--- title: "Unstructured" type: "AI Tool" url: "https://aidemos.com/tools/unstructured" description: "We converted scanned, text-heavy PDFs to Markdown and preserved reading order, but tables flattened, images dropped, and charts turned noisy." category: "developer-tools" website: "https://unstructured.io/" published: "2026-08-19T17:50:52.336586+00:00" updated: "2026-08-19T17:53:06.338150+00:00" --- # Unstructured Good for text-first PDF-to-Markdown workflows, but not for faithful tables, charts, or images. ## TL;DR Verdict **Strong on prose, weak on structure-heavy PDF elements** **Where it wins:** - You want an open-source PDF-to-Markdown parser you can run locally or in your own infrastructure. - Your PDFs are mostly prose with scanned pages, and you care about preserving reading order. - You can tolerate flattened headings and missing images if the text extraction is strong. **Main limitation:** You need faithful chart preservation or chart-to-data extraction. **Pricing:** Open source $0 `Open source` · `Scanned OCR` · `Complex tables` · `Reading order` **Website:** [Visit Unstructured](https://unstructured.io/) > **Strong on prose, weak on structure-heavy PDF elements** > > Unstructured is reliable for narrative OCR and reading order, including scanned pages, but this benchmark shows flattened headings, dropped images, noisy charts, and fragile reconstruction for dense tables. It works best when your PDF is mostly prose with only modest table complexity. ## Demo Recording [Video: Unstructured demo recording](https://cdn.futuresmart.ai/public/aidemos/d8171ac86f1a46979a5091fb8aa8d429.mp4?v=1) *Video — Colab notebook recording of the partition_pdf workflow processing the benchmark PDFs and writing Markdown outputs.* ## Feature-by-Feature Breakdown ### PDF Text Extraction to Markdown **Verdict:** Mostly preserved, with punctuation and superscript fragility. Extracts prose from both native-text and scanned PDFs into markdown, including legal disclosures and checkbox-style lines. It handles ordinary body text well, though typographic punctuation and superscript markers may not be preserved exactly. **Input:** > **Image** **Output:** > **Image** **Input:** > **Image** **Output:** > **Image** **Input:** > **Image** **Output:** > **Image** **Bottom line:** Good at ordinary prose OCR, but exact-string workflows will trip over non-ASCII punctuation and superscripts. ### Table Reconstruction **Verdict:** Simple tables hold up; dense tables are brittle. Converts tables into markdown, with cleaner results on simple 2-3 column tables. Dense financial tables and uneven side-by-side layouts can lose columns, misalign cells, or spill values into nearby text. **Input:** > **Image** **Output:** > **Image** **Input:** > **Image** **Output:** > **Image** **Input:** > **Image** **Output:** > **Image** **Input:** > **Image** **Output:** > **Image** **Input:** > **Image** **Output:** > **Image** **Input:** > **Image** **Output:** > **Image** **Bottom line:** Simple 2-3 column tables can come through well, but denser or uneven structures can lose columns, rows, or cell-to-value alignment. ### Heading Detection **Verdict:** Headings are detected, but nesting is flattened. Recognizes section headings and places them in markdown. In the tested PDFs it can flatten multi-level structure to a single depth and sometimes elevate non-heading text into heading form. **Input:** > **Image** **Output:** > **Image** **Input:** > **Image** **Output:** > **Image** **Input:** > **Image** **Output:** > **Image** **Bottom line:** The tool finds headings, but the source's real nesting depth does not survive the conversion. ### Reading Order Preservation **Verdict:** Section flow and column order stay in sequence. Keeps content in the source's top-to-bottom reading order across pages, including back-page footer text. It also linearizes two-column scanned content left-to-right in reading sequence. **Input:** > **Image** **Output:** > **Image** **Input:** > **Image** **Output:** > **Image** **Input:** > **Image** **Output:** > **Image** **Bottom line:** Reading order is a clear strength, including column linearization and end-of-document footers. ### Chart Handling **Verdict:** Charts become unreadable noise instead of usable figures or data. Attempts to process chart regions from both native and scanned documents. In the tested outputs, charts were not reconstructed as structured data or clean placeholders, and instead became OCR noise or digit-soup in the markdown body. **Input:** > **Image** **Output:** > **Image** **Input:** > **Image** **Output:** > **Image** **Bottom line:** Charts are not preserved usefully: they are neither converted to data nor kept cleanly as visuals. ### Embedded Image and Logo Preservation **Verdict:** Embedded images are dropped entirely. Handles embedded images and logos during markdown export, but in the tested PDFs they were dropped with no image reference, placeholder, or comment marker. Repeated logos across pages