A method and a server system for facilitating implementation of regulations by organizations is described. Regulations are sourced from data stores associated with a plurality of regulatory authorities to configure a corpus of regulations. A plurality of enriched regulations is generated from the corpus of regulations. A user is enabled to create a construct related to at least one of an organization and an industry associated with the user. The construct is indicative of corresponding functional constituents and relationships among the functional constituents. Search and discovery of one or more regulations applicable to the organization or the industry is facilitated. Subsequent to the discovery of the one or more regulations, a linking of clauses of a respective enriched regulation to at least one functional constituent of the construct is enabled for facilitating implementation of the one or more regulations applicable to the organization or the industry associated with the user.

Exemplary embodiments automate the production of memos in support of the due diligence process for underwriting. Target users may include investment bankers, financial analysts, and the like. The data collection process of supporting data for the memo may be automated thus improving efficiency in the creation of the due diligence memo. Both the collected data and memos may be stored in a database, enabling access at a later date and enabling the collected data from one memo, as well as other information from the memo, to be used for future memos. The data collection may be conducted from both structured and unstructured sources. The sources may be both internal and external sources. The external sources may be public data sources.

Exemplary embodiments automate the production of memos in support of the due diligence process for underwriting. Target users may include investment bankers, financial analysts, and the like. The data collection process of supporting data for the memo may be automated thus improving efficiency in the creation of the due diligence memo. Both the collected data and memos may be stored in a database, enabling access at a later date and enabling the collected data from one memo, as well as other information from the memo, to be used for future memos. The data collection may be conducted from both structured and unstructured sources. The sources may be both internal and external sources. The external sources may be public data sources.

A real-time conversation is monitored between a user and an intelligent virtual assistant (IVA). A visualization may be generated and displayed to the user on the user computing device based on one or more topics identified in the conversation. The conversation between the user and the IVA may continue and is continued to be monitored. The visualization can be updated as the conversation continues, e.g., based on further topics being identified.

A real-time conversation is monitored between a user and an intelligent virtual assistant (IVA). A visualization may be generated and displayed to the user on the user computing device based on one or more topics identified in the conversation. The conversation between the user and the IVA may continue and is continued to be monitored. The visualization can be updated as the conversation continues, e.g., based on further topics being identified.

A mechanism is provided for routinely evaluating an accuracy of a request processing pipeline. A set of questions is executed through the request processing pipeline, producing a list of answers, supporting documents, and accuracy metrics. A determination is made as to whether a document contribution value of each document associated with the answer is equal to or above a document contribution threshold value. For those documents equal to or above the document contribution threshold value, a snapshot is stored in a training-data data structure. Based on a clustering of questions, for each question cluster, a determination is made of an average accuracy metric. A comparison is performed and a determination is made as to whether an accuracy metric delta exceeds the accuracy metric threshold value. If so, a differential report is generated indicating a review is needed of a training of the request processing pipeline.

A mechanism is provided for routinely evaluating an accuracy of a request processing pipeline. A set of questions is executed through the request processing pipeline, producing a list of answers, supporting documents, and accuracy metrics. A determination is made as to whether a document contribution value of each document associated with the answer is equal to or above a document contribution threshold value. For those documents equal to or above the document contribution threshold value, a snapshot is stored in a training-data data structure. Based on a clustering of questions, for each question cluster, a determination is made of an average accuracy metric. A comparison is performed and a determination is made as to whether an accuracy metric delta exceeds the accuracy metric threshold value. If so, a differential report is generated indicating a review is needed of a training of the request processing pipeline.

The present disclosure involves systems, software, and computer implemented methods for creating line item information from tabular data. One example method includes receiving event data values at a system. Column headers of columns in the event data values are identified. At least one column header is not included in standard line item terms used by the system. Column values of the columns in the event data values are identified. The identified column headers and the identified column values are processed using one or more models to map each column to a standard line item term used by the system. The processing includes using context determination and content recognition to identify standard line item terms. An event is created in the system, including the creation of line items from the identified column value. Each line item includes standard line item terms mapped to the columns.

The present disclosure involves systems, software, and computer implemented methods for creating line item information from tabular data. One example method includes receiving event data values at a system. Column headers of columns in the event data values are identified. At least one column header is not included in standard line item terms used by the system. Column values of the columns in the event data values are identified. The identified column headers and the identified column values are processed using one or more models to map each column to a standard line item term used by the system. The processing includes using context determination and content recognition to identify standard line item terms. An event is created in the system, including the creation of line items from the identified column value. Each line item includes standard line item terms mapped to the columns.

Systems and methods for improving question-answering recall for complex, multi-sentence, convergent questions. More specifically, an autonomous agent accesses an initial answer that partly answers a question received from a user device. The agent represents the question and the initial answer as discourse trees. From the discourse trees, the agent identifies entities in the question that are not addressed by the answer. The agent forms an additional discourse tree from an additional resource such as a corpus of text. The additional discourse tree rhetorically connects a non-addressed entity with the answer. The agent designates this discourse tree as an imaginary discourse tree. When combined with the initial answer discourse tree, the imaginary discourse tree is used to generate an improved answer relative to existing solutions.