Every converter website says its output is clean. This page shows you ours instead. Below are eleven Parsyra conversion examples produced by the exact code that runs when you drop a file on the homepage: plain and financial PDFs, a scanned delivery note, a maths handout, a webpage, a note full of LaTeX, an engineering note full of Mermaid diagrams, a PPTX deck and an Excel workbook — with the report and the handout each compared twice, once through standard Parsyra conversion and once through High-accuracy OCR. Nothing was retouched. Where the result is strong we say so, and where it falls apart — PDF tables, equations, flattened slide tables — we show the failure and explain it.
All input files were authored by us for this page, so you can compare them freely. Every output below is the verbatim result of a single conversion run, with nothing corrected.
Pick a document type. The left panel is the input we fed in; the right panel is the Markdown that came out, byte for byte. Green notes are what held up, amber notes are what to check before you ship the result. Between them these Parsyra conversion examples cover the formats people actually bring us.
A two-page release memo exported straight from an editor: title, subtitle, four sections, two bullet lists. The friendliest kind of PDF — born digital, single column, real text layer.

# Fieldnote 2.4 Release Overview Product update memo — internal draft, April 2026 ## Summary Fieldnote 2.4 focuses on offline reliability. Sync conflicts dropped by roughly two thirds in the beta cohort after we replaced last-write-wins with a field-level merge. This memo covers what shipped, what we deferred, and the open questions for the 2.5 planning cycle. ## What Shipped Field-level merge for notes edited on two devices while offline. Background sync now retries with exponential backoff instead of a fixed 30-second timer. Attachment uploads resume after a dropped connection rather than restarting. A visible sync-state indicator in the note header, replacing the ambiguous spinner. ## Deferred to 2.5 Shared-notebook merge remains unsolved. When two collaborators restructure the same outline offline, the merge produces a valid but surprising order. We deferred this rather than ship a confusing resolution dialog. Outline-aware merge for shared notebooks. Selective sync for attachments over 50 MB. ## Open Questions The beta cohort skews toward single-device users, so the conflict numbers above may understate multi-device behavior. We plan to re-run the analysis once the 2.4 rollout reaches half of the multi-device population.
Ready to paste into a wiki or prompt after a ten-second skim; re-add list dashes if you need them.
recommended setup › Standard Parsyra run — no extra options needed; the source is processed temporarily and deleted afterward.
A results summary with two ruled tables — revenue by segment and operating costs. This is the case the honest answer matters most for: PDF stores a table as positioned glyphs and ruled lines, with nothing marking where a cell begins.

# Northwind Tooling Co. — Q3 2026 Results Unaudited condensed summary, prepared for the quarterly review ## Revenue by Segment Segment Q3 2026 Q2 2026 QoQ Hand tools $4,210k $3,955k +6.4% Power tools $2,875k $3,010k -4.5% Accessories $1,340k $1,180k +13.6% Service & parts $960k $915k +4.9% Total $9,385k $9,060k +3.6% ## Operating Costs Line Q3 2026 Share of revenue Cost of goods sold $5,210k ## 55.5% Sales & marketing $1,120k ## 11.9% R&D $860k ## 9.2% General & administrative $705k ## 7.5% ## Commentary Accessories growth reflects the June launch of the modular case line. Power tools declined on channel inventory drawdown; sell-through remained flat. Gross margin held at 44.5% despite steel cost inflation, helped by the supplier consolidation completed in Q1. Cash at quarter end was $6.2M with no drawn credit. The board approved a $1.5M capacity investment for the Tacoma line, expected online in Q2 2027.
Trust the prose, rebuild the tables — from the XLSX if you have it, or compare the next tab if your reports arrive as scans.
recommended setup › Standard Parsyra run for the prose; switch to the Excel converter or High-accuracy OCR when the tables matter.
The identical report from the previous tab, flattened to an image so it carries no text layer. That is what puts it on the AI recognition path, and it answers the question the previous tab raises: what happens to these tables when the page is read visually instead of by coordinates.

