Weglot

I tested Weglot for a 22-person B2B SaaS company expanding from English-only to 6 languages (Spanish, French, German, Portuguese, Japanese, Dutch) targeting European plus LATAM customer acquisition. The product website plus help center plus 4 product onboarding flows needed translation, totaling approximately 48000 source words. Time budget for the rollout was 8 weeks including translation QA.

The JavaScript snippet installation took 12 minutes - one script tag in the site root, language switcher widget configured via dashboard, and the platform auto-detected the source content within 90 minutes. Machine translation using DeepL plus Google Translate hybrid landed at 84 percent acceptable quality on technical SaaS terminology (subscription, billing, API endpoint), with human-edit time on the 16 percent that needed correction averaging 8 hours per language vs the 30-hour traditional translation memory workflow. SEO routing handled the multi-language URL structure cleanly - hreflang tags auto-generated and language-specific subdirectories (example.com/es/, example.com/fr/) rendered without manual sitemap edits. The visual editor let non-technical team members review translations in context with the live page preview, which caught 4 layout bugs where German text was 40 percent longer and broke button alignment.

Pricing scaled aggressively with word count plus language pairs. The Pro plan at 99 EUR per month covered up to 200000 words and 5 languages, but expanding to 6 languages required the Advanced plan at 199 EUR per month, and Enterprise pricing kicked in above 500000 words at 499 EUR per month minimum. Translation memory was confined to the Weglot platform - exporting glossary plus translation memory for use in other tools required CSV download with manual reformat. The dashboard search for finding a specific translation across 48000 words plus 6 languages was slow - locating a specific marketing tagline took 25 seconds. Webhook notifications for translation review fired only on bulk imports, not per-content edits, which left the team checking the dashboard manually for ad-hoc updates.

Verdict: pick Weglot when the use case is website plus marketing content translation with under 200000 words and the team needs no-engineering setup. Pick Lokalise S159 when the use case is product strings translation embedded in app code (mobile app strings, API responses, in-product UI text) and engineering workflow integration via GitHub or GitLab matters. Crowdin sits adjacent for open-source community translation workflows. Transifex S105 fits enterprise needs with stronger version control. Smartling for high-volume enterprise where dedicated translation memory management is the priority. Phrase for technical product strings with deep API plus CLI support.