---
title: "Nutrient.io"
type: "AI Tool"
url: "https://aidemos.com/tools/nutrient-io"
description: "A developer-first PDF-to-markdown API that handles straightforward OCR and hierarchy well, but loses fidelity on complex tables, charts, and handwritten vi"
category: "text"
website: "http://nutrient.io?via=aidemos"
authors:
  - "Mahreen Fathima"
published: "2026-06-12T07:06:33.929Z"
updated: "2026-06-16T11:06:59.806Z"
---

# Nutrient.io

A developer-first PDF-to-markdown API that handles straightforward OCR and hierarchy well, but loses fidelity on complex tables, charts, and handwritten visual content.

`Tested on 3 PDF types` · `API workflow` · `Good on clean OCR + hierarchy` · `Complex tables and charts weak`

**Website:** [Visit Nutrient.io](http://nutrient.io?via=aidemos)

> **Good text extraction, weak document fidelity**
>
> Nutrient.io worked as a hosted API for turning mixed PDFs into markdown, and it did a respectable job preserving headings, section structure, and readable OCR on straightforward pages. But in this use case, the hard parts were exactly where it slipped: complex financial tables lost header relationships, charts were flattened into text or garbled OCR, handwritten signatures were omitted, and one scanned title page came back in the wrong reading order. It looks usable for developer workflows that mostly need text and basic structure, but not for high-trust markdown conversion of complex PDFs without cleanup.

## Demo Recording

[Video: Nutrient.io demo recording (download MP4)](https://d3epheqghktydj.cloudfront.net/Nutrient%20FinancialPDF%20Tool%20Demo.mp4)
[▶️ Watch (streaming)](https://stream.futuresmart.ai/embed/3a6beec3-1093-4b0c-ad2f-644245a7002a)
*Video — Walkthrough of PDF to Markdown workflow*

## Feature-by-Feature Breakdown

### Programmatic PDF-to-markdown extraction

**Verdict:** Works via API, but the tested workflow depended on code rather than the web UI.

Nutrient accepts multi-page PDFs and returns markdown output files programmatically. In testing, it processed an 84-page hybrid earnings report, an 18-page table-heavy financial report, and a scanned research paper. The researcher noted that the web UI timed out, so the successful path was the API-key workflow shown in Nutrient's documentation.

**Input:** PDF

[Pdf: PDF](https://d3epheqghktydj.cloudfront.net/llamaparse-hybrid-earnings-pdf-1.pdf)

**Output:** Markdown output

[Markdown: Markdown output](https://d3epheqghktydj.cloudfront.net/nutrient-io-nutrient-hybrid-earningspdf-output-2.md)

**Input:** PDF

[Pdf: PDF](https://d3epheqghktydj.cloudfront.net/llamaparse-sumitomo-financial-pdf-1.pdf)

**Output:** Markdown output

[Markdown: Markdown output](https://d3epheqghktydj.cloudfront.net/nutrient-io-nutrient-financialpdf-output-1.md)

**Input:** PDF

[Pdf: PDF](https://d3epheqghktydj.cloudfront.net/llamaparse-scanned-research-pdf-1.pdf)

**Output:** Markdown output

[Markdown: Markdown output](https://d3epheqghktydj.cloudfront.net/nutrient-io-nutrient-scannedpdf-output-1.md)

**Bottom line:** If you are comfortable calling an API, Nutrient can return markdown for mixed PDFs. If you need a dependable browser flow, this research did not show one: the UI timed out and the tested path was code-first.

### Reading order, hierarchy, and OCR text recovery

**Verdict:** Good on straightforward pages, but not fully reliable on complex scanned layouts.

Nutrient was strongest when the task was recovering readable text with section structure intact. It preserved heading-to-body relationships on a native-digital annual-report page, recovered dense prose and numeric details from a financial-report page, and handled a scanned two-column research section cleanly. The main weakness was page-level ordering on a more complex scanned first page, where abstract material appeared before the title block.

**Input:** Source page

![Source page](https://d3epheqghktydj.cloudfront.net/landing-ai-target-annual-report-growth-story-page.png)
*Image: Source page*

**Output:** Parsed output screenshot

![Parsed output screenshot](https://d3epheqghktydj.cloudfront.net/nutrient-io-target-annual-report-parsed-document-hierarchy.png)
*Image: Parsed output screenshot*

**Input:** Source page

![Source page](https://d3epheqghktydj.cloudfront.net/nutrient-io-financial-summary-condition-page-9.png)
*Image: Source page*

**Output:** Parsed output screenshot

![Parsed output screenshot](https://d3epheqghktydj.cloudfront.net/nutrient-io-financial-summary-ocr-hierarchy-page-8.png)
*Image: Parsed output screenshot*

**Input:** Scanned source page

![Scanned source page](https://d3epheqghktydj.cloudfront.net/landing-ai-scanned-two-column-text-study-area.png)
*Image: Scanned source page*

**Output:** Parsed output screenshot

![Parsed output screenshot](https://d3epheqghktydj.cloudfront.net/nutrient-io-study-area-parsed-section-hierarchy.png)
*Image: Parsed output screenshot*

**Input:** Scanned source page

![Scanned source page](https://d3epheqghktydj.cloudfront.net/nutrient-io-usda-research-note-title-page.png)
*Image: Scanned source page*

**Output:** Parsed output screenshot

![Parsed output screenshot](https://d3epheqghktydj.cloudfront.net/nutrient-io-ocr-first-page-abstract-text.png)
*Image: Parsed output screenshot*

**Bottom line:** Nutrient can produce clean, usable text from both digital and scanned pages when the layout is straightforward. But the title-page ordering miss means you should still spot-check complex scanned layouts before trusting downstream ingestion.

