a document type is signed if the set of conditions is satisfied. When a supplier entity sends a document of the document type to a signing entity and the signing entity provides an electronic signature, the system determines whether conditions of rules associated with the document type are satisfied. For each rule that is satisfied, the system performs actions identified by the rule.

Abstract: Techniques are described for a system document management comprising one or more processors having access to a memory. The system is configured to determine an attribute for an input document for execution by a signer. The system is also configured to generate a similarity score for each of a plurality of candidate documents using a machine learning model, wherein using the machine learning model comprises providing the attribute as an input to the machine learning model. The system is also configured to generate data for a graphical user interface comprising an indication of at least a subset of the candidate documents based on the similarity scores generated for each of the plurality of candidate documents. The system is configured to output, for display, the data to a user device.

Abstract: A document management system can include an artificial intelligence-based document manager that can perform one or more predictive operations based on characteristics of a user, a document, a user account, or historical document activity. For instance, the document management system can apply a machine-learning model to determine how long an expiring agreement document is likely to take to renegotiate and can prompt a user to begin the renegotiation process in advance. The document management system can detect a change to language in a particular clause type and can prompt a user to update other documents that include the clause type to include the change. The document management system can determine a type of a document being worked on and can identify one or more actions that a corresponding user may want to take using a machine-learning model trained on similar documents and similar users.

Abstract: A system and a method are disclosed for providing recommendations for sets of security operations for improving security of documents created or executed within an online document system. A supplier entity may select sets of security operations to be performed for a request provided to a signing entity. The online document system computes an aggregate measure of security for the selected sets of security operations and compares it to a threshold measure of security. If the aggregate measure is less than the threshold measure, the online document system uses a machine-learned model to identify additional sets of security operations that when added, results in an updated aggregate measure of security greater than the threshold. The additional sets of security operations are presented to the supplier entity for inclusion within a security operation workflow in combination with the selected sets of security operations.

Abstract: An agenda dictating a sequence of actions to occur during a conference associated with a plurality of participants is accessed. The sequence of actions is associated with an electronic signature envelope. Content shared by a sharing participant of the conference is monitored for content corresponding to a given action of the sequence. Responsive to detecting the content corresponding to the given action, an acting participant for the given action is determined and data obtained from sensors of a client device of the acting participant is monitored. It is determined that the data indicates that the acting participant has performed the given action and an auditable data structure reflective of the data is generated. The content shared by the sharing participant of the conference is automatically modified to include content corresponding to a next action of the sequence of actions.

Abstract: A system predicts metadata attributes associated with documents using machine learning models. The document may represent an interaction between entities. The system trains machine learning models to predict scores indicating whether a token or a sequence of token of a document represents a metadata attribute. The metadata prediction is used to annotate the document and display to users. The system receives user feedback via the user interface and uses the user feedback to evaluate or retrain the model. The system generates training data by receiving a set of annotated documents and comparing the annotated documents against other documents to identify matching documents. The system determines when to execute the machine learning based metadata prediction based on steps of document workflow executed by the system.

Abstract: A system and a method are disclosed for automatic content upload and process. The system retrieves a set of files from a source location based on instructions received from a client device of a user. The system then classifies the set of files into a plurality of categories corresponding to a sequence of one or more services configured to process or store files. The system then generates a data structure storing key values, where the key values are derived based on respective processing of subsets of files. Responsive to receiving an input to execute logic relating to the set of files, the system determines that the input is associated with one or more of the key values, retrieves the one or more of the key values, and executing the logic using the one or more retrieved key values.