Phrase Tutorial: Get Started in 5 Minutes [2026]

What it does:

AI orchestration layer that automatically selects the best MT engine per language pair and content type, with built-in glossary enforcement, formatting preservation, and Quality Performance Score (QPS) to estimate translation quality before human review.

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What it does:

Proprietary translation models combining large language model reasoning with neural MT for context-aware, fluent output tailored to localization use cases, with support for custom MT engine training on customer data.

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What it does:

Developer-focused product with REST API, CLI, GitHub/GitLab/Bitbucket integrations, branching of translation keys, in-context editor, and over-the-air SDKs for iOS and Android to ship translation updates without app resubmission.

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What it does:

Enterprise translation management system with linguist and vendor workflows, project automation, translation memory, terminology management, and detailed quality assurance checks for content, documents, and marketing assets.

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What it does:

No-code automation builder for designing end-to-end localization workflows that connect CMSs, marketing tools, MT engines, and human review steps with triggers, conditions, and routing rules.

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What it does:

Dashboards and reports on MT quality, post-editing effort, linguist productivity, vendor performance, cost per language, and project throughput, enabling data-driven optimization of localization spend.

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What it does:

Native plugins for Figma, Sketch, and Adobe XD let designers send copy for translation in context, while in-app screenshots and previews give linguists visual context for accurate translations.

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