Abstract: Methods, systems, and computer-readable media are provided for asynchronous process automation that efficiently manages asynchronous processes based on process control metadata to keep data up-to-date at an adaptively variable type-specific cadence based on process control metadata, eliminating the need for manual engagement to maintain operational activities. An event-driven framework is provided for the asynchronous process automation that includes AI agent(s) for interactions, along with a process management system that tracks pending potential work items due to one or more changes in source data. The process management system activates an asynchronous process management process after a wait period. The process management system then determines which pending potential work items to perform in an iteration of evaluation of the pending potential work items. The process control metadata includes stored limitations on a timing for performing individual processes.

Abstract: Systems, methods, and computer-readable media provide a context-specific prompt to answer a user query. The systems, methods, and computer-readable media determine a context based on content of a natural language request and/or determine a role of a user who submitted the natural language request. Additionally or alternatively, templates or RAG sources that will be used for prompt generation may include financials domain-specific knowledge or other domain-specific knowledge or insights. Inclusion of this additional information in the prompt enhances the context to promote more accurate results from a large language model. In one embodiment, the prompt templates are created from various RAG sources, such as payables, general ledger, receivables, and asset management, containing structured data and information specific to the financial domain, enterprise, or other domain, which helps craft accurate prompts.