Abstract: An artifact generation platform can generate project artifacts by implementing extended context windows on an artificial intelligence model (e.g., a trained neural network). Project artifacts can be generated by processing a set of files (e.g., transcript, audio recording, video recording, audiovisual recording) to extract or generate transcript and/or context tokens. Using user-provided output type instructions and the tokens, a trained neural network can generate a project artifact according to the specific output type and context (e.g., project type, user role, domain, technology stack descriptor). The platform can include a chat bot to enable users to query the project artifact and/or cause computer systems to perform automatic actions using the generated project artifact.

Abstract: Systems, methods, and computer-readable media for computer-assisted output validation in machine learning/artificial intelligence platforms are disclosed. An application instance includes one or more machine learning models used to generate searchable data structures based on multimodal inputs.

Abstract: Systems, methods, and computer-readable media for generating responses to natural-language queries regarding items in unstructured documents are disclosed. An application instance that includes one or more machine learning models receives, from a subscriber computing system, a query and document comprising unstructured data. Based on the unstructured data, the application instance generates a searchable data structure using a machine learning model. A query response is generated by performing a semantic search on the searchable data structure. The query response is provided to a target application.

Abstract: Systems, methods, and computer-readable media for generating responses to natural-language queries regarding items in unstructured documents are disclosed. An application instance that includes one or more machine learning models receives, from a subscriber computing system, a query and document comprising unstructured data. Based on the unstructured data, the application instance generates a searchable data structure using a machine learning model. A query response is generated by performing a semantic search on the searchable data structure. The query response is provided to a target application.

Abstract: An application instance that includes one or more machine learning models receives, from a subscriber computing system, a document comprising unstructured data. Based on the unstructured data, the application instance generates an optimized model input that includes a plurality of parsed document sections. For each parsed document section, the application instance generates an output set by performing, by a machine learning model, at least one key information extraction operation. The machine learning model transmits the output in structured form to a target application operated or hosted at least in part by a subscriber entity associated with the subscriber computing system.