AI that fixes translation errors within your product.
Loqalit's AI scans your live product in real time—catching every linguistic error, text overflow, and layout break before your users ever see them.
No configuration required • Works on any web page • 60-second setup
How Loqalit Works Where Others Don't
Catch Bugs In Context, Not Hindsight
AI catches UI breaks, text overflows, and translation bugs directly on your live pages—before your users ever see them. No manual screenshots. No missing context.
Fix Critical First. Always.
Every defect is automatically ranked by severity—Critical, Major, Minor or Neutral. AI prioritizes what breaks user experience first, so your team always fixes what matters most.
Speaks Your Industry's Language
Gaming, SaaS, fintech, legal—every industry has its own linguistic rules. Loqalit's AI instantly adapts its validation to your sector's terminology and quality standards.
Reports in Seconds. Not Hours.
Generate comprehensive Translation QA reports in seconds. Export visual proofs and structured data into Excel for linguists, PDF for stakeholders, or JSON for engineering teams.
Plugs Into What You Already Use
Works natively with Crowdin, Phrase, and Lokalise. Sync automated issue reports and visual proofs directly into your existing workflow—zero friction, zero data loss.
Your Brand Voice. Every Language.
Enforce terminology, glossaries, and brand style guides across every target language automatically. Enterprise-grade AI architecture ensures absolute data privacy at every step.
Global Reach. Zero Translation Bugs.
Loqalit's AI reviews every translated page before your users do—protecting brand reputation, reducing QA cycles, and giving your team the confidence to ship fast in any language.
FAQs
We’ve Got the Answers You’re Looking For
Quick answers to your localization quality questions.
How does Loqalit detect translation errors?
Does Loqalit work with my Translation Management System (TMS)?
Why use Loqalit instead of pasting text into generic AI chats?
Can I use Loqalit on staging environments or password-protected sites?
How accurate is the error detection?