Building AI Products for a Global Audience: 7 Practical Lessons

AI products are global from day one.

A developer may discover your product in English, configure it in Chinese, read the documentation in Japanese, and debug an API response with a distributed team across several countries.

That makes localization more than a translation task. It is part of the developer experience.

Here are seven practical lessons we learned while building a multilingual experience for an AI API platform.

1. Design for localization before translating

Avoid placing interface text directly inside components.

Use translation keys from the beginning:

t("navigation.documentation")
t("dashboard.apiKeys")
t("errors.invalidRequest")

This makes it much easier to add languages later without modifying every page.

2. Keep technical terms consistent

Terms such as API, token, endpoint, model, request, and response are already familiar to many developers.

Translating every technical term can make documentation harder to understand. A better approach is to keep standard developer terminology while translating the surrounding explanation.

Consistency is more important than literal translation.

3. Expect text length to change

A short English button label can become much longer in French or Russian.

Interfaces should therefore avoid fixed-width text containers. Navigation items, buttons, alerts, and pricing cards all need enough flexibility to accommodate different languages.

Test the real translations—not placeholder text.

4. Keep code examples language-neutral

Code snippets should remain easy to copy regardless of the selected interface language.

For example:

curl https://your-api-endpoint/v1/chat/completions \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json"

Translate the explanation around the example, but avoid changing field names, endpoint paths, and commands.

5. Localize the complete onboarding journey

A translated homepage is only the beginning.

Developers may also need localized:

• Registration guidance
• API key instructions
• Error messages
• Billing explanations
• Documentation navigation
• Support information

If users switch back to an unfamiliar language immediately after registration, the localized landing page has not solved the real problem.

6. Make language switching predictable

The language selector should be visible, easy to recognize, and available without signing in.

Remembering the selected language also matters. Users should not need to change it every time they return.

We currently provide seven interface languages:

• Simplified Chinese
• English
• French
• Russian
• Japanese
• Vietnamese
• Traditional Chinese

7. Measure the experience by locale

Traffic alone does not tell you whether localization works.

Useful measurements include:

• Registration conversion by language
• Documentation visits by locale
• API key creation rate
• Onboarding completion
• Support requests by language
• Errors encountered during setup

These signals help identify translations that are technically correct but still confusing.

What we are building

We applied these ideas while developing APIHubRelay, an OpenAI-compatible API gateway designed to make access to multiple AI models easier for developers.

The goal is simple: developers should be able to explore and use AI infrastructure without language becoming an unnecessary barrier.

If you are building a multilingual developer product, what localization issue surprised you the most?

---

Disclosure: I am involved in building APIHubRelay. AI tools were used to assist with the structure and language editing of this article; the technical points and final review were completed by the author.