Who this decision is for
- A US or European generative-AI vendor whose English site is strong and who now needs Korean enterprise buyers to understand what the product does in Korean workflows.
- An AI startup with an API product that wants Korean developers and product teams to try it, but has no Korean documentation or community presence.
- A computer-vision or speech company approached by a Korean integrator and needing public Korean pages that make the vendor look credible before the next meeting.
- A marketing lead asked to justify localization spend for an AI product before knowing whether Korean-language performance holds up.
The decision to make
The core decision is what your Korean pages should claim and how you will show it. AI products attract skepticism because buyers have heard many promises. In Korea, enterprise and public-sector readers often look for a concrete use case, a working demonstration in Korean, and a clear statement of how their data is handled. You can lead with a single workflow, such as document search or call summarisation, or present a platform story and let readers find their own fit.
The trade-off is breadth against believability. A platform pitch reaches more roles but invites the question of what actually works in Korean. A narrow use case is easier to prove and easier to rank for, yet may look small. Data and privacy wording adds a second layer: statements about storage location, training use and retention must match the real product and be reviewed by Korean counsel before they appear publicly.
Options compared
| Option | Best when | Watch out for |
|---|---|---|
| Lead with one proven use case in Korean | You have a demo or sandbox that performs acceptably on Korean input and one buyer type you understand well. | Readers may assume the product does only that; add a clear path to broader capabilities. |
| Platform positioning with use-case sub-pages | Your product serves several teams and you can maintain separate Korean pages for each without diluting quality. | Too many thin sub-pages look generic; each needs its own demo, example and language checks. |
| Developer-first entry through docs and API examples | Adoption starts with engineers trying the product before any procurement conversation exists. | Localised docs must be maintained with releases, or they will quickly contradict the English version. |
Risks to manage
- Unverified Korean performance. Demos that work in English may stumble on Korean input, and a visible failure damages trust. Test with realistic Korean samples before publishing any capability claim.
- Data handling ambiguity. Vague wording about storage, model training and retention raises objections in security review. Write plain statements matching the product, then have Korean counsel review them.
- Overclaiming accuracy. Statements of accuracy or savings without a stated method are hard to defend. Describe what was measured, on what, or leave the claim out.
- Translated jargon. Literal translation of AI terms can read as odd or inconsistent to Korean engineers. Build a glossary and agree which English terms stay in English.
Evidence to gather first
- A list of Korean-language test inputs, such as sample documents, queries or audio, showing where the product performs well and where it does not.
- Your current data flow description: where processing happens, what is stored, whether customer data is used for training, and which sub-processors are involved.
- Search behaviour research showing which Korean terms buyers use for the problem your product solves, rather than the English category name.
- Existing proof you genuinely hold, such as documentation, technical write-ups, security materials or customer-approved references, with permission status noted.
Recommended process
- Positioning audit. SWIN reviews your English site, product and competitors visible in Korean search, then proposes one or two use cases to lead with and the claims that need proof.
- Terminology and tone. We build a Korean glossary for AI terms with your product team and decide which terms remain in English, so pages read as written by technical people.
- Demo and proof planning. Together we decide what a Korean visitor can try or watch, and which technical explanations, documentation and approved references support each claim.
- Page and discovery build. SWIN produces Korean pages with structured data, Naver and Google readiness and content designed to be understood by AI assistants that summarise vendors.
- Privacy wording review. We prepare data and privacy statements from your facts and hand them to Korean counsel for review before publication.
What SWIN can deliver
- A Korean positioning brief naming the lead use case, target roles and the claims that need supporting proof.
- Korean glossary of AI and product terms with notes on what stays in English.
- Korean product and use-case pages with structured data and a demo or sandbox call to action.
- Draft data and privacy summary copy prepared for counsel review.
- Keyword and intent map covering how Korean buyers describe the problem, not just the category.