Translated ModernMT
Open-source adaptive neural machine translation Pricing: Freemium. See pros, cons, alternatives, and comparisons.
What is Translated ModernMT?
ModernMT is an open-source neural machine translation platform designed for developers and organisations that need accurate, context-aware translation capabilities. Unlike static translation engines, ModernMT adapts to your content over time, learning from corrections and terminology preferences to improve quality for your specific domain. The tool is particularly useful for content teams, software localisation, and businesses handling multilingual material at scale. Because it's open-source, you can self-host it, integrate it into your infrastructure, and customise it without vendor lock-in. ModernMT handles both API-based translation workflows and can be trained on your own data to specialise in industry-specific language.
Key Features
Adaptive learning
the system improves from user corrections and feedback to provide better translations over time
Open-source codebase
full access to source code for self-hosting and customisation
Multi-language support
handles dozens of language pairs across European, Asian, and other language families
Context awareness
maintains consistency across documents and understands broader context for more natural translations
API integration
straightforward REST API for embedding translation into applications and workflows
Custom training
ability to train models on your own parallel texts and terminology databases
Pros & Cons
Advantages
- No vendor lock-in; you own and control the deployment since it's open-source
- Adapts to your specific terminology and writing style, improving quality for repeated content
- Cost-effective for high-volume translation needs with self-hosting options
- Active development community and transparent roadmap
Limitations
- Requires technical expertise to self-host and maintain the infrastructure
- Setup and initial training takes time; not a quick out-of-the-box solution
- Quality depends heavily on training data and configuration; setup requires effort to optimise for your domain
Use Cases
Software localisation for apps and websites across multiple markets
Content translation workflows where consistency and domain terminology matter
High-volume business document translation with cost control requirements
Organisations needing translation without third-party data processing
Translation teams integrating neural output into existing CAT tool workflows