# Northwind Tooling Co. — Q3 2026 Results Unaudited condensed summary, prepared for the quarterly review ## Revenue by Segment | Segment | Q3 2026 | Q2 2026 | QoQ | | --- | --- | --- | --- | | Hand tools | $4,210k | $3,955k | +6.4% | | Power tools | $2,875k | $3,010k | -4.5% | | Accessories | $1,340k | $1,180k | +13.6% | | Service & parts | $960k | $915k | +4.9% | | **Total** | **$9,385k** | **$9,060k** | **+3.6%** | ## Operating Costs | Line | Q3 2026 | Share of revenue | | --- | --- | --- | | Cost of goods sold | $5,210k | 55.5% | | Sales & marketing | $1,120k | 11.9% | | R&D | $860k | 9.2% | | General & administrative | $705k | 7.5% | ## Commentary Accessories growth reflects the June launch of the modular case line. Power tools declined on channel inventory drawdown; sell-through remained flat. Gross margin held at 44.5% despite steel cost inflation, helped by the supplier consolidation completed in Q1. Cash at quarter end was $6.2M with no drawn credit. The board approved a $1.5M capacity investment for the Tacoma line, expected online in Q2 2027.
If your financial reports arrive as scans, this is the tab that matters: unusable text lines become a table you can paste straight into a spreadsheet or a prompt.
recommended setup › Turn on "Automatic OCR for scanned PDFs" — sign-in required; 10 pages/month free, 500 on Pro.
A photographed-style delivery note: the PDF holds one image per page and no text layer at all, so standard Parsyra extraction finds zero characters. The widget flags it as a likely scan and offers High-accuracy OCR, which sends page images for visual recognition after you choose it.

# GREENFIELD NURSERY — DELIVERY NOTE Date: 14 March 2026 Order no. 2026-0312 Deliver to: Harbor Community Garden, Pier Road allotments | Item | Qty | Unit | Total | | --- | --- | --- | --- | | Apple sapling (Discovery) | 6 | $18.50 | $111.00 | | Compost, 40 L bag | 10 | $7.25 | $72.50 | | Willow stakes, bundle | 4 | $9.00 | $36.00 | | Total due | | | $219.50 | Payment terms: 30 days net. The variance of the germination estimate follows σ²/n as discussed with your volunteer coordinator. Received in good condition — M. Aldous
The strongest argument for OCR: an unreadable scan becomes a clean, structured table in one pass.
recommended setup › Turn on "Automatic OCR for scanned PDFs" — sign-in required; 1 page of quota per page converted.
A seminar handout with display equations — subscripts, superscripts, summation signs. Equations in a text-layer PDF are stored as scattered positioned glyphs, and this example shows exactly what that means for the output.

# A Note on Weighted Moving Averages Course handout — numerical methods seminar ## 1. Definition Given a series x , …, x and weights w , the weighted moving average over a window of size k is 1 n i k−1 k−1 m = ( ∑ w x ) / ( ∑ w ) t i=0 i t−i i=0 i i with the convention that the window is truncated at the start of the series. When w = λ for some 0 < λ < i 1, the average discounts older observations geometrically. ## 2. Variance Under Independence 2 If the x are independent with common variance σ , the variance of the estimator is i 2 2 2 Var(m ) = σ · ( ∑ w ) / ( ∑ w ) t i i 2 which is minimized by equal weights, giving the familiar σ /k. Geometric weights trade this efficiency for responsiveness: the effective sample size becomes (1+λ)/(1−λ) as k grows. ## 3. Practical Note For λ = 0.9 the effective sample size is 19, so a practitioner who wants the smoothing of a 19-point simple average with faster reaction to level shifts can use the geometric scheme without retuning the window length.
Fine for the prose around the maths; for the equations themselves, see the next tab.
recommended setup › Standard Parsyra run for text; High-accuracy OCR when you need the equations as LaTeX.
Identical page to the previous tab, but flattened to an image so it has no text layer — which is what puts it on the AI recognition path. This High-accuracy OCR route is designed for cases where equations need to come back as LaTeX rather than scattered glyphs.

