--- title: "Best tools to extract tables from complex PDFs (2026)" canonical_url: "https://www.nutrient.io/blog/extract-tables-from-complex-pdfs/" md_url: "https://www.nutrient.io/blog/extract-tables-from-complex-pdfs.md" last_updated: "2026-10-27T18:59:26.684Z" description: "Best tools to extract tables from complex PDFs, compared on merged cells, borderless and scanned tables, multipage tables, output formats, and cell grounding." --- **TL;DR** - Choose Nutrient Data Extraction API when complex tables from PDFs and scans must come back as JSON with merged-cell spans, header flags, and a bounding box and confidence score on every cell. - There’s no universal best table extractor. Choose by merged cells, borderless layouts, scans, tables that run across pages, output format, and cell-level grounding. - Choose Camelot when born-digital tables need a local Python library. - Choose Reducto when a hosted parser should cite cells and join tables that continue onto the next page. - Choose a hyperscaler document API when the rest of the pipeline already runs in that cloud. Nutrient Data Extraction API is the pick for extracting tables from complex PDFs when each table has to arrive as JSON, with row and column spans for merged cells, header flags, and a bounding box and confidence score on every cell. Camelot is the pick when tables live in born-digital PDFs and a local Python library is enough. Tabula is the pick for a one-off CSV export of a text-based table. pdfplumber is the pick when a developer wants to tune table detection by hand. Docling is the pick when table structure has to be recovered locally, including from scans. Reducto and LlamaParse are the hosted parsers that document joining tables across pages. Amazon Textract, Azure Document Intelligence, and Google Document AI fit teams committed to one cloud. Adobe PDF Extract API and ABBYY round out the field. The hardest table in your corpus decides the choice. Almost every tool here handles a ruled table in a born-digital PDF. Two-level headers, borderless columns, scanned statements, and tables that continue on the next page are where they diverge. ## What makes a PDF table “complex” A PDF doesn’t store a table. It stores characters, lines, and coordinates, and the extractor infers rows, columns, and headers from them. Four patterns cause most failures: - **Merged cells.** A header such as “Q3 2026” spans two columns. Flattening it shifts every value under it. - **Borderless tables.** Whitespace is the only column separator, so the extractor guesses where columns end. - **Scanned tables.** There’s no text layer, so optical character recognition (OCR) has to read the cells first. - **Tables across pages.** The tool has to decide whether page 5 starts a new table or continues the old one. ## Criteria that matter in production ### Merged cells and headers Check whether the output carries row and column spans and marks header cells, or only returns a grid of strings. Markdown tables can’t represent merged cells, so Markdown-only output flattens them. ### Borderless and scanned tables Test whitespace-separated columns and scans as their own slice. Confirm whether OCR runs in the same call or needs a separate package or mode. ### Tables across pages Find out whether the tool joins continued tables, offers an option to, or leaves stitching to your code, and how it decides two tables belong together. ### Output format Decide whether the consumer needs Excel, CSV, JSON with cell coordinates, Markdown or HTML for a large language model (LLM), or a pandas DataFrame. Converting later usually loses the spans. ### Cell-level grounding For review and audit, each cell should carry its page position and a confidence signal. Treat confidence as a routing signal, not a probability that a value is correct. ### Throughput, deployment, and cost Check page and file limits, asynchronous jobs, and whether documents can leave your infrastructure. A free library still costs engineering time at volume. ## Tools to extract tables from complex PDFs at a glance This table summarizes what each vendor documents. It isn’t a ranking. | Tool | Class | Merged cells and headers | Scanned