Guides and pricing comparisons on OCR, AI document data extraction, and intelligent document processing for teams evaluating tools.
Amazon Textract confidence runs 0 to 100, not 0 to 1. What AWS recommends as a threshold, how identification and qualification confidence differ, and why a per-field threshold flags far more documents than the field rate suggests.
Read articleTeams leave FineReader over its output and its 5,000 page automation cap, not its accuracy. Here is what each realistic alternative returns, what it costs per 1,000 pages, and the volume where a desktop license stops stretching.
Read articleIf Tesseract is failing you on invoices, the problem is not its accuracy. It returns text and coordinates, and an invoice pipeline needs named fields and a cell grid. Here is what each alternative actually gives you back, and what it costs to run.
Read articledots.ocr has the best table score of any open model its size, and three practical problems: it was renamed in March 2026, it will not run on the cheapest GPU you can rent, and there is no hosted API. Here is what to use instead, compared on the column that matters for invoices.
Read articleSelf-hosted MinerU raises no data residency question at all. The hosted MinerU API is documented to time out on AWS and GitHub URLs, which is a real blocker for US teams. The alternatives for both cases, ranked on table accuracy rather than the composite score.
Read articleDeepSeek-OCR 2 reads prose well and reconstructs grids poorly. For invoices and statements that is the wrong trade. The alternatives ranked by the column that matters, with the license traps and the break-even.
Read articlePaddleOCR leads on English at 0.071 edit distance against Tesseract at 0.096, but only if you switch to the English-specific recognizer. Costs, licenses and the layer no open-source engine covers.
Read articleThree of the four leading open source document parsers show a permissive license badge on GitHub and attach commercial conditions somewhere else. Docling is the one that does not. Here is the license, benchmark and cost comparison for teams choosing a parser they intend to ship.
Read articleAzure prices document extraction on three inputs: which model you call, how many pages you send it and how you deploy it. Here is the arithmetic, three worked examples at real volumes, and the four line items that turn a clean estimate into a surprising invoice.
Read articleForwarders replace ABBYY when the document set stops matching the templates. Here is why bills of lading break template capture, what the real alternatives are, and how to test them in a week.
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