Abstract: Systems, methods, and computer-readable media for constructing a tax return associated with a client during a session. A system may include a historical client data store operable to store historical client data associated with the client. A system may include a session data store operable to store session data associated with the session. A system may include an inferencing agent operable to analyze the historical client data and the session data and generate one or more inferences, the one or more inferences associated with at least one of additional data to gather from the client or a tax data value. A system may include a document manager agent operable to acquire and ingest the additional data from the client into the session data store. A system may include an orchestration agent operable to orchestrate one or more tasks of the inferencing agent and the document manager agent.

Abstract: Computer implemented methods and systems are provided for dynamic transcoding to stitch streaming digital content. A selection of a content file is received from a mobile device. An advertisement content file is identified for the selected content file. Attributes of the selected content file are determined. Attributes of the advertisement content file are determined. The advertisement content file and the selected content file are converted so that the attributes of the advertisement content file and the attributes of the selected content file match. The selected content file is stitched with the advertisement content file to produce streaming digital content. The streaming digital content is provided to the mobile device.

Abstract: In various embodiments, a method is described that includes receiving, at one or more computer systems, one or more ad network optimization factors corresponding to a plurality of ad networks registered with the one or more computer systems; analyzing, by the one or more computer systems, logged performance data corresponding to one or more previous ad requests routed to the plurality of ad networks over a predefined period of time; and generating, by the one or more computer systems, an optimal ad network distribution for future ad requests to be routed to the plurality of ad networks based on the analyzed logged performance data and the one or more ad network optimization factors.