tables | Tables across pages | Output | Cell grounding | | ---------------------------------------------------- | ---------------------------- | ------------------------------------------------ | ----------------------------- | ------------------------------------ | -------------------------------------------------------- | ------------------------------------------------- | | [Nutrient Data Extraction API](https://www.nutrient.io/api/table-extraction-api/) | Hosted table and parsing API | `rowSpan`, `colSpan`, and `isHeader` per cell | Yes, OCR in `understand` mode | Not described; stitch in code | JSON, Markdown with HTML tables; Excel via Processor API | Bounds and confidence on every cell | | [Adobe PDF Extract API](https://developer.adobe.com/document-services/docs/overview/pdf-extract-api/) | Hosted extraction API | Per-cell contents and formatting | Native or scanned PDFs | Not described | JSON, plus CSV, XLSX, and PNG table renditions | Bounds on elements | | [Azure Document Intelligence](https://learn.microsoft.com/en-us/azure/ai-services/document-intelligence/prebuilt/layout?view=doc-intel-4.0.0) | Cloud layout model | Row and column spans, column headers | Yes | Split and post-process, per the docs | JSON, Markdown with HTML tables | Bounding polygon per cell | | [Amazon Textract](https://docs.aws.amazon.com/textract/latest/dg/how-it-works-tables.html) | Cloud document analysis | `MERGED_CELL` blocks, titles, footers, headers | Yes | Not covered in the tables guide | Block JSON, CSV through sample code | Geometry and confidence per block | | [Google Document AI](https://docs.cloud.google.com/document-ai/docs/layout-parse-chunk) | Cloud processors | Layout Parser documents merged cells and headers | Yes, OCR in Form Parser | May split into two tables | Document JSON, chunks | Not described for Layout Parser tables | | [ABBYY FineReader](https://help.abbyy.com/assets/en-us/finereader/16/Users_Guide.pdf) | OCR desktop app and SDK | Manual merge and split tools | Yes | Not described | Excel and other editable formats | Desktop review in the OCR editor | | [Reducto](https://docs.reducto.ai/configs/parse/table-output-formats) | Hosted parsing platform | HTML output preserves merged cells | Yes | `merge_tables` option | HTML, Markdown, JSON, CSV | Cell boxes with `return_citations` | | [LlamaParse](https://developers.llamaindex.ai/llamaparse/parse/guides/configuring-parse/) | Hosted parser | Cell structure preserved; HTML tables option | Yes | `merge_continued_tables` option | Markdown, HTML tables, JSON, XLSX | Word, line, and cell boxes with `granular_bboxes` | | [Docling](https://docling-project.github.io/docling/) | Open source local converter | Table structure recognition | Yes, OCR support | Not described | Markdown, HTML, JSON, DataFrame to CSV | Lossless JSON export | | [Camelot](https://github.com/camelot-dev/camelot) | Open source Python library | Lattice and ML parsers for ruled and borderless | With the `[ml,ocr]` extras | `stack_contiguous()` | DataFrame, CSV, JSON, Excel, HTML, Markdown | Per-table accuracy and confidence metrics | | [Tabula](https://tabula.technology/) | Open source desktop app | Lattice and stream modes | No, text-based PDFs only | Not described | CSV, TSV, JSON | None | | [pdfplumber](https://github.com/jsvine/pdfplumber) | Open source Python library | Line and text strategies you tune | No, machine-generated PDFs | Not described | Python lists of rows | Cell boxes through `Table.cells` | ## Twelve tools compared ### 1. Nutrient Data Extraction API [Nutrient Data Extraction API](https://www.nutrient.io/api/data-extraction-api/) returns each table as an element from the [parse endpoint](https://www.nutrient.io/guides/dws-data-extraction/parsing.md), `POST /extraction/parse`. A [table element](https://www.nutrient.io/guides/dws-data-extraction/parsing/extract-document-elements.md) carries `rowCount`, `columnCount`, and `cells`, and each cell has its `row`, `column`, `rowSpan`, `colSpan`, `isHeader` flag, text, bounding box, and confidence score. A two-level header rebuilds as printed. Wrapped rows stay together as one row when detected, and `captionIds` and `footnoteIds` link