The Latest News

This section is updated almost daily with the most current industry-related press releases we receive.

KantanAPI SDK adds Asynchronous Interface


KantanMT, a subscription-based machine translation service, has announced that its Software Development Kit (SDK) will be enhanced by the addition of a new Asynchronous Interface. The new interface is intended to help clients that require high volume translations, but not in real-time by queuing translation requests and processing them when compute capacity is available.


Past news for KantanMT

Irish neural MT engine


KantanMT, a subscription-based machine translation service, has launched an Irish neural machine translation (MT) engine using KantanNeural technology. The engine has been added to KantanFleet, a collection of over 40 neural MT engines.

KantanMT Across Connector


KantanMT, a subscription-based machine translation service, has launched KantanMT Across Connector, a connector that integrates neural machine translation into the Across Language Server by Across Systems GmbH, a manufacturer of corporate translation management systems.

KantanLQR split testing feature


KantanMT, a subscription-based machine translation service, has introduced a split testing feature for KantanLQR that allows clients to test and compare machine translation (MT) output from up to four MT engines. The new feature follows the recent launch of neural MT stock engines, available within KantanFleet.

KantanMT upgrades


KantanMT, a subscription-based machine translation service, has updated its data resource library, KantanLibrary. The upgrade includes 204 new bilingual data sets in seven industry verticals and 59 new language combinations.
KantanMT has also announced a new finger-tip functionality to allow clients to switch deployment from On-Premise, hosted within the clients' own infrastructure, to the KantanMT Cloud Hosted option.

KantanMT collaborates with ADAPT Centre


KantanMT, a subscription-based machine translation service, in collaboration with ADAPT Centre, has developed a platform optimization technique intended to improve the performance of its core technology. The new optimization incorporates research into varying translation models similar to the IBM model 2 approach.

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