### Table extraction

**Verdict:** Mixed to weak: simpler tables survive, but complex financial and scanned tables lose important structure.

Nutrient can preserve the rough shape of simpler tables, including one scanned table with grouped columns, but it struggled as complexity increased. Across the hybrid earnings report, the table-heavy financial report, and the scanned research paper, the recurring failure mode was loss of row/column alignment and multi-level header relationships. The result was markdown that still contained many values, but often not in a form a human or pipeline could trust without cleanup.

**Input:** Scanned source table

![Scanned source table](https://d3epheqghktydj.cloudfront.net/mistral-ai-scanned-treatment-diameter-table.png)
*Image: Scanned source table*

**Output:** Parsed output screenshot

![Parsed output screenshot](https://d3epheqghktydj.cloudfront.net/nutrient-io-parsed-table-stand-structure-before-after-cutting.png)
*Image: Parsed output screenshot*

**Input:** Source table

![Source table](https://d3epheqghktydj.cloudfront.net/landing-ai-target-annual-report-financial-summary-table-2.png)
*Image: Source table*

**Output:** Parsed output screenshot

![Parsed output screenshot](https://d3epheqghktydj.cloudfront.net/nutrient-io-target-annual-report-parsed-complex-table.png)
*Image: Parsed output screenshot*

**Input:** Source table

![Source table](https://d3epheqghktydj.cloudfront.net/nutrient-io-financial-segment-table-cropped.png)
*Image: Source table*

**Output:** Parsed output screenshot

![Parsed output screenshot](https://d3epheqghktydj.cloudfront.net/nutrient-io-segment-financial-table-by-business-unit.png)
*Image: Parsed output screenshot*

**Input:** Source table

![Source table](https://d3epheqghktydj.cloudfront.net/nutrient-io-quarterly-consolidated-income-statement-table.png)
*Image: Source table*

**Output:** Parsed output screenshot

![Parsed output screenshot](https://d3epheqghktydj.cloudfront.net/nutrient-io-parsed-quarterly-income-statement-text.png)
*Image: Parsed output screenshot*

**Input:** Scanned source table

![Scanned source table](https://d3epheqghktydj.cloudfront.net/nutrient-io-table-trees-killed-per-acre.png)
*Image: Scanned source table*

**Output:** Parsed output screenshot

![Parsed output screenshot](https://d3epheqghktydj.cloudfront.net/nutrient-io-parsed-table-trees-killed-per-acre-1.png)
*Image: Parsed output screenshot*

**Bottom line:** Nutrient is acceptable for simpler tables, but it was not dependable on the exact table-heavy cases this use case cares about most: financial summaries, multi-level headers, and dense scanned matrices.

### Chart and visual-content handling

**Verdict:** Weak: charts lose their semantics, and handwritten visual content is not retained.

Nutrient did not meaningfully preserve non-text visuals in this research. For charts, it sometimes recovered some labels or values, but not the axes, series relationships, or chart structure that make the figure interpretable. For a scanned signatures page, it extracted surrounding text and signer details but did not capture the handwritten signature marks themselves.

**Input:** Source chart

![Source chart](https://d3epheqghktydj.cloudfront.net/llamaparse-sga-rate-waterfall-chart-1.png)
*Image: Source chart*

**Output:** Observed output

![Observed output](https://d3epheqghktydj.cloudfront.net/nutirent_hybrid_earningspdf_parsed_waterfall_chart.png)
*Image: Observed output*

**Input:** Scanned source chart

![Scanned source chart](https://d3epheqghktydj.cloudfront.net/nutrient-io-figure-3-average-radial-growth-by-treatment.png)
*Image: Scanned source chart*

**Output:** Parsed output screenshot

![Parsed output screenshot](https://d3epheqghktydj.cloudfront.net/nutrient-io-parsed-chart-forest-growth-cutting-blocks.png)
*Image: Parsed output screenshot*

**Input:** Scanned source page

![Scanned source page](https://d3epheqghktydj.cloudfront.net/landing-ai-target-annual-report-signatures-page-2.png)
*Image: Scanned source page*

**Output:** Parsed output screenshot

![Parsed output screenshot](https://d3epheqghktydj.cloudfront.net/nutrient-io-target-signatures-ocr-extraction.png)
*Image: Parsed output screenshot*

**Bottom line:** If charts, figures, or handwritten marks matter to the fidelity of your markdown, Nutrient did not preserve them well enough in this test set.

