Feature Overview

Build customised KantanMT engines using translation memories

Machine Translation is an important tool in your localisation mix, but how do you separate yourself from the poor and high performance engines. Machine Translation can be an efficient way to achieve higher levels of translation productivity as long as your engine is relevant, of high quality, and client-focused. KantanMT helps you easily build high performance machine translation engines for your clients, with little machine translation or technical expertise required.

  • High Performance MT: Build high-quality engines with our dashboard
  • KantanTemplates™: Use KantanTemplates to share common training data-sets across multiple KantanMT engines and update them all in one go.
  • Kantan BuildAnalytics: Use BuildAnalytics to analyse the performance of your KantanMT engines and to spot any data gaps within your training material
  • The Power of 2! KantanMT builds a TotalRecall™ translation memory to improve both the performance and accuracy of your KantanMT engines
  • Training Data: Use Translation Memory Interchange files (TMX) as training data
  • Data Cleansers: Develop your own data cleansers using our Preprocessor technology
  • Terminology: Use Terminology Interchange Files (TBX) to compliment your training data
  • KantanLibrary™ Training Sets: Use our training data sets to build larger KantanMT engines
  • Monolingual Training Data: Use monolingual training data to improve the fluency of your engines
  • Custom Test Data: Use your own test data to continuously measure quality improvements in your KantanMT engines
  • Easy Configuration: Manage all your KantanMT engines in one easy to use dashboard interface

KantanMT makes building high-performance machine translation engines as easy as 1-2-3!

Here's what our members are saying:

I am really pleased about how the platform works.

Bastin Geerts, Director, WK Automotive

KantanMT is different from the others because it is easy to use, fast, intuitive and reliable.

Raymonda Cesarela, Student, University of Alcalá

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