Tested it with the following documents: * Loan application form: It picks up checkboxes and handwriting. But it missed a lot of form fields. Not sure why? * E

Tested it with the following documents: * Loan application form: It picks up checkboxes and handwriting. But it missed a lot of form fields. Not sure why? * Edsger W. Dijkstra’s handwritten notes(from Texas univ archive) - Parsing is good.* * Badly(misaligned) scanned bill - Parsing is good. Observation: there is a name field, but it produced a synonymous name instead of the name in the bill — hallucination?? * Investment fund factsheet - It could parse the bar charts and tables, but it whimsically excluded many vital data points from the document. * Investment fund factsheet, complex tables - Bad extraction, could not extract merged tables and again whimsical elimination of rows and columns. Anyone curious, try LLMWhisperer[1] for OCR. It doesn't use LLMs, so no hallucination side effects. It also preserves the layout of the input document for more context and clarity. There's also Docling[2], which is handy for converting tables from PDFs into markdown. While it uses Tesseract/EasyOCR under the hood, which can sometimes make the OCR results a bit less accurate [1] - https://pg.llmwhisperer.unstract.com/ https://pg.llmwhisperer.unstract.com/ [2] - https://github.com/DS4SD/docling https://github.com/DS4SD/docling