Updated: 29 / 09 / 2022
info_outline General Info
|Country of Origin:||Germany|
Lexeri is language assistance software with which employees of a company can communicate in a target group-specific and consistent language.
Lexeri provides them with a digital tool with which they can collaboratively develop their corporate language to match their products and the core of the brand and use it in everyday content creation in CMS, editorial systems and office environments.
Toptranslation was founded in 2010 and started as a technology focused translation agency. In 2018 Toptranslation started the development of Lexeri as an addon to its customer dashboard. In 2020 Lexeri became a standalone product. Toptranslation currently employs about 32 people in Hamburg and Sevilla.
Term extraction is currently offered as a separate service.
Term candidates are then imported as drafts into the Lexeri workflow system.
Will be fully integrated in the future.
Integrations with TMS currently work via TBX export. There’s also a custom MemoQ-CSV export
Lexeri is currently focused on terminology management with a customizable workflow system and NLP backed terminology checks. Until the end of the year 2022 Lexeri will start developing authoring assistance features that help improve readability or matching the corporate language and styleguides of an organization.
Lexeri pricing is user based and divided in two licensing types.
The team license starts with 5 users minimum and a monthly cost of 100 EUR and includes all functionalities and add-ins.
Each additional user costs 15 EUR.
In addition to that, the enterprise license offers Single Sign-On functionalities and other enterprise focused features. Prices for this license are custom for each organisation. Lexeri offers a free trial via its website or individually after contacting them.
build QA check
For morphology support, Lexeri uses NLP language models for the term checks that allow for matching morphological version of terms not specifically listed in the termbase.
Methods like lemmatisation and part of speech tagging are used for this.
|Media support||check_circle Supported|