Abstract: An electronic computing system receives a document and identifies steps for processing the document. Each step is associated with a respective machine learning model trained to generate an output. The system subdivides content of the document into a plurality of chunks. For each step and for each chunk, the system applies the respective machine learning model to the chunk to generate an output and a confidence value. The system compares the confidence value to a threshold value. In accordance with a determination that the confidence value exceeds the threshold value, the system stores the output as final output for the chunk and the step. In accordance with a determination that the confidence value does not exceed the threshold value, the system requests user input for the chunk and the step, and the system stores received user input as final output for the chunk and step.