Technologies
Powers our quality management
Our internal QA systems transform experience and expertise into scalable, repeatable quality intelligence.
Why Technology Matters in Localization Quality
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Our QA Technology Framework
Our internal QA system is structured as a layered framework—designed to support how quality is detected, analyzed, interpreted, and continuously improved at scale.
LayerⅠ: Detection & Capture
Detects and captures quality signals from large volumes of multilingual content—creating a reliable foundation for analysis.
Layer Ⅱ: Analysis & Intelligence
Analyzes, aggregates, and contextualizes quality signals—combining AI-driven analysis with human expertise to surface meaningful insight.
Layer Ⅲ: Decision & Improvement
Turns insight into decisions, feedback, and improvements across workflows, standards, and teams.
Technology Powering Our QA Framework
Our internal technology is designed to detect quality signals, generate intelligence, and support informed decision-making.
AI-Powered Detection Engine
iQA provides full-volume detection and capture of grammar, spelling, typo, punctuation, and culture compliance issues, ensuring broad coverage while enabling human expert to focus on deeper, high-impact QA.
Intelligence & Decision Hub
Qhub centralizes quality data, expert review outcomes, and feedback to surface insights, track trends, and support traceable decisions across projects, teams, and accounts.
Where Expertise Leads
Where Technology Stops — and Expertise Leads. Our systems scale visibility—experts provide context, severity, and accountability.
What technology enables
Makes quality visible at scale by systematically surfacing clear issues and repeatable signals—ensuring coverage, consistency, and shared visibility across languages, projects, and releases.
What LQA experts leads
Experts lead the whole LQA effort, decide what matters in context, and define what quality means—ensuring outcomes that are meaningful, consistent, explainable, and actionable.
Discover What’s Possible
Let’s work together to stay ahead of the QA curve.