— Built by translators, for translators —
A 50-page job, before lunch
Batch translation, QA built in, and a styleguide per client — so a 50-page job reads like one translator wrote it, and client #7 gets the same terminology as client #1.
DOCX, PDF, MD, TXT — or paste raw text. Sourced into blocks, ready to batch. The dashboard shows progress as the run proceeds.
Build once, toggle on per project. Client terminology and tone, applied everywhere — page 1 to page 500.
Sentence-by-sentence control. Regenerate with directions ("redo this more formally") on just the one that needs it. The rest of the page stays put.
Inconsistent terminology, missed glossary terms, style deviations — flagged with one-click fixes. Review individually or accept in bulk.
Block-level version history. If the new take is worse, snap back to the one that worked. Every action is recorded.
Send a link. They review, leave comments on any block, you reply. Resolve threads when the discussion lands. No DOCX-by-email.
Three short comparisons, then a feature row to settle it.
Put text in, get text out. Hope you like what you get. No glossary, no styleguide, no memory of what came before.
You bring the glossary, the styleguide, the tone. Multiple options per sentence. You decide what makes the cut.
By page fifty it is calling the same character three different names and forgot what sarcasm was.
Page 300 reads just like page 1. Glossary and styleguide enforced across the run.
Impressive at parties. Try fifty docs with consistent terminology. Good luck.
Who does this for a living. Upload, translate, QA every sentence, export — on time, on brand.
| Capability | Transept | Google T. | DeepL | ChatGPT |
|---|---|---|---|---|
| Voice & tone consistency | ||||
| Glossary enforcement | ||||
| Full document context | ||||
| Sentence-level editing | ||||
| Batch translate + QA | ||||
| Team collaboration | ||||
| Notion & Google Drive |
Pay for words you actually translate. Top up when you need more — extra credits don’t expire.
For your first projects
3,000 words, standard quality.
For regular client work
For agencies & large catalogs
He wrote 120,000 words of satirical romance fantasy — mages drowning in debt, a multiverse economy that makes Wall Street look ethical, and a love story tangled up in all of it.
She writes semi-fictional stories about real people, built around how it felt. Most of the people she wrote about were foreigners. They met in English, spoke in English, lived those moments in English. So she wrote them that way too.
“But sometimes she wonders what version of them she missed by not writing them in their language.”
He had the same problem from the other side: every tool preserved the words, but killed the voice. Nothing they tried could hold onto tone, rhythm, wit, or emotional texture. It all came back flatter than it went in.
So they read multiple machine translation papers. Tested every AI model they could get their hands on. And made the tool they wished had existed from the start.