# A Note on Weighted Moving Averages
Course handout — numerical methods seminar
## 1. Definition
Given a series $x_1, \dots, x_n$ and weights $w_i$, the weighted moving average over a window of size $k$ is
$$m_t = (\sum_{i=0}^{k-1} w_i x_{t-i}) / (\sum_{i=0}^{k-1} w_i)$$
with the convention that the window is truncated at the start of the series. When $w_i = \lambda^i$ for some $0 < \lambda < 1$, the average discounts older observations geometrically.
## 2. Variance Under Independence
If the $x_i$ are independent with common variance $\sigma^2$, the variance of the estimator is
$$Var(m_t) = \sigma^2 \cdot (\sum w_i^2) / (\sum w_i)^2$$
which is minimized by equal weights, giving the familiar $\sigma^2/k$. Geometric weights trade this efficiency for responsiveness: the effective sample size becomes $(1+\lambda)/(1-\lambda)$ as $k$ grows.
## 3. Practical Note
For $\lambda = 0.9$ the effective sample size is 19, so a practitioner who wants the smoothing of a 19-point simple average with faster reaction to level shifts can use the geometric scheme without retuning the window length.Side by side with the previous tab, this is the clearest measure of what the paid recognition path buys you: unusable glyph soup becomes publishable LaTeX.
recommended setup › Turn on "Automatic OCR for scanned PDFs" — sign-in required; 10 pages/month free, 500 on Pro.
A saved blog post with an ordered list, a table, a blockquote, a code block and links. HTML is the best-case input: unlike PDF, the structure is written into the file, so the converter translates markup instead of guessing from geometry.
<article>
<h1>How We Version Our Field Guides</h1>
<p><em>Posted to the Fieldnote engineering blog, March 2026.</em></p>
<p>Every field guide we publish is a set of Markdown files in a Git
repository. Print editions are tagged releases. This post explains the
branching model and the two rules that keep 40 contributors from
stepping on each other.</p>
<h2>The two rules</h2>
<ol>
<li>A chapter owner merges their own chapter. Nobody else does.</li>
<li>Cross-chapter renames land in a dedicated <code>restructure/*</code>
branch, never in a chapter branch.</li>
</ol>
<h2>Release cadence</h2>
<table>
<tr><th>Edition</th><th>Branch</th><th>Cadence</th></tr>
<tr><td>Web</td><td><code>main</code></td><td>continuous</td></tr>
<tr><td>Print</td><td><code>release/YYYY</code></td><td>yearly</td></tr>
<tr><td>Translations</td><td><code>l10n/*</code></td><td>after print freeze</td></tr>
</table>
<blockquote>Versioning prose like code only works if the prose is
actually plain text. That is the whole trick.</blockquote>
... How We Version Our Field Guides
# How We Version Our Field Guides
_Posted to the Fieldnote engineering blog, March 2026._
Every field guide we publish is a set of Markdown files in a Git repository. Print editions are tagged releases. This post explains the branching model and the two rules that keep 40 contributors from stepping on each other.
## The two rules
1. A chapter owner merges their own chapter. Nobody else does.
2. Cross-chapter renames land in a dedicated `restructure/*` branch, never in a chapter branch.
## Release cadence
| Edition | Branch | Cadence |
| --- | --- | --- |
| Web | `main` | continuous |
| Print | `release/YYYY` | yearly |
| Translations | `l10n/*` | after print freeze |
The print freeze is the only synchronization point. Everything else flows continuously, and the [style guide](https://example.com/fieldnote-style-guide) resolves formatting arguments before they reach review.
> Versioning prose like code only works if the prose is actually plain text. That is the whole trick.
## What broke
Image-heavy chapters caused merge pain until we moved figures to per-chapter directories with numeric prefixes:
```
guides/
coastal-birds/
ch03-waders/
fig-01-sandpiper.jpg
text.md
```
Since that change, no figure conflict has required manual resolution.Ship-ready minus one stray line. For content that exists as a webpage, convert the page, not a PDF print of it.
recommended setup › Default run — or use the From URL tab and let the site fetch the page for you.
A small funding-pitch deck: title slide, bullet slides, one table slide, and speaker notes on two slides. The converter reads the text runs out of each slide's XML and writes them under per-slide headings.

