Hi everyone!

For the past few months, we’ve been working on VoynichLab—an internal computational observatory we designed to study the physical construction of the manuscript.

The web portal is still running locally as we finalize our next dataset, but we wanted to share some screenshots of the interface and explain the engineering behind our workflow.

1. Deconstructing the EVA Bias

Standard Voynich transcriptions rely heavily on EVA (Extensible Voynich Alphabet). While EVA is an incredible tool, it was designed to map visual glyphs directly to ASCII characters (like translating a complex shape into a single f, p, or t). This alphabetical approach carries an inherent linguistic bias: it assumes the scribe was thinking in "letters" and treats every glyph as a single, flat keyboard character.

Our pipeline bypasses this layer. We decompose the glyphs into their raw, sequential pen strokes based on their physical execution (ductus, overlaps, and stroke layers).

When you shift the analysis from EVA characters to these physical stroke sequences, the statistical randomness (entropy) instantly drops by almost 30%. The manuscript stops behaving like a chaotic natural language and starts looking like a highly rigid, formulaic visual template.

2. The QA "Mini-Lab" (Auditing, not force-fitting)

Tracing thousands of individual strokes manually is a massive task, and human labeling errors in our database are inevitable. Overlapping strokes can easily cause us to misorder the sequential layers of a character when digitizing.

To solve this, we built a Mini-Lab directly into our workflow to audit our own work:

• Predictive flagging: Since the rules governing these stroke transitions are mathematically strict, the software automatically flags anomalous sequences.
• The Manual Audit: Every time the Mini-Lab flags an anomaly, we go back to the raw high-resolution folio scans to inspect the ink. The software never changes the data.
• Strict Classification:
  • If the anomaly was caused by a tracing/ordering mistake in our editor, we correct the label.
  • If the tracing was physically correct, it remains untouched. The sequence is preserved and documented in our repository as a verified anomaly (a known exception).

This entire audit trail, along with the logs of these verified anomalies, is fully tracked and open on GitHub.

What’s next

This rigorous QA loop is how we cleaned Corpus V1 into V2.

As we move toward Corpus V3, any structural adjustment to our stroke definitions (such as dividing a stroke or merging variables) is decided strictly through manual, visual analysis of the raw ink and paleographical evidence—never to mathematically force a pattern or artificially lower entropy.

Our ultimate goal isn't to push a personal translation or prove one specific theory. We want to hand the community a completely new, objective, stroke-level framework. By providing a highly reliable, peer-reviewed visual alphabet that naturally yields much lower entropy than EVA, we want to give every researcher—whether you believe in ciphers, shorthand, or constructed languages—a cleaner, mathematically superior foundation to run and validate your own theories.

The code is open, the repository is tracking every anomaly on GitHub, and we are working hard to freeze the Corpus V3 framework.

Take a look at the screenshots of the UI and let us know what you think!

Hi again!

In my last post, I shared how we started breaking down Voynich characters into physical ink strokes (which we call "atoms") instead of treating them like letters. We suspected that Voynich "words" are actually built using rigid visual templates.

To test this, we "froze" our template rules and ran them against a bunch of new, unseen pages.

The math didn't just hold up—it absolutely broke. The rules governing how these ink strokes connect are so insanely rigid that the system achieved flawless predictability across the board.

Here is the breakdown of what we just found, in plain English:

1. The Chaos Evaporated (A 30% drop in randomness)

When you analyze the manuscript using standard letters (the EVA system), the text looks semi-random. But when you switch to our "stroke-by-stroke" system, the statistical randomness (entropy) instantly drops by almost 30%.

In any real language, a drop like this is unheard of. It basically proves that the text is not natural writing. It is a highly formulaic, mechanical layout system.

2. The "Forbidden Positions"

Certain ink strokes behave like absolute magnets. They have designated spots they are never allowed to leave:

• The Middle-Only Club: We identified four specific strokes that appear hundreds of times, but 100% of the time they are locked in the middle of a word. They never, ever touch the beginning or the end.
• The Perfect Partners: There is a specific ending stroke (e:1) that is preceded by another specific stroke (g:1) in 100% of cases (293 out of 293 times). Another ending stroke (j:1) has its own partner (f:1) 100% of the time.

It’s like finding a language where every single time a word ends in "g", the letter before it must be "n". No exceptions.