the table to its caption and footnotes. Scanned PDFs go through OCR before the tables are read. The [table extraction API](https://www.nutrient.io/api/table-extraction-api/) page recommends `understand` mode for tables, at 9 credits per page. `structure` mode, at 1.5 credits, can miss complex table structure, and `text` mode returns no table elements. `auto` is the recommended starting mode for mixed documents. Ask for Markdown, and tables arrive as HTML tables with `rowspan` and `colspan`, ready for a retrieval-augmented generation (RAG) index. For spreadsheets, the sibling Nutrient DWS Processor API’s [PDF-to-Excel API](https://www.nutrient.io/api/pdf-to-excel-api/) returns an XLSX workbook with rows and columns preserved. CSV and XML output are in development. Each table element carries one page reference, and the parse guide doesn’t describe joining continued tables, so stitch those in your code. The free plan includes 5,000 Data Extraction API credits a month with no credit card required, and the [Python SDK for PDF data extraction](https://www.nutrient.io/sdk/python/pdf-data-extraction/) runs table extraction on your own infrastructure. Choose Nutrient when complex tables must arrive as JSON with spans, header flags, and cell-level bounds and confidence a reviewer can check. ### 2. Adobe PDF Extract API [Adobe PDF Extract API](https://developer.adobe.com/document-services/docs/overview/pdf-extract-api/) extracts native or scanned PDFs into JSON, with tables “extracted and parsed with the contents and table formatting information delivered for each cell.” Table data can also be written as CSV and XLSX, plus PNG images for visual checks. The [Extract API how-to](https://developer.adobe.com/document-services/docs/overview/pdf-extract-api/howtos/extract-api/) lists limits of 400 pages for non-scanned PDFs, 150 for scanned PDFs, and 100 MB per file, lower for files with many tables. Choose Adobe PDF Extract API when tables are headed for spreadsheets and the team already uses Adobe PDF Services. ### 3. Azure Document Intelligence The [Azure Document Intelligence layout model](https://learn.microsoft.com/en-us/azure/ai-services/document-intelligence/prebuilt/layout?view=doc-intel-4.0.0) returns tables with row and column counts, spans, cell bounding polygons, and a `columnHeader` kind, including rotated tables. With `outputContentFormat=markdown`, v4.0 returns tables as HTML so merged cells and multirow headers survive. For tables that span pages, Microsoft suggests splitting the PDF and post-processing the pages into one table. XLSX input isn’t supported for table analysis. Choose Azure Document Intelligence when the application runs on Azure and Markdown with HTML tables suits the consumer. ### 4. Amazon Textract [Amazon Textract](https://docs.aws.amazon.com/textract/latest/dg/how-it-works-tables.html) returns tables from `AnalyzeDocument` or the asynchronous `GetDocumentAnalysis` with the `TABLES` feature. The response is a graph of blocks: a `TABLE` marked structured or semistructured, `CELL` blocks with row and column indexes, and `MERGED_CELL` blocks for merged cells. Cells can be tagged as column headers, section titles, titles, footers, or summary cells, and every block carries geometry and confidence. Your code walks the block graph to rebuild the grid. Choose Amazon Textract when documents already land in Amazon S3 and the team can own the block-to-table conversion. ### 5. Google Document AI [Google Document AI](https://docs.cloud.google.com/document-ai/docs/layout-parse-chunk) Layout Parser “excels at extracting data from complex tables with merged cells and intricate headers” and builds chunks that carry table headers. Its documentation warns that PDF “tables spanning multiple pages might be split in two tables” and caps online processing at 15 pages per PDF, or 500 in batch. [Form Parser](https://docs.cloud.google.com/document-ai/docs/form-parser) extracts simple tables with no spanning cells from images and PDFs. Choose Google Document AI when table-aware chunks feed a retrieval system on Google Cloud. ### 6. ABBYY FineReader [ABBYY FineReader PDF](https://help.abbyy.com/assets/en-us/finereader/16/Users_Guide.pdf) is