Abstract: An automated system and method of converting legacy decision logic to a target format. The legacy files are received by the decision logic translation system, which outputs the business rule content in a standard rule structure, according to the selected target format. The process involves decision logic-based rule extraction. In general, methods or processes for extracting business rules have been difficult to reproduce and do not present clearly the extracted rules regarding the concepts of business rules, their composition and categorization. These drawbacks lead to incomplete extraction of rules and massive manual effort to achieve a complete extraction and verification. In contrast, the proposed system overcomes these drawbacks, and outputs files that can be easily used to migrate the business rules to a new platform.

Abstract: In some implementations, a device may receive, from a user device, a query for information from a user. The device may receive, from an enterprise system, data identifying products and services to be offered by the user. The device may process the query and the data, with a model, to identify a subject of the query and a context for the subject. The device may process the subject and the context, with a model, to determine a workflow for the user. The device may process the data, the subject of the query, and the context for the subject, with a model, to determine a key performance indicator or a decision associated with one of the products or the services. The device may provide information identifying the workflow, the key performance indicator, and/or the decision to the user device via a virtual assistant or a user interface.

Abstract: An automated system and method of converting legacy decision logic to a target format. The legacy files are received by the decision logic translation system, which outputs the business rule content in a standard rule structure, according to the selected target format. The process involves decision logic-based rule extraction. In general, methods or processes for extracting business rules have been difficult to reproduce and do not present clearly the extracted rules regarding the concepts of business rules, their composition and categorization. These drawbacks lead to incomplete extraction of rules and massive manual effort to achieve a complete extraction and verification. In contrast, the proposed system overcomes these drawbacks, and outputs files that can be easily used to migrate the business rules to a new platform.

Abstract: A knowledge graph based reasoning recommendation system and method may analyze past concluded legal cases to find patterns and predict the outcomes of new legal cases before or during litigation. These patterns and outcomes may be used to determine a recommendation for a legal strategy. Input documents and/or enterprise claim data from past concluded cases may be combined and processed to calculate an association rule for the legal outcome associated with one or more of the claim type, counsel, and judge for the group of similar cases based on the analysis of individual cases within the group. Features extracted from the input documents from the past concluded cases and the calculated association rules may be incorporated into a knowledge graph, along with features extracted from input documents from new legal cases. A Policy-Guided Path Reasoning (PGPR) may be applied over the knowledge graph to calculate which legal strategy to recommend.

Abstract: A DevOps virtual assistant platform may analyze a DevOps workflow request received via a collaboration tool to identify one or more tasks, may activate and assign one or more worker bots to the one or more tasks, may verify, based on user credentials of a user associated with the DevOps workflow, that the user is authorized to access one or more backend DevOps tools, may access, via a DevOps orchestration engine, the one or more backend DevOps tools to automatically perform the task using the one or more backend DevOps tools, may determine that the one or more worker bots have completed the one or more tasks, and may provide, based on determining that the one or more worker bots have completed the one or more tasks, an indication via the collaboration tool that the DevOps workflow request has been processed.

Abstract: In some implementations, a device may receive, from a user device, a query for information from a user. The device may receive, from an enterprise system, data identifying products and services to be offered by the user. The device may process the query and the data, with a model, to identify a subject of the query and a context for the subject. The device may process the subject and the context, with a model, to determine a workflow for the user. The device may process the data, the subject of the query, and the context for the subject, with a model, to determine a key performance indicator or a decision associated with one of the products or the services. The device may provide information identifying the workflow, the key performance indicator, and/or the decision to the user device via a virtual assistant or a user interface.

Abstract: A DevOps virtual assistant platform may analyze a DevOps workflow request received via a collaboration tool to identify one or more tasks, may activate and assign one or more worker bots to the one or more tasks, may verify, based on user credentials of a user associated with the DevOps workflow, that the user is authorized to access one or more backend DevOps tools, may access, via a DevOps orchestration engine, the one or more backend DevOps tools to automatically perform the task using the one or more backend DevOps tools, may determine that the one or more worker bots have completed the one or more tasks, and may provide, based on determining that the one or more worker bots have completed the one or more tasks, an indication via the collaboration tool that the DevOps workflow request has been processed.