— From literary fiction to localization at scale —
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The old town unfolds at its own pace — a courtyard here, a hidden café there. Sit where the locals sit, try whatever the waiter recommends, and let the city come to you. The best discoveries here happen by accident, somewhere between your second coffee and a conversation you half-understand.
El casco antiguo se despliega a su propio ritmo: un patio aquí, un café escondido allá. Siéntate donde se sientan los locales, pide lo que recomiende el camarero y deja que la ciudad venga a ti. Los mejores descubrimientos aquí suceden por casualidad, en algún punto entre tu segundo café y una conversación que solo entiendes a medias.
Ask about this translation —
Batch translation, QA built in, and a styleguide per client — so a 50-page job reads like one translator wrote it.
Translate faster, deliver better →Define your tone once. Batch your backlog. Ship in any language before the publishing window closes.
Publish on your terms →Shared glossaries, shared styleguides, comment threads on every block — twelve languages from one source of truth.
Scale your team workflow →DOCX, PDF, MD, TXT — or paste raw text. Side-by-side editor, your language pair on the way in. Translation is the starting point, not the destination.
Build once, toggle on per project. Terminology stays consistent — page 1 to page 500, language 1 to language 12.
Sentence-level control. Add a custom direction ("more formal," "keep the metaphor") and your glossary and styleguide feed in automatically — so the rewrite obeys your terminology and stays in your tone. The rest of the page stays put.
A literary editor at your side — and she remembers your projects and preferences between documents. She reads the translation, flags where the tone has flattened or the meaning has drifted, and leaves comments on the blocks that need a second look.
A clean reading view for the final pass. Comments on any block; reply and resolve in place. Send a link to a reviewer or client — 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 | ||||
| Memory across documents | ||||
| 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.
One credit = one source word translated in Standard mode. Premium mode uses a deeper model and costs 3 credits per source word. Manual edits, exports, comments, and review activity are free — credits are only spent when a block is translated by AI.
For your first projects
Standard mode, 1 credit per word.
For regular client work
For agencies & large catalogs
Prices are in EUR. VAT is added at checkout where applicable — EU consumers see local VAT, while EU businesses with a valid VAT ID pay the net price under reverse charge. Top up any paid plan with credit packs — 50,000 credits for €5, 200,000 for €18, or 500,000 for €40 — and pack credits never expire. Cancel anytime; 7-day money-back guarantee on your first subscription payment, no questions asked.
Two writers, one problem.
— Vitalii.I 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.
— Mariia.I write semi-fictional stories about real people, built around how it felt. Most of the people I wrote about were foreigners. We met in English, spoke in English, lived those moments in English. So I wrote them that way too.
“But I sometimes wonder what version of them I missed by not writing them in their language.”Mariia
— Vitalii.The same flatness hit me from the other side. Every tool I tried preserved the words but killed the voice. Tone, rhythm, wit, emotional texture — nothing held. It all came back flatter than it went in.
— Both of us.So we did what we know how to do. We read the machine-translation papers. We benchmarked Claude, GPT, Gemini, and a handful of open models on the same 50-page chapter — judging accuracy, tone, and whether the satire still landed. None of them held all three; each failed in a different way. So we built the tool we wished had existed when we started.