a desktop OCR application that converts PDFs and scans to Excel. When a table isn’t detected, its user guide has the operator draw a table area, run Analyze Table Structure, and fix rows and columns with split and merge tools. Developers use [ABBYY FineReader Engine](https://www.abbyy.com/finereader-engine/), an OCR SDK for Windows, Linux, or Mac, deployable on premises. Choose ABBYY when operators correct scanned tables by hand or an on-premises OCR SDK is required. ### 7. Reducto [Reducto](https://docs.reducto.ai/configs/parse/table-output-formats) returns tables as `dynamic`, `html`, `md`, `json`, `jsonbbox`, or `csv`, and says HTML is the only format that preserves merged cells. Its `merge_tables` option combines consecutive tables with the same column count, with a warning that different tables with matching column counts may be merged incorrectly. With [`return_citations`](https://docs.reducto.ai/configs/parse/citations), table blocks list each cell with its indexes and page box. Deployment covers software as a service (SaaS), hybrid or full virtual private cloud (VPC), and air-gapped on premises. Choose Reducto when cell citations, a cross-page merge option, and VPC or air-gapped deployment lead the evaluation. ### 8. LlamaParse [LlamaParse](https://developers.llamaindex.ai/llamaparse/parse/) runs in four tiers, from `fast` to `agentic_plus`, and recommends the agentic tiers for scans, real tables, and dense financial reports. Its [configuration options](https://developers.llamaindex.ai/llamaparse/parse/guides/configuring-parse/) include HTML tables, `merge_continued_tables`, XLSX table export, and `granular_bboxes` for word, line, and cell boxes. Tiers can be pinned to a release date, and self-hosting is available. Choose LlamaParse when parsed tables feed a LlamaIndex pipeline and continued tables should be merged. ### 9. Docling [Docling](https://docling-project.github.io/docling/) is an MIT-licensed converter that runs locally, including air-gapped. It covers layout, reading order, table structure, and OCR for scans, and exports Markdown, HTML, and lossless JSON. Its [table export example](https://github.com/docling-project/docling/blob/main/docs/examples/export_tables.py) turns each table into a pandas DataFrame and saves CSV and HTML. In Nutrient’s [opendataloader-bench run](https://www.nutrient.io/blog/pdf-extraction-benchmark-opendataloader-bench.md), docling 2.110.0 scored 0.93 on tree edit distance similarity (TEDS), the table structure metric. Choose Docling when table structure has to be recovered on your own hardware and the team can run the models. ### 10. Camelot [Camelot](https://github.com/camelot-dev/camelot) 2.0.0 is an MIT-licensed Python library built only for tables. It ships `lattice` for ruled tables, `stream` and `network` for whitespace-separated ones, and an optional `ml` parser for hard borderless tables. Its built-in parsers need a text-based PDF, and scans need the `[ml,ocr]` extras. Tables come back as pandas DataFrames with CSV, JSON, Excel, HTML, Markdown, and SQLite export, a per-table parsing report, and `stack_contiguous()` to join continued tables. Choose Camelot when tables sit in born-digital PDFs and a configurable local library is enough. ### 11. Tabula [Tabula](https://tabula.technology/) is a free, open source tool: Draw a box around a table and export CSV or Excel. Its site says it “only works on text-based PDFs, not scanned documents,” and its desktop release is 1.2.1 from 2018. The [tabula-java](https://github.com/tabulapdf/tabula-java) library offers lattice and stream modes with CSV, TSV, and JSON output, and tabula-py wraps it for Python. Choose Tabula when a person needs a one-off CSV export of a text-based table. ### 12. pdfplumber [pdfplumber](https://github.com/jsvine/pdfplumber) is an MIT-licensed Python library for inspecting PDF characters, lines, and rectangles. `find_tables()` and `extract_tables()` use `lines`, `text`, or `explicit` strategies with tolerance settings, and visual debugging shows what the detector saw. Its README says it “works best on machine-generated, rather than scanned, PDFs” and lists OCR as out of