## Slide 1 Community Workshop Program Funding pitch — spring 2026 ## Slide 2 Why now Tool library membership doubled in 18 months Waitlists on every repair workshop since October Two volunteer instructors ready to lead new sessions ## Slide 3 Program economics Line Monthly Covered by Venue hire $420 Council grant Materials $300 avg Ticket sales Instructor fees $650 avg This proposal ## Slide 4 What we are asking for $7,800 to underwrite instructor fees for one year Access to the annex room on weekday evenings A decision before the summer schedule is printed ## Slide 5 Thank you Questions — [email protected]
Good enough to get a deck's words into a prompt or a doc; not a faithful reconstruction of the slides.
recommended setup › Default run. If a table slide matters, keep the numbers in a spreadsheet and convert that.
A two-sheet workbook: a budget sheet with a merged title cell and SUM formulas, and an attendance sheet. Spreadsheets carry explicit cell structure, which makes this the strongest input format on the site.

## Budget | Q3 2026 Budget — Community Workshop | | | | | --- | --- | --- | --- | | Category | Jul | Aug | Sep | | Venue hire | 420 | 420 | 420 | | Materials | 310 | 265 | 340 | | Instructor fees | 600 | 600 | 750 | | Insurance | 85 | 85 | 85 | | Outreach & printing | 120 | 90 | 60 | | Total | 1535 | 1460 | 1655 | ## Attendance | Workshop | Seats | Attended | Waitlist | | --- | --- | --- | --- | | Intro woodworking | 12 | 12 | 5 | | Bike repair basics | 10 | 8 | 0 | | Sewing machine 101 | 12 | 11 | 3 | | Home electrics safety | 16 | 14 | 2 |
The showcase case: if your data lives in a spreadsheet, this is the conversion to lean on.
recommended setup › Standard Parsyra run — tables come out as tables, with no extra options needed.
A growth-review note whose formulas are written as TeX so they stay reviewable in version control. Markdown in, Markdown out — the interesting part is what the math survives as, and what our editor can then do with it.
# Sizing an A/B Test
Notes for the growth review. The formulas are written as TeX so they stay reviewable in version control.
## Confidence interval for a conversion rate
With $n$ visitors and $k$ conversions the point estimate is $\hat{p} = k/n$, and the normal-approximation interval at level $1-\alpha$ is
$$\hat{p} \pm z_{1-\alpha/2} \sqrt{\frac{\hat{p}(1-\hat{p})}{n}}$$
The approximation is reasonable once $n\hat{p} \geq 10$ and $n(1-\hat{p}) \geq 10$; below that use the Wilson interval instead.
## Required sample size
To detect an absolute lift of $\delta$ with power $1-\beta$, each arm needs roughly
$$n \approx \frac{2\bar{p}(1-\bar{p})\left(z_{1-\alpha/2} + z_{1-\beta}\right)^2}{\delta^2}$$
where $\bar{p}$ is the pooled rate. For $\bar{p} = 0.12$, $\delta = 0.02$, $\alpha = 0.05$ and $\beta = 0.2$ this gives about 4,150 visitors per arm.
## Why the test ran long
Traffic split unevenly for the first four days, so the effective $n$ was closer to the smaller arm than to the total. The variance term $\sqrt{\hat{p}(1-\hat{p})/n}$ shrinks with $\sqrt{n}$, so halving usable traffic costs roughly $\sqrt{2}$ in interval width.# Sizing an A/B Test
Notes for the growth review. The formulas are written as TeX so they stay reviewable in version control.
## Confidence interval for a conversion rate
With $n$ visitors and $k$ conversions the point estimate is $\hat{p} = k/n$, and the normal-approximation interval at level $1-\alpha$ is
$$\hat{p} \pm z_{1-\alpha/2} \sqrt{\frac{\hat{p}(1-\hat{p})}{n}}$$
The approximation is reasonable once $n\hat{p} \geq 10$ and $n(1-\hat{p}) \geq 10$; below that use the Wilson interval instead.
## Required sample size
To detect an absolute lift of $\delta$ with power $1-\beta$, each arm needs roughly
$$n \approx \frac{2\bar{p}(1-\bar{p})\left(z_{1-\alpha/2} + z_{1-\beta}\right)^2}{\delta^2}$$
where $\bar{p}$ is the pooled rate. For $\bar{p} = 0.12$, $\delta = 0.02$, $\alpha = 0.05$ and $\beta = 0.2$ this gives about 4,150 visitors per arm.
