Help center & knowledge base translation
Support content is high-volume and always changing. We translate help centers with the right mix: machine translation plus human post-editing at scale, terminology locked to your actual UI.
Support content is a different translation problem
A help center is not like a contract or a UI. It is big — hundreds or thousands of articles. It changes constantly, because the product does. And each individual article is low-risk: a slightly awkward sentence in a how-to guide costs little, while the same sentence in a warning label or a clause could cost plenty.
That risk profile changes the right answer. Translating every article with full specialist attention would price most teams out of multilingual support entirely — so they ship English-only help centers, and their international users file tickets instead of self-serving. The economics need a different tool.
MTPE: the honest middle
Machine translation post-editing (MTPE) means a machine produces the first draft and a professional human editor corrects it — fixing mistranslations, terminology and awkward phrasing rather than translating from scratch. For instructional content with clear sentence structure, it delivers reliable quality at a cost and speed that makes a large multilingual help center feasible.
The machine never publishes unsupervised. Every article passes through a human post-editor working against your term base — the same rule we apply everywhere, applied economically: machines draft, humans sign off.
Not every article belongs in that lane. Billing terms, security documentation, privacy and data-handling articles, anything with legal weight — these get full human translation with independent second review. Our quote sorts your content into lanes explicitly, so you pay MTPE rates for the how-to guides and specialist rates only where the risk justifies it.
Consistency with the UI is the whole game
A help article has one job: to let the user fix something without filing a ticket. It fails at that job the moment it tells them to click a button that does not exist — because the article says “Preferences” and the button says “Settings” in that language.
So terminology is the backbone of our help center work:
- One term base per language, built from your actual UI strings, enforced on every article — whether human-translated or post-edited
- Screenshots flagged for locale — we identify which images show English UI so you can plan localized captures, and translate captions consistently either way
- Product names, feature names and error messages rendered exactly as they appear in the product, never paraphrased
If we localize your UI, docs and help center together, this consistency is automatic — one practice group, one term base, one source of truth.
Built for content that never stops changing
Help centers are never finished, so the workflow assumes change. Translation memory stores every sentence we translate; an updated article costs you the delta, not the article. For Zendesk, Intercom and similar platforms, articles can flow through an integration rather than manual exports, so your languages stay days — not months — behind the source.
Start by sending us a content export and your target languages. Within 24 hours you get a fixed quote, split by lane: what MTPE covers, what needs human translation, and what the ongoing update flow will look like.
Frequently asked questions
Is machine translation good enough for help articles?
For most of a help center, machine translation with human post-editing (MTPE) is the right tool: a human editor corrects the machine output, at a lower cost than full translation. For sensitive articles — billing, security, legal, data handling — we recommend full human translation, and the quote tells you which articles fall where.
How do you keep article terminology matching the UI?
Your UI labels live in a term base, and every article is translated or post-edited against it. When an article says to click "Settings", it uses exactly the word on the button in that language. If we localized your UI, the term base already exists; if not, we build it from your string files first.
What happens when articles are updated?
Translation memory stores every translated sentence, so an updated article is quoted on the changed sentences only. For help centers on platforms like Zendesk or Intercom, content can flow through an integration instead of manual exports, so updates go out in all languages days after the source changes.
Which languages should a help center launch with?
Usually the languages where your support ticket volume is highest — translated self-service content directly reduces tickets in those queues. We cover 30+ languages and can start with your top two or three markets, expanding as ticket data justifies it.