The Translation Management System for Enterprise Teams
Run enterprise localization on one translation management system. Connect your CMS and repos, automate the busywork, and keep human review where it counts.
What an Enterprise Translation Management System Has to Do
Most platforms stop at moving strings from one place to another. Enterprise localization needs more than that. Structured process, review, payments, compliance, and content sync across every system you run.
Connect Easily to Your Systems
Integrate with your LMS, CMS, or repositories. Pull source content automatically, translate, and send updates back. No copy-paste.
Beyond Just Translation
Crawlers create the jobs. AI proposes the translator. Managers review, approve, and pay in one place.
More Than Generic AI
Our Context Sensitivity applies terminology, tone, and style to every translation, learns from edits, and flags errors before they go live.
Enterprise Localization for Agile Teams
wxrks adapts to how your teams work. Fast, iterative, global. Detect new content, translate it, and publish without disrupting your release cycles.
Automated Updates
Web crawlers monitor your content and trigger jobs automatically, so updates never get lost.
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Translate Your Way
Route routine content through AI for instant delivery or send critical training/legal materials for professional review.
Real-Time Delivery
With CLI, Connectors, and API, push translations from your content systems straight to production.
Run the Whole Operation
Track assignments, review quality, manage payments, and keep stakeholders aligned in one unified platform.
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Built for Developers, Not Just Translators
wxrks Supplies the Framework. The Configuration Is Yours.
Security your review team can sign off. A configuration that survives every model change. Behaviour that holds from one page to a hundred million words.
Built for Security Review
SOC 2 Type 2 held continuously since 2020. AWS in the US or Ireland at your election, with SSO, SCIM, MFA and role-based access to the individual action. Models run stateless, and no customer content trains any model.
Results From 4.3M Segments
39% more effective than traditional MT post-editing, measured as edit rate across 4.3M segments and 20 language pairs. Harley-Davidson cut turnaround 70% across 42 languages. wxrks study, 22 June to 23 December 2023, English source.
Automation-First Workflows
Trigger jobs via API, CLI, or connectors. No manual exports, no copy-paste.
Context Sensitivity
AI applies your terminology and voice across content, so your learning and training modules feel authentic.
Switch Models Without Re-implementation
Model Management is a table of rows, so changing the model behind an operation is an edit to one row. OpenAI, Anthropic, Gemini, Vertex AI, Groq, or any endpoint you point it at. Nothing is fine-tuned on your content, so nothing is lost when you switch.
Quality Gated on Your Rules
Every segment is scored with a named finding, a severity and an explanation. You set the thresholds per content tier. Output above threshold passes and locks, deterministic fixes apply automatically, and the rest routes to a named person.
Brands and Regions Held Apart
Account, Organization and Organizational Unit keep brands, regions, business units and suppliers separate under one roof. Unlimited users and units, each holding its own memories, glossaries, workflows, models and audit trail.
One Subscription, Sized by Volume
Priced on processed volume. Your team, your requesters and your suppliers are not licensed per seat. In enterprise plans, implementation, onboarding, training and asset import sit inside the subscription, so there is no first-year spike.
A 30-Day Proof of Concept
Full platform, your real content, your target locales, and up to three of your existing suppliers working inside the instance as they would in production. Four measures agreed at the start, including edit distance against your current baseline.
Integrations
Connect your content to the tools your team uses every day - plus create your own micro-apps using no code integration
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