Writing and content decision

Crowdin

Build a useful, narrow localization workflow yourself (sync, AI pre-translate, editor, QA), but replicating Crowdin’s integrations, Copilot orchestration, dubbing, and enterprise polish/scale is expensive and time-consuming—worth self-hosting for limited needs, not a full replacement.

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Subscription$59/month
Initial build80 hours
Monthly upkeep8 hours + $50
Evidence3/3 runs agree

Open-source builds that already do this

Every project below is open source and already does this job today. Fork one, self-host it, or take the parts you need — the build prompt further down assumes an empty file, and this is the shortcut past that. Licences differ; check the one on each card before you ship.

What a replacement has to do

  • Sync source strings from a repo/CMS, generate AI pre-translations, present an editor for human review with TM/glossary suggestions, run QA checks, and sync approved translations back to the codebase or CMS.

What it still won’t have

  • The 700+ ready-made integrations/app marketplace
  • Crowdin Copilot orchestration and task automation features
  • AI dubbing studio and built-in audio/video localization tooling
  • Enterprise polish, scale, and managed services (over-the-air SDK, AWS Marketplace packaging)

What remains hard

  • Product polish and ongoing maintenance
Read the build prompt

First-year cost

Keep paying

Paying ischeaper in year one.

On cash alone, building overtakes the subscription at 1 seat.

Paid seatsseats

Money you would actually spend

Keep paying

Subscription price × seats × 12

Build it

AI build APIs + hosting

Time you would spend

What you would spend

What we assumed

The verdict above measures whether you could build it. This one is only about money.

Runnable build prompt

Not run yet
Build a minimal self-hosted localization service using Node.js (Express), Postgres, Redis, and a React-based editor. In scope: (1) webhook/CLI to import source files from GitHub and a CMS and export translated files back (create PRs), (2) a Postgres schema for projects, source strings, target translations, and Translation Memory, (3) integration with at least one external MT/LLM provider via API keys for pre-translation, (4) a web translation editor with TM/glossary suggestions and save/approve flow, (5) an automated QA step (placeholder/format/length checks), and (6) background worker for tasks (BullMQ). Out of scope: audio/video dubbing, large-scale integrations marketplace, enterprise billing/managed services. Include error handling, input validation, authentication (JWT + workspace multi-tenancy), and automated tests for API endpoints and the editor save/approve flow.
How we checked5 sources · 3/3 runs agreed · evidence score 64

How the score was reached

  • Partly verdict base52
  • An open-source build was found+5
  • 5 cited sources+3
  • 3/3 assessment runs agreed+4
  • Evidence score64

The base comes from the verdict. Everything under it is a check that either happened or did not, and each one is a fact frozen in this record rather than a judgement made at render time — so the same evidence always produces the same number.

How scoring works →

Integrity checks

What held up, and what did not.

! Price not confirmed on the page — this pricing page renders its price in the browser✓ 3 independent runs, one answer✓ Citations limited to fetched pages! 1 moat recorded