## Why the test ran long
Traffic split unevenly for the first four days, so the effective $n$ was closer to the smaller arm than to the total. The variance term $\sqrt{\hat{p}(1-\hat{p})/n}$ shrinks with $\sqrt{n}$, so halving usable traffic costs roughly $\sqrt{2}$ in interval width.Markdown in, Markdown out, with the maths intact — the cleanest path for anything equation-heavy.
recommended setup › Standard Parsyra run to convert. Typesetting the result, as shown above, is a Pro feature of the Markdown editor.
A design note that keeps its diagrams two ways: two Mermaid definitions written as code, and the same flowchart exported as a PNG. Diagram-as-code and diagram-as-picture behave very differently in conversion, and this sample shows both in one file.
<article>
<h1>Sync Architecture Note</h1>
<p>How a note travels from an offline edit to a merged document. The
diagram below is kept in the repository as Mermaid source so it can be
reviewed in a pull request like any other code.</p>
<h2>Merge flow</h2>
<pre><code class="language-mermaid">flowchart TD
A[Offline edit] --> B{Has remote changed?}
B -->|No| C[Fast-forward]
B -->|Yes| D[Field-level merge]
D --> E{Conflict?}
E -->|No| F[Write merged note]
E -->|Yes| G[Queue for review]
C --> F</code></pre>
<h2>Retry timing</h2>
<pre><code class="language-mermaid">sequenceDiagram
participant App
participant Queue
participant Server
App->>Queue: enqueue(change)
...</code></pre>
<h2>The same flow as a picture</h2>
<figure>
<img src="diagram.png" alt="Rendered flowchart of the merge path">
<figcaption>Figure 1 — the merge path, exported as PNG.</figcaption>
</figure>
... Sync Architecture Note
# Sync Architecture Note
How a note travels from an offline edit to a merged document. The diagram below is kept in the repository as Mermaid source so it can be reviewed in a pull request like any other code.
## Merge flow
```mermaid
flowchart TD
A[Offline edit] --> B{Has remote changed?}
B -->|No| C[Fast-forward]
B -->|Yes| D[Field-level merge]
D --> E{Conflict?}
E -->|No| F[Write merged note]
E -->|Yes| G[Queue for review]
C --> F
```
## Retry timing
```mermaid
sequenceDiagram
participant App
participant Queue
participant Server
App->>Queue: enqueue(change)
Queue->>Server: POST /sync
Server-->>Queue: 503
Queue->>Queue: backoff x2
Queue->>Server: POST /sync
Server-->>App: 200 merged
```
## The same flow as a picture

Figure 1 — the merge path, exported as PNG for the slide deck.
## Notes
* Mermaid source lives beside the prose, so diagram changes show up in review diffs.
* The exported PNG is generated from the same source and is never edited by hand.

If your diagrams live as Mermaid source, they convert perfectly and stay drawable — the strongest argument for keeping diagrams as code rather than as exported images.
recommended setup › Standard Parsyra run to convert. Rendering the diagrams, as shown above, is a Pro feature of the Markdown editor; the fenced source itself is free and renders anywhere that supports Mermaid.
The converter deliberately has few knobs. These are the setups behind the Parsyra conversion examples above, and when to reach for each one.
What every example on this page used unless noted: drop the file, read the result. The current converter sends supported files to the self-hosted Parsyra service for temporary processing. Best for DOCX, XLSX, CSV, HTML and digital-born single-column PDFs.
The high-accuracy path for scanned PDFs. When a PDF has no usable text layer the widget flags it and offers OCR; it rebuilds tables that ordinary text extraction flattens and returns equations as LaTeX — compare the two maths tabs in the gallery to see the difference. Requires sign-in: 10 pages a month free, 500 on Pro.
The financial-report example shows why: PDF tables arrive as text lines, spreadsheet tables arrive as pipe tables. If the numbers exist in XLSX or CSV anywhere upstream, convert that file and skip the PDF entirely. Paste-a-table mode does the same for data on your clipboard.
