While in the past the only fully automated linguistic task was machine translation, AI brought a plethora of new actions that can be automatically performed. Previously, BeLazy was only able to extract an XLIFF from a TMS, and import that XLIFF back into the TMS at the end of the project. Custom Workflow steps enable the automation of any TMS and BMS step.
In TMS connectors with XLIFF support, you can now export XLIFF from any step, and import another XLIFF back to the same step. In the BMS connectors, including BeLazy’s own REST API, you can now close any job, which means that BeLazy can trigger closing the job in the TMS as well. This opens up new horizons for every use case where XLIFF transformation is needed, which is pretty much every AI action: machine translation quality estimation, machine translation, automated post-editing, glossary extraction, you name it.
While BeLazy right now does not contain any AI automated actions, you can easily use tools like Make, n8n, Blackbird or LLM-based coding tools such as Lovable, Bolt.new, Base44 or Replit to process the resulting XLIFF with any tool of your choice including popular LLMs such as OpenAI or Claude, and send it back via the files API. This implements a third API use case for BeLazy. If you want to be AI-ready, probably BeLazy is your best bet now, because we separate the AI engine from the TMS you are using.
And cherry on top, we extended the range of jobs in Plunet, XTRF, Protemos that BeLazy monitors. Previously we only monitored jobs that were connected to BeLazy actions, and now we monitor all jobs in projects created by BeLazy. Basically, you can use the new business management system API of BeLazy to manipulate any job of any project in the business management system that BeLazy created. You probably already know how much easier it is to use the BeLazy APIs compared to the Plunet or XTRF APIs.
