Abstract: Improved techniques to access content from documents in an automated fashion. The improved techniques permit extraction of data from documents, namely, images of documents. The extraction processing can be hierarchical, such as being performed in multiple levels (i.e., multi-leveled). At an upper level, numerous different objects within a document can be detected along with positional data for the objects and can be categorized based on a type of object. Then, at lower levels, the different objects can be processed differently depending on the type of object. As a result, data extraction from the document can be performed with greater reliability and precision.

Abstract: Systems and methods for producing automation programs that are suitable for performing business and personal tasks using software application programs. The methods and systems involve can identify or receive a user request for the production of an automation program and then utilizing one or more machine learning models, where each of the machine learning models can produce an aspect of the requested automation program. Each of the machine learning models are provided with inputs such as a specific user's request for an automation program to automate tasks, the definition of a role that the model should take on, domain knowledge specific to an aspect of the automation program being requested, and functional instructions for each of the machine learning models to produce a desired output. The outputs of each of the machine learning models can be combined to form the user-requested automation program.

Abstract: Improved techniques to access content from documents in an automated fashion. The improved techniques permit content within documents to be retrieved and then used by computer systems operating various software programs (e.g., application programs), such as an extraction program. Documents, especially business transaction documents, often have various descriptors (or tables) and values that form key-value pairs. The improved techniques permit key-value pairs within documents to be recognized and extracted from documents. Consequently, RPA systems are able to accurately understand the content of tables within documents so that users and/or software robots can operate on the documents with increased reliability and flexibility.

Abstract: Improved techniques to access content from documents in an automated fashion. The improved techniques permit content within documents to be retrieved and then used by computer systems operating various software programs (e.g., application programs), such as an extraction program. Documents, especially business transaction documents, often have various descriptors (or tables) and values that form key-value pairs. The improved techniques permit key-value pairs within documents to be recognized and extracted from documents. Consequently, RPA systems are able to accurately understand the content of tables within documents so that users and/or software robots can operate on the documents with increased reliability and flexibility.

Abstract: Improved techniques to access content from documents in an automated fashion. The improved techniques permit content within documents to be retrieved and then used by computer systems operating various software programs (e.g., application programs), such as an extraction program. Documents, especially business transaction documents, often have various descriptors (or tables) and values that form key-value pairs. The improved techniques permit key-value pairs within documents to be recognized and extracted from documents. Consequently, RPA systems are able to accurately understand the content of tables within documents so that users and/or software robots can operate on the documents with increased reliability and flexibility.

Abstract: Improved techniques to access content from documents in an automated fashion. The improved techniques permit content of tables within documents to be retrieved and then used by computer systems operating various software programs (e.g., application programs). Consequently, Robotic Process Automation (RPA) systems are able to accurately understand the content of tables within documents so that users, application programs and/or software robots can operate on the documents with increased reliability and flexibility. The documents being received and processed can be electronic images of documents. For example, the documents can be business transaction documents which include tables, such as purchase orders, invoices, delivery receipts, bills of lading, etc.

Abstract: Improved techniques to access content from documents in an automated fashion. The improved techniques permit extraction of data from documents, namely, images of documents. The extraction processing can be hierarchical, such as being performed in multiple levels (i.e., multi-leveled). At an upper level, numerous different objects within a document can be detected along with positional data for the objects and can be categorized based on a type of object. Then, at lower levels, the different objects can be processed differently depending on the type of object. As a result, data extraction from the document can be performed with greater reliability and precision.