scope. Choose pdfplumber when a developer needs fine-grained control over table detection in born-digital PDFs. ## Scenario-based recommendations Each recommendation depends on the scenario. No tool wins every table. - Choose Nutrient when complex tables from PDFs and scans must arrive as JSON with spans, header flags, and per-cell bounds and confidence. - Choose Adobe PDF Extract API when CSV and XLSX table renditions should come from the same Adobe call. - Choose Azure Document Intelligence when Markdown with HTML tables must come from an Azure-hosted model. - Choose Amazon Textract when tables are part of an AWS pipeline that already uses Textract blocks. - Choose Google Document AI when table-aware chunks feed a retrieval system on Google Cloud. - Choose ABBYY when people correct scanned tables by hand. - Choose Reducto when cell citations and a cross-page merge option must run in a VPC or air-gapped deployment. - Choose LlamaParse when continued tables should be merged inside a LlamaIndex pipeline. - Choose Docling when table structure has to be recovered locally, including from scans. - Choose Camelot when born-digital tables need ruled, borderless, and multipage handling in Python. - Choose Tabula when a one-off CSV export from a text-based PDF is the whole job. - Choose pdfplumber when a developer wants to tune table detection rules by hand. ## Run a fair proof of concept 1. Collect 30–50 tables you actually receive: ruled and borderless, born-digital and scanned, two-level headers, and at least five that continue across pages. 2. Write the expected output for each by hand, including spans and header rows. 3. Score structure and text separately. Right text in the wrong cells still breaks the next step. 4. Check cell coordinates where a tool returns them, and test the continuation rule with one continued table and one new table with the same column count. 5. Measure throughput and monthly cost, including OCR, retries, and review time. ## FAQ #### What is the best tool to extract tables from complex PDFs? Nutrient Data Extraction API is the pick when complex tables from PDFs and scans must come back as JSON with row and column spans, header flags, and a bounding box and confidence score on every cell. Camelot and pdfplumber fit born-digital PDFs processed locally in Python, and Docling fits local processing that includes scans. Reducto and LlamaParse document merging tables across pages, and the hyperscaler APIs fit teams already on those clouds. Test each on your hardest tables. #### What is the best table extraction API? Nutrient’s table extraction API is the pick when one REST call should return tables as JSON with merged-cell spans and per-cell confidence, as Markdown with HTML tables, or as an Excel workbook. Adobe PDF Extract API returns table JSON with CSV and XLSX renditions. Amazon Textract, Azure Document Intelligence, and Google Document AI return tables in their own cloud formats. Reducto and LlamaParse offer table options inside broader parsing platforms. #### How do I extract tables with merged cells from a PDF? Nutrient Data Extraction API returns each cell with `rowSpan`, `colSpan`, and an `isHeader` flag, so merged cells and two-level headers rebuild as printed, and its Markdown output uses HTML tables with `rowspan` and `colspan`. Avoid plain Markdown tables for this job, since they flatten merged cells. Reducto and Azure Document Intelligence document HTML output for the same reason, and Amazon Textract groups merged cells in `MERGED_CELL` blocks. #### Can I extract tables from scanned PDFs? Nutrient Data Extraction API runs OCR on scanned tables in `understand` mode and returns table elements with a confidence score for each cell. Adobe PDF Extract API, Amazon Textract, Azure Document Intelligence, Google Document AI, ABBYY, Reducto, LlamaParse, and Docling also handle scans. Tabula and pdfplumber need a text layer, and Camelot reads scans only with its `[ml,ocr]` extras. #### How do I handle tables that span multiple pages? Nutrient Data Extraction API returns each table element with its own page reference and doesn’t document joining continued tables, so stitch them in your code by