Neotask connects DeepL and Wrike so localization tasks create themselves, content translates automatically, and your team tracks progress in one place.
New Wrike localization tasks trigger DeepL translations instantly without any manual handoff.
DeepL completion events update Wrike task status so project managers see live translation progress.
Approved Wrike terminology syncs to your DeepL glossary, keeping all translations on-brand.
Translate campaign assets across multiple languages as soon as copy is finalized in Wrike.
Auto-create per-language subtasks in Wrike whenever a new documentation translation task is added.
Push Wrike-approved terminology directly to DeepL glossaries to maintain consistent brand language.
Automatically assign Wrike review tasks once DeepL returns completed translation output for each language.
Query DeepL character usage data and log monthly counts as Wrike task notes for budget visibility.
Tell Neotask which Wrike folder to watch and which target languages to use for all new translation tasks.
When a task is created, Neotask extracts the content and sends it to DeepL with your configured language and glossary settings.
Completed translations return as Wrike subtasks or status updates automatically - no manual steps required.
| Automation | Wrike Action | DeepL Action |
|---|---|---|
| Auto-translate | Create Task (trigger) |
Translate Text |
| Status updates | Update Task |
Get Usage |
| Glossary sync | Get Task (approved) |
Create Glossary |
| Quality review | Create Task (review) |
Translate Text |
Localization projects break down when translation and project management live in separate systems. Teams copy content out of Wrike, paste it into DeepL, then manually update task status when translations return. That process does not scale.
Neotask connects DeepL's neural translation engine directly to Wrike's project management so the two systems work as one coordinated pipeline.
When a new task lands in your Wrike Localization folder, Neotask reads the attached content and sends it to DeepL automatically. Subtasks are created for each target language, and as translations complete, Wrike task statuses update in real time. No polling, no manual updates required.
Maintaining brand consistency across languages is hard when glossaries live separately from approval workflows. With Neotask, terms approved in Wrike flow directly into your DeepL glossary. Every future translation uses the approved terminology from the start.
Project managers no longer need to check DeepL separately. Translation progress, completion rates, and usage data surface directly inside Wrike tasks, giving you a single source of truth for every localization project.
Whether you are localizing a product launch across six markets or maintaining ongoing documentation in three languages, the DeepL and Wrike connection through Neotask scales with your volume. Describe what you need in plain language and Neotask handles the orchestration.
Connect both apps once and every future localization project runs on the same automated pipeline.
Use a dedicated Wrike folder for localization requests so Neotask watches a single source and routes all translation jobs consistently.
Set up your DeepL glossary before running bulk translations so brand terms apply from the first job, not retrofitted later.
Schedule a weekly Neotask prompt to check DeepL usage and log the count to a Wrike task before hitting your monthly character limit.
Yes. Neotask creates a separate DeepL translation job and Wrike subtask for each target language you specify, so every language is tracked independently.
Yes. You can configure Neotask to apply different glossaries based on the Wrike project or folder, keeping domain-specific terminology separate per project.
Neotask logs the failure and updates the Wrike task status to flag the issue, so your team knows to investigate without checking DeepL manually.
Neotask uses standard Wrike API endpoints available on paid plans. Check Wrike current plan details for API access.
Connect DeepL and Wrike in under 2 minutes. Translation projects run on autopilot.
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