Machine translation & AI quality
How this is scored
What the machine translation does and how well it is controlled: the languages and language pairs covered, the engine (own neural or LLM model, or a choice of third-party engines such as DeepL, Google, Microsoft or an LLM), glossaries and formality applied during translation, document translation that keeps the layout (Word, PowerPoint, PDF, InDesign), custom or adaptive models trained on the customer's own translations, automatic quality estimation or scoring, and published evaluations of translation quality.
0 — No machine translation of any kind, and no way to connect an engine.
3 — Machine translation is offered or one engine can be connected; languages, glossary use and quality controls are basic or not described.
5 — Machine translation for the major European and world languages with the list published, glossaries applied during translation, a formality or tone setting, document translation that keeps formatting for common office formats, and either an own engine or a choice of several named engines.
8 — Custom or adaptive models that learn from the customer's translation memory or corrections, automatic quality estimation per segment with a threshold that routes weak segments to human review, LLM-based translation with style guides and context, engine selection per language pair stated, and a published quality evaluation with its method.
10 — Translation quality that an organisation can measure and steer: evaluations against named benchmarks or blind human review published with their method, quality estimation calibrated and explained, custom models with their training data and isolation documented, and every machine-translated segment traceable to the engine, model version and glossary that produced it.
The In-House Document Translator
For my desk this covers the essentials: 189 languages with any-to-any pairs, glossaries enforced during translation (TSV, CSV or TMX import, with case handling and fine-grained permissions), and document translation that preserves the original formatting and layout for Word, PowerPoint and PDF, including scanned PDFs — though the documentation warns that content inside text boxes is not translated. Custom AutoML models and LLM-based Adaptive Translation that works from our own datasets are available, but custom models cover only 53 language pairs via English, and we found no published quality evaluation with its method and no formality or tone setting. 1 3 4 5