Question 1

Which localization tool should I pick for an AI-generated app?

Accepted Answer

Start by deciding whether your bottleneck is extraction and structure or translation workflow. If your UI is still mostly hardcoded English from Cursor, Copilot, or similar agents, you need infrastructure that scans the repo, proposes keys, and keeps locale files aligned on every Git push before a TMS adds value. If you already have stable keys and professional translators, a translation management system is the right layer. Use the comparison cards above to open the page that matches your situation.

Question 2

What is the difference between a TMS and localization infrastructure?

Accepted Answer

A translation management system (TMS) coordinates human translators, glossaries, assignments, and import or export of segments your app already exposes as keys. Localization infrastructure targets the earlier problem: finding user-visible strings inside components, deduplicating literals, generating catalogs, and automating sync so engineers are not blocked on manual cleanup. Many AI-built products need the second layer first; the TMS becomes relevant once catalogs are trustworthy.

Question 3

Do I need both globalize.now and Lokalise or Crowdin?

Accepted Answer

They are complementary for many teams, not duplicates. globalize.now focuses on producing and maintaining translation-ready structure from real code on every push. Lokalise or Crowdin excel once those segments exist and humans need collaborative review, pricing, and delivery workflows. If you try to replace infrastructure with a TMS alone, you still owe the refactor from hardcoded UI to keys; if you skip a TMS forever, you may still want one when translator scale arrives.

Question 4

Which tool is cheapest for a solo developer shipping fast?

Accepted Answer

Cost depends on whether you pay with engineering time or subscription seats. A TMS often charges per seat or string volume while your repo still contains duplicate English and fragile literals, which hides rework in engineering hours. Infrastructure that automates extraction and sync reduces that hidden tax early. Compare each vendor’s published pricing and limits, then weigh how much manual i18n cleanup you would do without automation on every feature branch.

Question 5

Which tools work natively with Cursor, Claude Code, or GitHub Copilot workflows?

Accepted Answer

Agent-native setup means your coding assistant can install skills, run a CLI in the repo, and open diffs without a separate export portal. globalize.now is designed around that loop: run skills in the project root, review proposed key and locale changes in Git, and merge like any other feature. TMS products can integrate with Git but rarely rewrite JSX for you; pairing agent skills with a TMS later is a common mature pattern for AI-generated apps.

Question 6

How do I choose between i18next and globalize.now?

Accepted Answer

i18next is a mature runtime library for loading messages, plural rules, and namespaces in the browser or server. It does not replace the need to extract hardcoded strings from AI-generated components or to keep locale files synchronized with every push. globalize.now targets repository automation and structure; many teams use both, with infrastructure producing catalogs and i18next rendering them. Open the i18next comparison for a feature-level view.

Compare globalize.now

Lokalise

Crowdin

i18next

lingo.dev