matching column counts and header cells. Reducto’s `merge_tables`, LlamaParse’s `merge_continued_tables`, and Camelot’s `stack_contiguous()` join continued tables. Google’s Layout Parser may split a spanning table in two, and Azure suggests post-processing pages into one table. Review merged output either way. #### Are Camelot and Tabula good enough for complex PDF tables? Nutrient treats them as solid baselines for born-digital PDFs, not for scans without extra setup. Camelot handles ruled tables with `lattice`, targets borderless ones with `network` and `ml`, and joins continued tables. Tabula works only on text-based PDFs, and its desktop release dates from 2018. Neither returns per-cell confidence for review, so add your own checks. #### How accurate is PDF table extraction? Nutrient publishes its table scores by mode, including where it scores lower. On opendataloader-bench’s 200 PDFs, `understand` mode scores 0.94 on table structure (TEDS) in Nutrient’s internal test of the latest engine, which isn’t independently verified. On ParseBench, a benchmark from LlamaIndex, Nutrient’s public leaderboard row scores 72.1 on tables, and Nutrient’s internal test of the latest engine scores 86.0; both figures are on the benchmarks page. 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[Using Yarn](/blog/how-to-build-a-react-word-viewer.md) - [How To Build A Reactjs File Viewer](/blog/how-to-build-a-reactjs-file-viewer.md) - [How To Build A Reactjs Pdf Viewer With React Pdf](/blog/how-to-build-a-reactjs-pdf-viewer-with-react-pdf.md) - [or](/blog/how-to-build-a-reactjs-pdf-viewer.md) - [How To Build A Reactjs Viewer With Pdfjs](/blog/how-to-build-a-reactjs-viewer-with-pdfjs.md) - [How To Build A Vuejs Pdf Viewer With Pdfjs](/blog/how-to-build-a-vuejs-pdf-viewer-with-pdfjs.md) - [How To Build A Vuejs Pdf Viewer](/blog/how-to-build-a-vuejs-pdf-viewer.md) - [How To Build An Android Pdf Viewer](/blog/how-to-build-an-android-pdf-viewer.md) - [How To Build An Angular Pdf Viewer With Ng2 Pdf Viewer](/blog/how-to-build-an-angular-pdf-viewer-with-ng2-pdf-viewer.md) - [How To Build An Angular Pdf Viewer With Pdfjs](/blog/how-to-build-an-angular-pdf-viewer-with-pdfjs.md) - [How To Convert Docx To Pdf Using Javascript](/blog/how-to-convert-docx-to-pdf-using-javascript.md) - [How To Convert Docx To Pdf Using Python](/blog/how-to-convert-docx-to-pdf-using-python.md) - [How To Convert Html To Pdf Using Html2pdf](/blog/how-to-convert-html-to-pdf-using-html2pdf.md) - [How To Convert Html To Pdf Using React](/blog/how-to-convert-html-to-pdf-using-react.md) - [How To Convert Html To Pdf Using Wkhtmltopdf And Csharp](/blog/how-to-convert-html-to-pdf-using-wkhtmltopdf-and-csharp.md) - [or](/blog/how-to-convert-html-to-pdf-using-wkhtmltopdf-and-python.md) - [How To Convert Html To Pptx](/blog/how-to-convert-html-to-pptx.md) - [How To Convert Pdf To Json](/blog/how-to-convert-pdf-to-json.md) - [Quarterly report](/blog/how-to-convert-pdf-to-markdown-using-python.md) - [How To Convert Word To Pdf In Nodejs](/blog/how-to-convert-word-to-pdf-in-nodejs.md) - [How To Convert Word To Pdf Using Javascript](/blog/how-to-convert-word-to-pdf-using-javascript.md) - [or](/blog/how-to-create-a-react-js-signature-pad.md) - [How To Create Pdfs With React To Pdf](/blog/how-to-create-pdfs-with-react-to-pdf.md) - [How to digitally sign PDFs in C# with Nutrient .NET SDK](/blog/how-to-digitally-sign-pdf-in-csharp.md) - [How To Edit Pdfs Using Ios Pdf Library](/blog/how-to-edit-pdfs-using-ios-pdf-library.md) - [How To Embed A Pdf Viewer In Your Website](/blog/how-to-embed-a-pdf-viewer-in-your-website.md) - [How To Extract Tables From Pdf And Images](/blog/how-to-extract-tables-from-pdf-and-images.md) - [How To Generate Pdf From Html With Nodejs](/blog/how-to-generate-pdf-from-html-with-nodejs.md) - [How to generate PDFs in C# with Nutrient .NET SDK](/blog/how-to-generate-pdf-in-csharp.md) - [base_url tells WeasyPrint where to resolve relative asset paths](/blog/how-to-generate-pdf-reports-from-html-in-python.md) - [How To Merge Pdfs Using Javascript](/blog/how-to-merge-pdfs-using-javascript.md) - [How To Ocr Pdfs In Linux](/blog/how-to-ocr-pdfs-in-linux.md) - [How