The Markdown body is standard GFM, so it drops into a vault untouched. The Export to Obsidian button additionally writes source, date and tag front-matter and a vault-safe filename. Tables from Excel and webpages render in Obsidian exactly as shown above.
Output is GitHub-Flavored Markdown already — pipe tables, fenced code blocks and blockquotes in the examples above render on GitHub without changes. Copy the result straight into a README or an issue; there is no separate mode to configure.
A quality page is only useful if you can trust its samples. Here is how these Parsyra conversion examples were produced — dull on purpose, so you could repeat it yourself and get the same bytes. Samples produced 30 July 2026.
Every input file was written for this page — a memo, a results summary, a delivery note, a maths handout, a blog post, an architecture note, a deck and a workbook — so there are no copyright questions and nothing was cherry-picked from files we knew would convert well. The generator scripts live in the site's repository.
Each file went through the public widget exactly once — the same code path you get, not a lab build. The three scanned samples used High-accuracy OCR; every other file used the default server run with no extra options.
What you see in each output panel is the copied result of that run. We fixed nothing: the flattened financial tables, the exploded equations and the collapsed PPTX table are all shown as they came out, because that is the information you actually need before trusting a converter.
The strengths and limitations under each example are our reading of the output, written after the fact. Where a weakness has a workaround — spreadsheet sources for tables, OCR for scans and columns — the annotation says so instead of hiding the weakness.
What these samples do and don't prove, and how to reproduce them.
Yes. Each output panel is the verbatim clipboard result of one conversion run — including the failures. The financial tables arrive as loose lines rather than a grid, the equations in the maths handout fall apart into scattered glyphs, and the slide table collapses to one value per line, all on public display. The only editorial act anywhere on the page is annotation around the output, never changes inside it.
Because you'll find out anyway, five minutes after you rely on it. Showing the flattened PDF tables here costs us a little polish and saves you a surprise. It also makes the good cases believable: when the Excel example says every value lands in the right cell, you know that claim survived the same no-retouching rule as the failures did.
Yes, and we'd encourage it. The sample files and the scripts that generate them are committed to the site's repository, and the converter on the homepage is the same code that produced these outputs. Author a similar file, run it through, and compare — same input, same bytes out.
A PDF stores a table as ruled lines plus positioned glyphs; nothing in the format marks where a cell begins or ends. Tools that promise perfect grids from that are guessing from pixel coordinates, and the guess eventually shifts a column silently. We'd rather hand you correct text than a confident wrong table — and point you at the spreadsheet source or AI OCR when the grid itself matters.
Through High-accuracy OCR, yes, and the two maths tabs in the gallery show both sides of it. The standard Parsyra PDF path reads a text layer where an equation is stored as scattered positioned glyphs, so subscripts and summation bounds break onto their own lines — no tool reading that layer can reassemble them reliably. Reading the rendered page visually instead returns proper LaTeX in dollar delimiters. Because that route is offered only for PDFs with no text layer, a born-digital paper has to be flattened to an image first.
Two of the Parsyra conversion examples in the gallery use the high-accuracy OCR path, and each answers a different doubt. The scanned delivery note rebuilds a table that ordinary text extraction flattens into text lines; the maths handout appears twice, converted normally and then with visual OCR, where the equations return as real LaTeX. Reading the rendered page rather than a text layer is what makes both possible. The path is metered at 10 pages a month free and 500 on Pro.
Most examples on this page use the standard Parsyra conversion path. The scanned tabs use High-accuracy OCR, which is metered at 10 pages a month on the Free tier and 500 on Pro.
Most likely your input carries less structure than the sample did. The examples show the pattern: HTML and XLSX convert almost perfectly because structure is in the file; PDFs degrade as layout complexity rises; scans may yield little or no text until you turn on High-accuracy OCR. Check whether your PDF has a selectable text layer, whether it's multi-column, and whether the data exists in a structured format upstream — that diagnosis covers nearly every disappointing result.
Dig deeper into a specific format: PDF, Excel, PowerPoint, Word, web pages, or scanned files via image to Markdown.
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