were also removed. **Input:** > **Image** **Output:** > **Image** **Input:** > **Image** **Output:** > **Image** **Input:** > **Image** **Output:** > **Image** **Bottom line:** No embedded image or logo tested here survives the markdown export. ### Footnote and Caption Placement **Verdict:** Nearby footnotes and captions stay attached. Keeps footnotes directly beneath their source table and preserves figure captions in the correct relative position to the figure. This adjacency holds even when surrounding table or figure content is degraded. **Input:** > **Image** **Output:** > **Image** **Input:** > **Image** **Output:** > **Image** **Bottom line:** Adjacency is preserved for footnotes and captions, even when the underlying table or figure is damaged. ## Pricing | Plan | Price | Notes | | --- | --- | --- | | Open source ★ (tested) | $0 | Apache 2.0; self-hosted library. | *The report describes Unstructured as free and open source under Apache 2.0. The benchmark run was done in Google Colab on a T4 GPU, and processing time was not recorded.* ## Is It Right For You? **Use it if** - You want an open-source PDF-to-Markdown parser you can run locally or in your own infrastructure. - Your PDFs are mostly prose with scanned pages, and you care about preserving reading order. - You can tolerate flattened headings and missing images if the text extraction is strong. **Skip it if** - You need faithful chart preservation or chart-to-data extraction. - You need embedded images and logos retained in the markdown output. - Your workflow depends on complex tables, merged cells, or exact punctuation and superscript preservation. ## Classification - **Category:** developer-tools - **Subcategory:** pdf-tools - **Type:** text - **Built for:** Other ## Frequently Asked Questions **Q: Does Unstructured preserve scanned PDF text well?** Yes for ordinary prose. In the scanned research paper, full paragraphs were read accurately, but superscript ² markers and some footnote numerals were misread. **Q: What happens to charts in Unstructured's markdown output?** Charts were not reconstructed usefully. Native charts became interleaved digit-soup, and scanned chart regions became OCR noise with only fragments of labels surviving. **Q: Can Unstructured keep complex tables intact?** Not reliably. Simple tables were mostly fine, but dense tables could lose a column, garble cells, drop summary rows, or spill correct values into orphaned text after the table. **Q: Does Unstructured preserve heading hierarchy?** It detects headings, but the benchmark showed that multi-level structure collapses to one heading depth, and at least one byline was misclassified as a heading. **Q: Does Unstructured keep images or logos in the markdown?** No. Embedded images and logos were omitted entirely in all three inputs, with no placeholder, comment, or image reference left behind. **Q: Is Unstructured free to use?** Yes. The report describes it as open source under Apache 2.0, so there is no license fee; the benchmark itself was run in Google Colab on a T4 GPU. ## Similar Tools AI tools similar to Unstructured: - [Docling](https://aidemos.com/tools/docling) — Open-source PDF-to-markdown conversion that is strong on text, headings, and standard tables, but drops charts and other visual assets. - [PyMuPDF4LLM](https://aidemos.com/tools/pymupdf4llm) — Open-source PDF-to-markdown for clean native PDFs, but unreliable on scans, dense tables, and images. - [LiteParse](https://aidemos.com/tools/liteparse) — Open-source PDF-to-markdown parsing that works well on native-digital reports, but degrades on scans, tables, and charts. - [Doc2Mark](https://aidemos.com/tools/doc2mark) — Open-source PDF-to-markdown that preserves native text and headings, but still struggles with tables, charts, images, and scans. - [MarkItDown](https://aidemos.com/tools/markitdown) — Fast native-PDF text extraction for markdown, but structure, charts, images, and scans are unreliable. - [MinerU](https://aidemos.com/tools/mineru) — Open-source PDF-to-markdown that keeps figures and charts in place, but tables and punctuation can get messy on complex files. - [PaddleOCR](https://aidemos.com/tools/paddleocr) — Open-source PDF-to-markdown conversion that keeps images and tables in place, but still corrupts text and complex structure on harder documents. - [Dolphin](https://aidemos.com/tools/dolphin) — Self-hosted PDF-to-Markdown that preserves most text and tables, but drops charts and struggles with repeated images. ## Need a custom AI solution for this use case? If you are looking to build a custom PDF to Markdown, text extraction, or document parsing system for your business or internal workflow, email us at [contact@futuresmart.ai](mailto:contact@futuresmart.ai). ### Found something inaccurate or missing? We try to keep our AI research accurate and useful. If you found outdated information, an issue, or have a suggestion, email us at [collaborate@aidemos.com](mailto:collaborate@aidemos.com).