To Print Pdf In Csharp](/blog/how-to-print-pdf-in-csharp.md) - [How To Programmatically Create And Fill Pdf Form In Angular](/blog/how-to-programmatically-create-and-fill-pdf-form-in-angular.md) - [C# barcode scanner: How to scan and read 1D barcodes and QR codes](/blog/how-to-scan-barcodes-in-csharp.md) - [Open an image.](/blog/how-to-use-tesseract-ocr-in-python.md) - [From an HTML string.](/blog/html-in-pdf-format.md) - [Html To Pdf In Javascript](/blog/html-to-pdf-in-javascript.md) - [Ide Text Editors Cpp Large Scale](/blog/ide-text-editors-cpp-large-scale.md) - [Intelligent Data Extraction](/blog/intelligent-data-extraction.md) - [Invoice Approval Software](/blog/invoice-approval-software.md) - [Javascript Document Editor](/blog/javascript-document-editor.md) - [Javascript Pdf Editors](/blog/javascript-pdf-editors.md) - [Javascript Pdf Libraries](/blog/javascript-pdf-libraries.md) - [Keep Document Ai Private](/blog/keep-document-ai-private.md) - [Landing Ai Alternatives](/blog/landing-ai-alternatives.md) - [Langextract Vs Llamaindex Extraction Comparison](/blog/langextract-vs-llamaindex-extraction-comparison.md) - [Linearized Pdf](/blog/linearized-pdf.md) - [Uses OpenAI by default — set OPENAI_API_KEY.](/blog/llamaindex-vs-langchain-rag.md) - [Llamaindex Vs Langchain Vs Haystack](/blog/llamaindex-vs-langchain-vs-haystack.md) - [Llamaindex Workflows Vs Langgraph](/blog/llamaindex-workflows-vs-langgraph.md) - [Llamaparse Alternatives](/blog/llamaparse-alternatives.md) - [Llm Vs Document Parsing Api](/blog/llm-vs-document-parsing-api.md) - [Low Code No Code Document Integrations](/blog/low-code-no-code-document-integrations.md) - [One segment per document found, in page order:](/blog/mailroom-automation-api.md) - [Material Requisition](/blog/material-requisition.md) - [or](/blog/merge-pdfs.md) - [Migrating Observability Hyperdx To Dash0](/blog/migrating-observability-hyperdx-to-dash0.md) - [Swift Package Manager](/blog/mobile-pdf-sdk.md) - [Numeric and identifier fields: exact single-block matches only.](/blog/mortgage-document-processing.md) - [`elements` come from your document parser — each has a type and content.](/blog/multimodal-rag.md) - [Multipage Extraction Page Boundaries](/blog/multipage-extraction-page-boundaries.md) - [Nutrient Flutter 6 Bindings Api](/blog/nutrient-flutter-6-bindings-api.md) - [Nutrient Flutter Bindings Architecture](/blog/nutrient-flutter-bindings-architecture.md) - [Nutrient Vs Conga Composer](/blog/nutrient-vs-conga-composer.md) - [Ocr Api Comparison](/blog/ocr-api-comparison.md) - [Online Document Viewer](/blog/online-document-viewer.md) - [Open Pdf In Your Web App](/blog/open-pdf-in-your-web-app.md) - [Operations Management Software](/blog/operations-management-software.md) - [Optical Character Recognition In Scanned Pdfs](/blog/optical-character-recognition-in-scanned-pdfs.md) - [CPU](/blog/paddleocr-python-guide.md) - [PDF accessibility for developers: Meeting WCAG 2.2, Section 508, and PDF/UA with an SDK](/blog/pdf-accessibility.md) - [Extract data from PDF files: A developer guide to structured data from PDFs and scans](/blog/pdf-data-extraction-developer-guide.md) - [Pdf Extraction Benchmark Opendataloader Bench](/blog/pdf-extraction-benchmark-opendataloader-bench.md) - [Pdf Extraction Document Case Studies](/blog/pdf-extraction-document-case-studies.md) - [Pdf Page Labels](/blog/pdf-page-labels.md) - [Pdf Sdk Compliance Security Checklist](/blog/pdf-sdk-compliance-security-checklist.md) - [Pdf Sdk Performance Benchmark](/blog/pdf-sdk-performance-benchmark.md) - [Pdf Ua Compliance Guide](/blog/pdf-ua-compliance-guide.md) - [Pdf Ua Validation](/blog/pdf-ua-validation.md) - [Pdfjs Accessibility Structtree Printing](/blog/pdfjs-accessibility-structtree-printing.md) - [Pdfjs Advanced Loading Streaming Workers](/blog/pdfjs-advanced-loading-streaming-workers.md) - [Pdfjs Annotation Editor Layer](/blog/pdfjs-annotation-editor-layer.md) - [Pdfjs Area Annotations Canvas Capture](/blog/pdfjs-area-annotations-canvas-capture.md) - [Pdfjs Coordinate Systems Pdf To Screen](/blog/pdfjs-coordinate-systems-pdf-to-screen.md) - [Pdfjs Document Outline Bookmarks