Localization Guide for Developer: Advanced AI Workflows

Lightning fast, continuous localization. Decent quality. Super affordable. All automated with no humans in the loop.

This guide shows you how to build a multilingual product on autopilot using Crowdin. The workflow is tech stack agnostic and suitable for web, mobile and desktop applications, as well as their documentation and marketing materials.

Let AI to have all the information it needs to produce the best possible AI translations. You still are able to bring in human linguists to improve translations.

Prerequisites: You have an internationalized web or mobile application. This means that all translatable texts from the UI have been extracted into the resource files. The implementation time of this guide is 30 minutes.

Create Crowdin Account

Visit the Pricing page, find the Free plan option, and click Get Started to sign up for a free plan.

While Crowdin offers a generous free plan, you may need a paid plan for content-heavy projects.

Create Translation Project

The Crowdin project is just like a Git repo but for translation files. To create one, visit this page. Once you have completed this step, you should find a Crowdin project ID and save it.

Configure AI Provider and the Prompt

Please follow the quick start guide to configure AI in your Crowdin account. Once completed, you will be able to find a Prompt ID, which is needed for the next step in this guide.

Install CLI tools

To get started, you’ll need the Crowdin CLI to manage your configuration, sync source files, and handle context extraction.

npm i -g @crowdin/cli

Configure ENV Variables

Crowdin CLI requires CROWDIN_PERSONAL_TOKEN and CROWDIN_PROJECT_ID variables to be set to authenticate and communicate with Crowdin. Visit the Settings -> API page to create a personal API token.

Crowdin CLI would need Projects scope. Context Harvester would require the Projects and AI scopes.

Store the personal Auth token in the ENV variables:

export CROWDIN_PERSONAL_TOKEN="xxxxx"
export CROWDIN_PROJECT_ID=xxxxxx

Configure Crowdin CLI

We recommend placing crowdin.yml at the root of your repo. It’s needed during the initial setup and ongoing CI/CD localization.

Run the following command to initialize crowdin.yml:

crowdin init

The command will create crowdin.yml in your work directory. Here’s what a simple config might look like:

preserve_hierarchy: true

files:
  - source: "/locales/**/*"
    translation: "/%two_letters_code%/%original_file_name%"

Edit the source and translation properties in the files section or add more objects if you have multiple sets of localization files. For more advanced configurations, please refer to the Crowdin CLI documentation.

Upload Source Files

Now it’s time to do the first upload of your translation resources to check the connection and configuration.

Add the --dry-run option to preview what files will be uploaded to Crowdin:

crowdin upload sources

Extract Context from the Code

Context harvesting is critical for UI copy localization. Both human translators and AI models struggle to accurately translate short UI labels (like “Save” or “Post”) without knowing where they appear in the app.

Instead of running legacy scripts or manually setting up AI provider credentials, you can now harvest string context using native Crowdin CLI context management combined with Crowdin Skills for AI coding agents (Claude Code, Cursor, Copilot, Gemini CLI, etc.). Read our dedicated guide on how to automate i18n context with AI agents using Crowdin Skills to generate precise translation context descriptions directly from your codebase.

Step 1: Install Crowdin Skills

Teach your AI agent how to extract context by adding Crowdin Skills to your workspace:

npx skills add crowdin/skills

This equips your agent with:

• context-extraction: Teaches the agent best practices for writing concise UI descriptions.
• crowdin-context-cli: Teaches the agent how to handle context CLI commands.

Step 2: Download String Context

Export your project’s strings to a local .jsonl file:

crowdin context download

By default, this generates crowdin-context.jsonl. You can also filter for specific strings (e.g., only those missing context):

Step 3: Enrich Context with Your AI Agent

Prompt your AI coding agent in your IDE or terminal:

“Using Crowdin skills, enrich the context for empty strings in crowdin-context.jsonl”

Your AI agent will analyze your local codebase, figure out where each UI string is rendered, and populate the ai_context fields with 1–3 sentence descriptions.

Step 4: Upload Enriched Context to Crowdin

Once your agent has processed the file, push the enriched context back to Crowdin:

crowdin context upload

Other ways of providing context for localization projects are Screenshots, context applications, and context request workflow.

Translate Content

Use the prompt ID created at the beginning of this guide and run the pre-translate command to have your content translated:

crowdin pre-translate --ai-prompt=xxx

Learn more about the command and the different options you can apply to improve the outcome. For larger projects, we recommend setting up a CI/CD localization workflow.

After the initial translation you might want to check your Crowdin project to verify translations are complete and see if you want to adjust Crowdin project settings, like automatic QA checks.

Download Translations

Run crowdin download to download translations.

crowdin download

Learn more about the download translations command.

Continuous Localization

To make Crowdin part of your product development cycle and translate new content as it’s created, you’ll need to repeat the last 4 steps in your CI/CD. Basically:

• Upload the latest source files every time they are changed;
• Extract context;
• Translate;
• Download translations;

Find out more about Crowdin Github Action and Crowdin CLI in CI/CD pipelines.

Automate AI Workflows with Crowdin Skills

While CLI tools and CI/CD pipelines automate standard synchronization, you can now bring AI agents directly into your development workspace using Crowdin Agentic Skills.

If you use AI assistants like Cursor, Claude Desktop, or custom LLM scripts, these open-source skills teach your AI how to navigate Crowdin’s ecosystem using natural language:

• Automating UI context: Instead of running manual harvesting scripts, learn how to automate i18n context with AI agents to automatically generate and enrich translation context descriptions directly in your project.
• Smart search and querying: Need to find duplicate keys, clean up legacy TM, or build custom CI/CD checks? Discover how to search and filter localization resources using CroQL and GraphQL skills to draft and run complex Crowdin API queries.

To install and start using these skills in your workspace, check out the official Crowdin Skills Repository on GitHub.

Contact us if you need more information, or if your AI translations require human proofreading to improve their quality, please choose a vendor.