## Pricing & Access

| Plan | Price | Notes |
| --- | --- | --- |
| Free (tested) | $0 | 5,000 credits/month |
| Starter | $59/month | 25,000 credits/month |
| Pro | $500 | 500,000 credits/month |
| Custom | Custom | Custom credit volume Volume discounts Dedicated support |

## Is This Right For You?

A side-by-side guide based on our hands-on testing.

**✓ Use This If**
- You need a hosted API that returns markdown files for mixed PDFs and you are comfortable working from an API key and code instead of relying on the web UI.
- Your documents are mostly straightforward report pages where readable OCR text and basic heading hierarchy matter more than perfect reconstruction of tables or charts.
- You can tolerate manual review of scanned title pages and visually complex sections before sending the markdown downstream.

**✕ Skip This If**
- You need complex financial tables preserved with reliable multi-level headers and row-to-value alignment.
- You need charts retained as meaningful visual elements instead of flattened labels or garbled OCR text.
- You need handwritten signatures or other non-text visuals preserved as part of the extracted document.
- You need flawless reading order on complex scanned layouts without spot-checking.

## Use Case Track

Usecases

| Rank | Use Case | Notes |
| --- | --- | --- |
| #8 | Convert a Complex PDF to Clean Markdown with API | A developer-first PDF-to-markdown API that handles straightforward OCR and hierarchy well, but loses fidelity on complex tables, charts, and handwritten visual content. |

## Related Pages

- [Best AI APIs to Convert Complex PDFs into Clean Markdown](https://aidemos.com/best/pdf-to-markdown-apis) — Ranking

## Related Reads

- **Best AI Tools to Convert Complex PDFs into Clean Markdown with an API** — RANKING

## Classification

- **Type:** text
- **Built for:** Founders

## Frequently Asked Questions

**Q: Does Nutrient.io convert scanned PDFs to markdown?**

Yes. In this research, Nutrient accepted a scanned research paper and returned markdown output. It also OCR'd scanned pages inside a hybrid earnings report. The quality was mixed: straightforward scanned text came through reasonably well, but page-order mistakes, chart failures, and complex-table errors remained.

**Q: How well does Nutrient preserve headings and reading order?**

It did well on several straightforward pages. The annual-report page titled 'A Growth Story Again' kept its heading, paragraph, and bullets in order, and a scanned two-column 'STUDY AREA' page was turned into coherent paragraphs with the heading preserved. But on a scanned research-note first page, Nutrient placed the abstract before the title and authors, so reading order is not fully reliable on complex layouts.

**Q: Can Nutrient extract complex financial tables accurately?**

Only inconsistently. A simpler scanned treatment table remained mostly readable, though OCR changed values like 7.8 to 78. But harder tables were weaker: the hybrid earnings-report financial summary lost alignment, the segment table lost multi-level header relationships, the quarterly income statement came back partially truncated, and a dense scanned mortality table broke down badly.

**Q: Does Nutrient preserve charts and figures in markdown?**

Not well in this test. The hybrid waterfall chart reportedly came back as flattened text without chart semantics, and the scanned line graph produced mostly garbled OCR text. In both cases, labels or values may survive, but the visual structure does not.

**Q: Does Nutrient capture signatures from scanned pages?**

Only the surrounding text. On the scanned signatures page, Nutrient extracted the section heading, signer names, titles, and dates, but it did not extract the handwritten signature marks themselves.

**Q: Can you use Nutrient through the web UI, or do you need the API?**

The researcher's tested path was the API. The report says the UI hit a timeout, so the markdown output was produced through an API key and code snippet from Nutrient's documentation.

**Q: Was Nutrient tested on multilingual or degraded-scan PDFs here?**

No. This Nutrient section includes a hybrid earnings report, a table-heavy financial report, and a scanned research paper, but it does not include a multilingual input or a degraded-scan stress test.

## Similar Tools

AI tools similar to Nutrient.io:

- [LlamaParse](https://aidemos.com/tools/llamaparse) — LlamaParse Review: AI Resume Parser & Schema Extraction Tested (2026)
- [Landing AI](https://aidemos.com/tools/landing-ai) — A capable PDF-to-markdown API for complex financial and scanned PDFs, with strong table and chart extraction but inconsistent heading semantics.
- [Extend AI](https://aidemos.com/tools/extend-ai) — A capable PDF-to-markdown API for mixed and scanned documents that keeps structure and most visuals, but stumbles on the hardest table headers.
- [Mistral AI](https://aidemos.com/tools/mistral-ai) — A strong hosted PDF-to-markdown API for mixed and scanned documents, with solid OCR, table recovery, and asset export but uneven structural fidelity.
- [Upstage AI](https://aidemos.com/tools/upstage-ai) — Solid on native financial tables, but unreliable for multi-column and scanned-document structure in markdown conversion.