Delivering fast and cost-effective translations

inWhatLanguage makes it easy to start working with MT through its extensive support for engines and advanced MT management features on our translation platform. 

Workflow Automation

Supported Machine Translation Engines

We make it easy to start using MT with our fully managed engines, which can be enabled with a single click. You can also add supported engines manually to take advantage of AI-powered features like MT Quality Estimation and MT Autoselect.


Amazon Translate

Amazon Translate is a neural machine translation service that delivers fast, high-quality, and affordable language translation.



DeepL helps users save valuable time, globalize their business, and easily scale their translations. DeepL offers world-leading data security, which includes end-to-end data encryption and ISO 27001 certified European data centers.


Google AutoML

Developers, translators, and localization experts with limited machine learning expertise can quickly create high-quality, production-ready models. Just upload translated language pairs and AutoML Translation will train a custom model that you can scale and adapt to meet your domain-specific needs.


Google Translate

Google Translate enables organizations to dynamically translate between languages using Google’s pre-trained engine. With Google Translate users can instantly translates texts into more than one hundred languages for fast, dynamic results.

Human Science

Human Science offers unique neural machine translation solutions their customers, including the development of custom models. MT systems built by Human Science have offer high levels of security for both on-premise systems and cloud systems that do not require internal servers.


Microsoft Custom Translator

Microsoft Custom Translator allows users to customize Microsoft Translator’s advanced neural machine translation to create translations that better understand the terminology used in their own business and industry.


Microsoft Translator

Microsoft Translator is a pre-trained cloud-based machine translation service supporting 90 languages and dialects. Built for business, Translator is a proven, customizable, and scalable technology for machine translation.


Rozetta Translate

Rozetta Translate is an exclusive machine translation model developed for inWhatLanguage. It is ideal for translations between Japanese and English and includes support for multiple domains, such as Legal and Medical.


Systran PMNT

SYSTRAN’s Pure Neural MT is based on complex algorithms that enable the engine to learn the rules of a language from a given translated text and produce high-quality translations.


Tencent TranSmart

Tencent TranSmart is a unique MT solution that combines both neural and statistical machine translation models and supports over 160 different language pairs.

Ubiqus NMT

Ubiqus NMT offers a breadth of engines for varying levels of translation needs. Of the 300+ engines available through Ubiqus NMT, 80% are for general translation, covering the most commonly request language pairs, while the remaining 20% are specialized for industries as finance, medical, legal or technology.

Yandex Translate

Yandex Translate uses machine translation technology developed at Yandex to enable developers to integrate machine translation into their localization workflows. Yandex Translate is currently available for more than 90 languages.

You can add supported engines to inWhatLanguage manually via API key. These engines do not benefit from any of the advanced features available and must be configured outside of inWhatLanguage.

1,000+ brands have made the switch to inWhatLanguage

We are a proud provider of translation, localization, and interpretation services in over 200 languages for businesses, Fortune 500, and government entities worldwide. We have optimized our processes to meet their unique needs, adapting from small, on-demand tasks to high-touch, fully-managed solutions.

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“inWhatLanguage’s project managers and coordinators are the best and friendliest in the industry.”   Lauren L.