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Language AI & Translation System for your business
Discover how leaders in tech companies speed up translations, reduce errors, and accelerate global product delivery.
How teams apply AI safely in regulated and technical documentation
AI is transforming how teams produce and translate regulated and technical documentation, but speed without control creates compliance risk. This guide explains how leading teams apply AI safely, maintain audit trails, enforce terminology, and use platforms like TextUnited to keep documentation accurate, consistent, and audit-ready.
Automatic Post-Editing (APE) explained
Automatic Post-Editing (APE) improves machine translation by automatically correcting common errors. This guide explains how APE works, its limitations, and how it fits into modern translation workflows.
Why export teams keep recreating sales content instead of reusing it
This article explains why the traditional translation process breaks in export workflows, how modern systems are designed to apply translation memory (TM), and how centralized translation management helps export teams save time, reduce risk, and scale confidently across markets.
Machine translation vs Human post-editing is the wrong question in 2026
In 2026, translation is no longer a choice between machines and humans. It is an operating model decision shaped by risk, reuse, and governance. This guide explains how modern teams design translation systems that scale without losing control.
Choosing the right translation model for B2B companies in 2026
Translation in 2026 is no longer about picking a vendor or tool. This article explains how B2B companies choose the right translation models based on content type, risk, cost, and scale; and why structure matters more than technology.