Databricks is used by an engineering team for invoice data processing via AI functions and experimentation with Databricks Genie.

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    "summary": "Databricks is used by an engineering team for invoice data processing via AI functions and experimentation with Databricks Genie.",
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      {
        "url": "https://www.reddit.com/r/Rag/comments/1xkb6p7/comment/19rxn58o0cjgk/",
        "depth": 0,
        "score": 11,
        "author": "I_HALF_CATS",
        "excerpt": "I have a benchmark page I make for myself maintained / updated by an AI every week.\n\n https://bench.voshart.com/ocr\n\n That I think answers some of your questions",
        "posted_at": "2026-10-31T14:42:23.000Z",
        "author_url": "https://www.reddit.com/user/I_HALF_CATS/"
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      {
        "url": "https://www.reddit.com/r/Rag/comments/1xkb6p7/comment/19rxnbm7wobr5/",
        "depth": 0,
        "score": 5,
        "author": "elimelis",
        "excerpt": "I use LlamaParser, it has free version to try",
        "posted_at": "2026-10-31T14:46:22.000Z",
        "author_url": "https://www.reddit.com/user/elimelis/"
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      {
        "url": "https://www.reddit.com/r/Rag/comments/1xkb6p7/comment/19rxpc5r50f43/",
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        "author": "Significant_Tune9219",
        "excerpt": "Keep the split you already have: pdfplumber when the PDF has a real text layer, and RapidOCR only when that layer is missing or tiny. The failure I keep seeing isn't a blurry scan, it's a confident wrong total, where two line items get merged and the model still looks sure. Reject uploads that are rotated or come back empty after OCR, and for the rest store a confidence on each field. Don't post a",
        "posted_at": "2026-10-31T15:31:32.000Z",
        "author_url": "https://www.reddit.com/user/Significant_Tune9219/"
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        "author": "teroknor92",
        "excerpt": "The models and tools you mentioned will give you OCR text. However, if you want to extract structured data across different document formats you will find most success with using LLMs for it or tools such as ParseExtract and LlamaExtract are easier to use, as they can directly extract structured JSON data from various formats.\nIf the document format is relatively consistent, you can simply perform",
        "posted_at": "2026-10-31T16:28:19.000Z",
        "author_url": "https://www.reddit.com/user/teroknor92/"
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        "depth": 0,
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        "author": "Ok-Cauliflower8805",
        "excerpt": "Llamaparse is simply the best. But quite expensive. Especially if using Agentic Plus.\n\n Happy to be proven wrong",
        "posted_at": "2026-10-31T16:53:39.000Z",
        "author_url": "https://www.reddit.com/user/Ok-Cauliflower8805/"
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        "author": "LawfulnessOptimal597",
        "excerpt": "Invoicing is very very difficult as the layouts can often be totally wild and incredibly difficult for a human. This is one of the additional reasons for the electronic invoicing laws coming into power across Europe. Some have already mandated and others roll out the requirement next year. Starting next year pretty much all European B2B invoicing must be electronic. In Germany it’s either XRechnun",
        "posted_at": "2026-10-31T18:37:23.000Z",
        "author_url": "https://www.reddit.com/user/LawfulnessOptimal597/"
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        "author": "liltingly",
        "excerpt": "TL;DR -- if I had to do it again, I'd go with the the simplest stack, and the highest precision way to identify defects (vote based or multi-modal agreement). Try and keep the defect identification and correction as deterministic for as long as possible.\n\n How varied are your templates? The two you've flagged are good for extracting. Neither is good at the \"structured\" party, though you can feed e",
        "posted_at": "2026-10-31T20:19:10.000Z",
        "author_url": "https://www.reddit.com/user/liltingly/"
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        "url": "https://www.reddit.com/r/Rag/comments/1xkb6p7/comment/19ryupebhiiys/",
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        "author": "hazyhaar",
        "excerpt": "pdfast",
        "posted_at": "2026-11-01T06:59:01.000Z",
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    "evidence": [
      "[comment u/WorldOfUmbro] We have a pipeline in Databricks with their AI functions. We’ve also experimented with Genie, to actually reason over the invoice data. Yet to try out the volumes feature there."
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    "post_date": "2026-10-31T14:08:50.000Z",
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    "post_text": "Looking for recommendations: Best PDF parser / OCR for extracting invoice data\n\nHas anyone worked on invoice parsing or document extraction and experimented with different PDF parsers or OCR solutions?\n\nI'm building an application that needs to extract structured data from invoices in different formats and layouts.\n\nCurrently, I'm using:\n\nPDFPlumber – For text-based PDFs.\n\nRapidOCR – For scanned PDFs or image-based invoices.\n\nI'm looking for a reliable solution that can handle different invoice formats, layouts, and varying document quality.\n\nA few things I'm trying to figure out:\n\nWhich PDF parser or OCR solution works best for extracting structured invoice data?\n\nHow well do these tools handle poor-quality scans, blurry images, rotated documents, etc.?\n\nIs it better to reject low-quality uploads and ask users to upload a clearer document, or are there solutions that can reliably handle poor-quality images?\n\nHave you tried any alternatives like PaddleOCR, Tesseract, Docling, Marker, or cloud-based solutions?\n\nI'm particularly interested in real-world experience rather than just library recommendations.\n\nIf you've built something similar, I'd love to know what worked well for you and what you'd recommend.",
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    "post_title": "Best PDF parser / OCR for extracting structured data from invoices – What works in production?",
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    "source_url": "https://www.reddit.com/r/Rag/comments/1xkb6p7/best_pdf_parser_ocr_for_extracting_structured/",
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    "products_mentioned": [
      "AI functions",
      "Genie"
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