XTM Cloud 13.3 is packed with new features. We’ve already announced the launch of our closed-beta program for AI-powered quality checks and our new project management features, but there’s more!  Today, we’ll focus on the features that are coming straight from XTM Labs.

XTM Labs gives users early access to some of the feature ideas they submit via the XTM Wish List. For 13.3, our XTM Labs users have been busy providing feedback on a number of features, which are now accessible to all users! Here are the latest Labs features.

Using NLP, XTM Cloud identifies non-translatable segments much more accurately, ensuring that no costs are incurred for segments that should not be translated, such as codes or formulas, for instance. Plus, it ensures that linguists do not waste unnecessary time copying and pasting values that do not require any rework.

A new ‘Accept’ option can be added to workflows, which prompts linguists and LSPs to accept a task or project before they can start working on it—or reject it if they don’t have enough bandwidth for it. This allows for even more clarity and control over your processes. 

For instance, a project manager (PM) creates a translation project and assigns a linguist to the first step, ‘Translate’, and a reviewer to the second step, ‘Review’ with the ‘Accept’ step feature enabled. Once the project is created, the linguist gets notified and opens the project. Before they can start editing, they have to accept it first. Once they accept, the PM gets an email notification letting them know that the ‘Translate’ step has been accepted, and they can see that the work is in progress in their workflow view.

Once the linguist is done, the project is passed on to the reviewer. The reviewer gets notified, but doesn’t have the capacity to do this task. They reject the project. The PM gets notified immediately and can react right away by assigning someone else to that step. This ensures there is no miscommunication, which can lead to potential delays. This new step allows you to streamline communication with your linguists and LSP,  providing better and faster information as you complete your projects on time.

Inline tags are used to signal text formatting, such as words in bold, or elements of code, like hyperlinks. For consistency, everything that’s included in the source file needs to be included in the target file as well, which is why these tags are required. The challenge comes from the fact that the placement of these tags within the source will likely differ from the target. As a result, when linguists are translating content, they also need to be aware of where to place these inline tags. Since these must  be included, linguists have to stop focusing on translation to think about where these tags should appear, which is a tedious and time-consuming task that takes them out of their flow.

In XTM Cloud, inline tags can be placed automatically, with an accuracy of 92%. This saves linguists precious time, as they don’t have to worry about manually placing them and can instead focus on localization. Now, they can also be automatically inserted into machine-translated segments through our XTM Inter Language Vector Space algorithm. As a result, files translated via MT can be prepared even more swiftly, eliminating the need for linguists to manually reposition inline tags. Those who use machine translation will be able to choose when to use auto placement of inline tags:

• “Off” means the inline tags will never be placed automatically.
• “Only fixing” means auto-inlines will work only on segments that have broken inline placement.
• “Always” means inlines won’t be sent to the MT engine, and after receiving translation from MT, auto-inlines will work on all segments.

As an example, let’s consider the translation of the phrase “Select the {1}latest updates{1} tab to find out more” into French using MT. If the feature is set as ‘Always’, the inline tags will be correctly placed, even when dealing with variations in word order and length. The translated version, “Sélectionnez l’onglet {1}Dernières mises à jour{1} pour en savoir plus,” maintains the correct identification of the hyperlinked words, guaranteeing their proper functionality.

After the first iteration of project groups with XTM Labs 13.0, we are now going into stage two for all our customers! This project group functionality enabled project managers to manage projects and assignments in bulk by saving advance searches as groups and making them available at the click of a button. Now, the project group view includes additional columns and options, providing users with much more information and control.

This feature significantly benefits project managers, enabling them to effortlessly locate essential information and efficiently manage projects. To illustrate this, consider a scenario where a project manager responsible for the marketing department frequently needs to access project details in French. Specifically, they regularly check the status of marketing projects and require a streamlined method to access this information promptly. By performing a search for marketing projects in French and saving it as a project group, they can conveniently navigate to the Project Group tab with just a single click. Consequently, they no longer need to re-run the search each time they access XTM Cloud, saving them valuable time and effort in project management.

From there, they can easily access project information, and apply batch actions if needed, significantly reducing the time spent on managing similar projects.

Our concordance search  feature in XTM Workbench and XTM Concordance has been enhanced to support Boolean search. This will enable linguists to find the right information faster using more powerful and precise search criteria.

For instance, you could perform an advanced search for translations of ‘Raise a query’ specifically excluding any Marketing projects, that would look like this: source IS “Raise a query” OR source CONTAINS “query” AND projectName NOT_IN (“Marketing”). That way, you can refine your search and find exactly what you’re looking for.

For those of you who have particularly large databases with thousands of projects and even more segments to search through, this will make the task of finding the right context and therefore the translation a lot easier.

Linguistic Quality Assessment (LQA) gives you data on how your linguists are performing. Are they meeting deadlines? Are they providing high-quality translations? This data is key to ensuring you work with the best vendors, and it is already easily accessible within XTM Cloud.

For those of you who use our REST API to manage projects, you are now also able to access this information. Data will be collected through your REST API endpoints, allowing project managers to get statistics on all their projects. This ensures that LQA reports can be accessed and extracted for linguists using XTM Cloud and the REST API, providing a global view of your localization teams’ performance, from a single place.

This also enables you to create comprehensive reports at the click of a button, saving you a lot of time-consuming manual work when creating reports for a number of different languages. This data can then be analyzed along with other data through your preferred Business Intelligence tool. Previously, this would have been challenging when certain tasks were completed outside of XTM Cloud using API. With XTM Cloud 13.3, you can now gather, track, and manipulate all relevant data points relating to their localization efforts. This enhanced visibility allows you to make informed evaluations and streamline your localization processes more effectively.

In our last article of this series that covers all the new features in 13.3, we’ll tell you more about flexibility, terminology, and machine translation.