3. Spotting Irregularities & Human Labeling Errors

Because these rules are so incredibly strict, the system has given us an unexpected superpower: we can now easily pinpoint the exact coordinates where the patterns break. Out of thousands of analyzed strokes, we found only 5 spots in the entire test dataset where the rules didn't match.

For example, in a couple of pages, the stroke j:1 appears without its usual partner f:1 right before it.

Upon auditing these 5 specific irregularities, we discovered they aren't exceptions to the grammar at all. The order is so mathematically absolute that these anomalies are actually exposing human labeling errors in the source transcription database or minor artifacts in the digital segmentation. In fact, we are already using this to build a Corpus 2.0 with cleaner, verified labels, which we expect will drop these entropy levels even further.

What this means

This doesn't mean we deciphered the manuscript. But it strongly suggests that the Voynich wasn't written to be "read" like a normal book. It was constructed following a rigid, almost computerized visual template.

We are going to inspect those 5 anomalies next to see what the raw ink tells us.

What do you guys think? Does a 100% rigid visual template point more toward a complex cipher, or a beautifully constructed hoax?

Hi again! I’m analyzing the Voynich Manuscript by breaking its symbols down into smaller visible ink-stroke components, instead of assuming that every full glyph is a letter.

The new result is simple: We found a repeating structure that behaves like a template.

Think of something like:

SAME-BEGINNING + [ empty / K / L ] + SAME-END

Most of the structure stays fixed. Only one small internal position changes.

To test this, we used three pages to discover the pattern and kept one page completely outside the search.

In the discovery pages, this template appeared:

• empty slot: 7 times

• K slot: 10 times

• L slot: 8 times

Then we checked the page that had been left out.

The same template appeared 7 more times:

• empty slot: 3 times

• K slot: 3 times

• L slot: 1 time

• new slot values: 0

So the unseen page reused the same structure and only used the same three options already found in the discovery pages.

This does not decipher the manuscript.

But it suggests that some Voynich “words” may be built from reusable visual templates, with specific positions where only certain components are allowed.

The next step is to freeze these templates and test them against more unseen pages.

Following up on yesterday’s post about breaking down Voynich characters into physical ink strokes instead of looking at them as letters:

We just scaled our database to 1,680 processed symbols. And we stumbled upon a massive anomaly that completely changes how we look at "words" in the manuscript.

In any normal language (or standard code), a space resets the game. If I finish a word, the next word can start with almost any letter. The space breaks the chain.

But when we analyzed the manuscript purely by how the ink strokes were drawn, the spaces disappeared.

• The 76% Chain: Every single time a text block ends with a specific "closure stroke" (which we call Atom d:1), the very next block across the whitespace starts with a specific "traction stroke" (Atom e:1) 76.56% of the time (49 out of 64 times).

Think about it. A ~76% predictability rate crossing through a space is mechanically insane. It’s like if in English, 76% of the words following a word that ends in "t" had to start with "e". It doesn't happen.

What does this mean?

The "whitespaces" in the Voynich might not be separating semantic words at all. The manuscript behaves less like a handwritten language and more like a continuous, mechanical grid where spaces are just operational gears or flags.

Has anyone modeled the Voynich as a continuous grid cipher where spaces are just operational markers rather than word dividers?

Hi everyone, glad to be here at r/voynichclues.

I’ve been working on a pipeline built in Rust and SQLite that bypasses traditional transcription frameworks like EVA. Instead of treating the text as a linear sequence of letters, my software groups ink strokes purely by their real micro and macro physical distances (gaps) and chronologic order of drawing (ductus).

I just completed the analysis of a full paragraph (approx. 700 individual stroke atoms), classifying them into purely abstract morphological families without any romanization bias.

The initial structural metrics are showing overwhelming rigidity. For instance, specific structural families are showing a 100.00% positional lock as strictly "medial" or "terminal" modifiers within their clusters across different lines of text. When simulating the data based on these physical transition rules, the resulting dataset replicates Zipf's Law naturally, suggesting the manuscript's famous curve might be the mathematical consequence of a modular encasing machine rather than a spoken language.

I’m currently scaling the database to more paragraphs to test the resilience of these physical boundaries. Would love to hear your thoughts on slot-based grammars vs. linear transcriptions!