Translate at superhuman speeds with our adaptive neural machine translation technology

We train our NMT engine on historical translation data and then refine it over time. With every word that our translators type, our system learns and gets smarter - enabling higher accuracy, greater consistency, and increased speed.

Predictive Translation Suggestions

The NMT engine uses AI and machine learning to analyze existing translation data and make predictive translation suggestions. These suggestions dramatically increase translator accuracy and efficiency by enabling translators to spend their time on new or particularly challenging translation work while the system handles predictable and repetitive parts automatically.

Adapts as Translators Work

As translators interact with the translation suggestions, the system learns and updates future suggestions based on how they reacted to prior ones. By adapting in real-time, translators see substantial efficiency gains from one sentence to the next. Best of all, the system updates those improved suggestions across the rest of the document as well as all future projects for your organization. That means that each translator is working not just to translate content, but also to train our systems to be more accurate for your organization.

Gets Smarter Over Time

We train our NMT engine on as much data as we can find, and we regularly retrain it with new data, languages, and improvements to the predictive models behind the engine. The best part is that each word translated on Lilt provides valuable feedback that is automatically incorporated to train our systems on your organization's content. But don't worry - your data is completely secure and only used to train your organization's engine. Data is never shared from one organization to the next.

Lilt sets a new standard for AI-powered translation

Your business's content and brand are too valuable to entrust solely to an algorithm with no human supervision. That's why the Lilt Adaptive Neural Machine Translation Engine augments, rather than replaces, human translators.

How does it work? First, we never use post-editing, which is the term for pre-translating an entire document and asking translators to go through and fix mistakes. Instead, our engine makes suggestions to translators as they do their work, helping them to translate faster, more consistently, and more accurately with no loss in quality. If a suggestion isn't accurate, the translator ignores it and continues working on that segment. If a suggestion is accurate, the translator accepts it and moves on. Whichever decision the translator makes, the system has an additional data point on the accuracy of its suggestion, and learns in real time for the future. If similar segments appear elsewhere across that same document or any other existing projects or documents, the system updates those translation suggestions as well.

The Lilt Adaptive NMT Engine is the future of language translation, unleashing new levels of human productivity that make it faster, simpler, and more affordable for every organization around the world to translate all of their content in all of the languages spoken by all of their customers, constituents, and stakeholders.

Drives Efficiency

  • Out NMT engine makes translators who use Lilt significantly faster and more efficient at their jobs, enabling them to translate 3-5 times more content than they could with other solutions.

Constantly Learning

  • We train and retrain our NMT engine to ensure it quickly produces accurate translations, and each word translated on our platform helps the system get smarter over time.

Trains on Your Content

  • We make copies of our NMT engine and train them on your company's content, enabling our predictions to quickly get specific to your content, brand, tone, and voice.

Powered by AI

  • Unlike other solutions, Lilt's team of researchers has built the latest advances in AI and machine learning right into Lilt technology, so every one of our customers gets access to cutting-edge AI solutions.

Get started with Lilt today.