FREE EXPERT COURSE

AI-Powered Localization Quality: From Human Review to Intelligent LQA

AI: Essential in Localization Quality

Localization workflows are evolving rapidly. With tighter deadlines, higher content volumes, and growing language coverage, traditional quality assurance methods alone are no longer enough.

This session explores how AI-powered language quality tools are reshaping localization, supporting linguists, project managers, and LSPs in detecting errors, enforcing style consistency, and improving overall translation quality at scale.

From Manual Review to Intelligent LQA

Rather than replacing human expertise, AI can act as a second set of expert eyes, flagging linguistic issues that are easy to miss and helping teams focus their effort where it truly matters.

In this course, we’ll look at how AI fits into real localization workflows, what types of errors it can reliably detect, and how language teams can adopt these tools without disrupting existing processes.

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  • This webinar includes:
  •    Expert panellist: Marco Baglioni, CEO & Co-Founder at LanguageCheck.ai
  •  Lifetime access to the course and extra contents
  •  In English
  •  TranslaStars Certificate of Completion
  •  Course duration: 2 h (approximately)
  •  When: 8 April, 16.00 CET
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AI-Powered Localization Quality

From Human Review to Intelligent Language QA

Session 1 - From Human Review to Intelligent Language QA
SESSION 1

From Human Review to Intelligent Language QA

Session 1

1.1 Why LQA is changing in the age of AI
1.2 Common quality challenges in multilingual and large-scale localization projects
1.3 How AI can support linguists without replacing human judgment
1.4 What makes the difference during the PE task?
1.5 How to integrate AI language QA into existing localization workflows
1.6 Practical examples of AI-assisted language quality checks in action
1.7 Key considerations when adopting AI tools in localization teams

Course Description

This course provides a practical, non-technical introduction to AI-powered language quality assurance within localization.

Participants will gain a clear understanding of:
  • How AI evaluates language quality
  • How it differs from traditional QA tools
  • How it complements translators, reviewers, and LSP workflows
  • The effective advantages of using AI

Rather than focusing on theory, the course highlights real-world use cases, best practices, and decision-making criteria to help localization professionals assess whether and how AI language QA can add value to their projects.

The goal is to equip attendees with actionable knowledge they can apply immediately, whether they are managing vendors, reviewing translations, or scaling multilingual content production.

Who is this course for?

This course is ideal for:
  • Localization Managers and Localization Leads
  • Project Managers working with multilingual content
  • Language Service Providers (LSPs) and Vendor Managers
  • Translators and Revisers interested in AI-assisted QA
  • Content and International Marketing Managers
  • Anyone curious about how AI is practically used in localization today

No technical background or prior AI experience is required

Resources

Linguistic skills and previous knowledge:
  • A good English level is required
  • Familiarity with localization processes (TMS, translation pipelines)

IT resources:
  • A computer with speakers as well as a stable internet connection are necessary

Availability:
  • Life access to the recording of the course and extra contents

Marco Baglioni

| CEO and co-founder of LanguageCheck.ai
About MARCO
Marco Baglioni is the CEO and co-founder of LanguageCheck.ai, an AI-powered platform dedicated to translation and localization quality assurance.
He began his career in the translation industry in 1999, gaining first-hand experience of the challenges faced by translators, reviewers, and localization teams in managing quality at scale.
In 2014, Marco shifted his focus to language technologies, working at the intersection of linguistics and artificial intelligence to improve how multilingual content is reviewed and evaluated.
With more than two decades of experience in the language industry, Marco combines a deep understanding of human translation workflows with a practical approach to AI adoption, helping language professionals use technology to enhance, rather than replace, human expertise.
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