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Transsta: Translation Station - Claudia Preissinger — 18 websites ranked by shared content topics, category and on-page relevance.

Each result shows its full tech stack, contacts and AI-policy — not just a name · Browse all sites in Language Learning →

Domain	Match	Title	Country/Lang	Category	AI files	Contact	AI-protection
a-ct.net ↗	66 match 1 shared topics	HomePage-DE - ¡ACT! Avance Communication & Translation	de	language-learning WordPress WooCommerce	robots llmsaihumans	emailphone	none
gaia-translations.com ↗	65 match 1 shared topics	Gaia Translations – by Marina Schraml	de	language-learning WordPress WooCommerce	robotsllmsaihumans	emailphone	none
cherrak.com ↗	65 match 1 shared topics	AC Specialized Translations \| Anke Cherrak	de	language-learning WordPress WooCommerce	robotsllmsaihumans	emailphone	none
claudiasenglishprograms.com ↗	64 match 1 shared topics	Was biete ich an? - claudia-rihaceks Webseite!	de	language-learning Jimdo	robotsllmsaihumans	emailphone	none
palmatranslation.com ↗	64 match 1 shared topics	Palma-Translation – Übersetzer und Dolmetscher in Italienisch, Deutsch, Englisch	de	language-learning WordPress	robotsllmsaihumans	emailphone	none
translatetheweb.com ↗	63 match 1 shared topics	Microsoft Translator – aus Englisch übersetzen	de	language-learning	robotsllmsaihumans	emailphone	none
claudiagross.net ↗	63 match 1 shared topics	CLAUDIA GROSS ⋆ Redaktion, Diversity-Lektorat, DaF-Material, Lehre	de	language-learning WordPress WooCommerce	robotsllmsaihumans	emailphone	none
doraarva.com ↗	63 match 1 shared topics	Home - Übersetzung Deutsch Ungarisch Englisch, magyar német angol fordítás, English German Hungarian Translation	de	language-learning	robotsllmsaihumans	emailphone	none
translateit4you.com ↗	62 match 1 shared topics	translate it- polnische Übersetzungen, Iweta Hartman, Bamberg	de	language-learning WordPress	robotsllmsaihumans	emailphone	none
ctc-academy.de ↗	62 match 1 shared topics	CTC-Academy \| Premier Education & Tutoring in Germany	DE de	language-learning	robotsllmsaihumans	emailphone	none
travagin.com ↗	62 match 1 shared topics	Laura Travagin - Home	de	language-learning	robotsllmsaihumans	emailphone	none
businessenglish-for-you.de ↗	62 match 1 shared topics	Conversation & Business English, Dresden, Paul Ashley	DE de	language-learning	robotsllmsaihumans	emailphone	none
deutsch-lernen-ebooks.com ↗	61 match 1 shared topics	B1 Prüfung & Deutsch lernen – Präsentationen, Briefe, A1 A2 B1 eBooks	de	language-learning	robotsllmsaihumans	emailphone	none
trainerdoppel.com ↗	61 match 1 shared topics	Trainerdoppel Scheinert \| Forberg – Planspiel & Wirtschaftsenglisch im Trainerdoppel \| Business Simulation & Business English with a trainer team	de	language-learning WordPress WooCommerce	robotsllmsaihumans	emailphone	none
translito.com ↗	61 match 1 shared topics	WWW.TRANSLITO.COM : Online 47 Sprachen Übersetzungen und Wörterbuch	de	language-learning	robotsllmsaihumans	emailphone	none
communicating-internationally.de ↗	61 match 1 shared topics	,,Wer fremde Sprachen nicht kennt, weiß nichts von seiner eigenen.” - communicating-internationallys Webseite!	DE de	language-learning Jimdo	robotsllmsaihumans	emailphone	none
deine-sprachtrainerin.de ↗	61 match 1 shared topics	Deine Sprachtrainerin - Startseite	DE de	language-learning	robotsllmsaihumans	emailphone	none
ab-daf-h.com ↗	61 match 1 shared topics	Aktuell - Aktionsbündnis DaF Hannover	de	language-learning Jimdo	robotsllmsaihumans	emailphone	none

How the match score works

Each match is a 0–100 similarity score — the higher it is, the more two sites resemble one another. It’s computed automatically from our own crawl data (never from what a site says about itself) by combining several independent signals, so a high score means several of them point the same way:

shared topics how many of the same fine‑grained content topics (IAB sub‑categories) both sites cover — the main signal.
same category whether they sit in the same business / industry category.
content & title how closely their titles and page descriptions line up in wording and meaning.

No single signal decides the result — they’re blended together. Treat the score as a way to rank candidates rather than an absolute percentage; the chips on each result show which signals contributed.