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Lilt vs Crowdin

LiltCrowdin

Bottom line: Lilt for large enterprises; Crowdin for product and engineering teams doing continuous localization.

Enterprise AI translation platform combining contextual models with human verification

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Cloud localization management for software, apps, and content

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Votes00
PricingContactFreemium
CategoryTranslationTranslation
Tags
translationlocalizationenterprisehuman-in-the-loopadaptive AI
localizationtranslation-managementsoftware-localizationdeveloper-toolscollaboration
Best for
  • large enterprises
  • global product and support teams
  • localization managers
  • Product and engineering teams doing continuous localization
  • Open-source projects needing free collaborative translation
  • Documentation and content teams managing many languages
Pros
  • Adaptive contextual models that learn from translators in real time
  • Human-in-the-loop quality control
  • Deep connectors and API for enterprise systems
  • Enterprise security including SSO/SAML and high uptime
  • Strong investor backing and roughly $138M raised
  • Generous free tier, especially valuable for open-source projects
  • Deep integrations with GitHub, GitLab, Figma, and CI/CD
  • Strong automation for continuous localization workflows
  • Translation memory and glossaries reduce repeat work and cost
  • Supports both machine translation and human review
Cons
  • No public pricing; enterprise sales only
  • Overkill for small or occasional translation needs
  • Requires integration and onboarding effort
  • Cloud-based rather than self-hosted
  • Value depends on sustained content volume
  • Costs rise with seats and hosted word volume
  • Implementation and training can add significant overhead for large rollouts
  • Advanced integrations and MT engines are limited on the free tier
  • Interface has a learning curve for non-technical translators
  • Enterprise features require moving to a separate, custom-priced product

Comparison generated from each tool's listing. Add or remove tools above to change it.