Metadata](/blog/pdfjs-document-outline-bookmarks-metadata.md) - [Pdfjs Eventbus Guide](/blog/pdfjs-eventbus-guide.md) - [macOS](/blog/pdfjs-file-format-conversion-to-pdf.md) - [macOS](/blog/pdfjs-generating-pdf-thumbnails-pdf2pic.md) - [Pdfjs Limitations Commercial Upgrade](/blog/pdfjs-limitations-commercial-upgrade.md) - [Pdfjs Native Annotation Layer Forms](/blog/pdfjs-native-annotation-layer-forms.md) - [Pdfjs Navigation Zoom Rotation](/blog/pdfjs-navigation-zoom-rotation.md) - [Pdfjs Pdf Page Manipulation Pdf Lib](/blog/pdfjs-pdf-page-manipulation-pdf-lib.md) - [Pdfjs React Viewer Setup](/blog/pdfjs-react-viewer-setup.md) - [Pdfjs Rendering Overlays React Portals](/blog/pdfjs-rendering-overlays-react-portals.md) - [Pdfjs Server Side Text Extraction](/blog/pdfjs-server-side-text-extraction.md) - [Pdfjs Sticky Note Annotations](/blog/pdfjs-sticky-note-annotations.md) - [Pdfjs Text Highlight Annotations](/blog/pdfjs-text-highlight-annotations.md) - [Pdfjs Text Search Pdffindcontroller](/blog/pdfjs-text-search-pdffindcontroller.md) - [Pdfjs Thumbnail Sidebar](/blog/pdfjs-thumbnail-sidebar.md) - [Pdfplumber Python Guide](/blog/pdfplumber-python-guide.md) - [People Process Tools](/blog/people-process-tools.md) - [Process Flows](/blog/process-flows.md) - [React Docx Editor](/blog/react-docx-editor.md) - [React Native Pdf Annotation](/blog/react-native-pdf-annotation.md) - [React Pdf Annotation Layer Forms](/blog/react-pdf-annotation-layer-forms.md) - [React Pdf Custom Rendering Hooks](/blog/react-pdf-custom-rendering-hooks.md) - [Using Yarn](/blog/react-pdf-editor.md) - [React Pdf Loading States Errors Passwords](/blog/react-pdf-loading-states-errors-passwords.md) - [React Pdf Non Latin Fonts Special Pdfs](/blog/react-pdf-non-latin-fonts-special-pdfs.md) - [React Pdf Outline Table Of Contents](/blog/react-pdf-outline-table-of-contents.md) - [React Pdf Performance Optimization](/blog/react-pdf-performance-optimization.md) - [React Pdf Setup Basic Rendering](/blog/react-pdf-setup-basic-rendering.md) - [React Pdf Text Layer Custom Renderer](/blog/react-pdf-text-layer-custom-renderer.md) - [React Pdf Thumbnails Page Navigation](/blog/react-pdf-thumbnails-page-navigation.md) - [Reducto Alternatives](/blog/reducto-alternatives.md) - [Requisition System](/blog/requisition-system.md) - [labels.py](/blog/route-documents-automatically-classify-api.md) - [or](/blog/sample-blog-updated.md) - [Sdk Product Updates Q2 2026](/blog/sdk-product-updates-q2-2026.md) - [System Of Record Vs Source Of Truth](/blog/system-of-record-vs-source-of-truth.md) - [Add DWS MCP Server to your Claude Code project.](/blog/teaching-llms-to-read-pdfs.md) - [Open an image file.](/blog/tesseract-python-guide.md) - [The Six Best Pdf Generator Apis](/blog/the-six-best-pdf-generator-apis.md) - [Define the HTML part of the document.](/blog/top-10-ways-to-generate-pdfs-in-python.md) - [Top 5 Javascript Pdf Viewers](/blog/top-5-javascript-pdf-viewers.md) - [Top Js Pdf Libraries](/blog/top-js-pdf-libraries.md) - [Top Ten Ways To Convert Html To Pdf](/blog/top-ten-ways-to-convert-html-to-pdf.md) - [Unstructured Alternatives](/blog/unstructured-alternatives.md) - [Using Javascript In Pdf Form Fields](/blog/using-javascript-in-pdf-form-fields.md) - [Vector Pdf](/blog/vector-pdf.md) - [Wcag2 Accessibility Requirements Documents](/blog/wcag2-accessibility-requirements-documents.md) - [Web Sdk Is Now Headless](/blog/web-sdk-is-now-headless.md) - [What Are Annotations](/blog/what-are-annotations.md) - [What Is A Vpat](/blog/what-is-a-vpat.md) - [What Is Bpms](/blog/what-is-bpms.md) - [What Is Business Logic](/blog/what-is-business-logic.md) - [What Is Document Processing](/blog/what-is-document-processing.md) - [What Is Intelligent Document Processing](/blog/what-is-intelligent-document-processing.md) - [What Is Ocr Invoice Processing](/blog/what-is-ocr-invoice-processing.md) - [What Is Pdf Ua](/blog/what-is-pdf-ua.md) - [Why Pdfium Is A Trusted Platform For Pdf Rendering](/blog/why-pdfium-is-a-trusted-platform-for-pdf-rendering.md) - [Why Your Ai Agent Hallucinates Pdf Table Data](/blog/why-your-ai-agent-hallucinates-pdf-table-data.md) - [Workflow Analysis](/blog/workflow-analysis.md)