A person's native language shouldn't limit their ability to learn, grow, and support themselves. It's a form of social inequity that is less visible than gender, race, or class, yet it is no less intrinsic: you cannot choose your native language.
It's also bad for business. When you artificially limit your business to operating only in English, German, Chinese, Japanese, or any other language, you deny your existing global customers an experience that deeply resonates with them, and you lose out on the billions of potential customers who have a different preferred language. For decades, companies have been limited by translation services that took too long, cost too much, and had persistent lapses in quality. That's why we built Lilt.
Making information accessible to everyone in every language.
We're Lilt, the modern language service and technology provider. We build language translation technology and have a community of the world's best translators, which enables us to provide efficient and affordable translation services to the enterprise.
Our Vision
Our Technology
Our mission is to make the world's information accessible to everyone regardless of where they were born or which language they speak. We do that by building the world's most advanced translation technology - leveraging advanced research in human-computer interaction to build intuitive, efficient software applications, doing fundamental cutting-edge research in neural networks, natural language processing, and machine translation to build machine learning models that predict more accurately than ever before the correct translation across 40+ of the world's most widely-spoken languages, and then using that technology to build a high quality, efficient, and cost-effective service model to provide our customers with translation services that get the job done and don't break the bank.
How is all of this possible? By building technology built on recent advances in AI, machine learning, and natural language processing - augmenting human capabilities and enabling 20 people to do the work of 100. After 70 years of work by pioneering computer scientists, machine translation is finally enterprise-ready. And we are best positioned to operationalize and bring that technology to the enterprise.
How is all of this possible? By building technology built on recent advances in AI, machine learning, and natural language processing - augmenting human capabilities and enabling 20 people to do the work of 100. After 70 years of work by pioneering computer scientists, machine translation is finally enterprise-ready. And we are best positioned to operationalize and bring that technology to the enterprise.
Leadership
Spence Green
CEO
- Spence graduated from Stanford with a PhD in computer science under the direction of Chris Manning and Jeff Heer. He has published papers on machine translation, language parsing, and mixed-initiative systems and given talks on translator productivity.
John DeNero
Chief Scientist
- John DeNero is Giancarlo Teaching Fellow in the Electrical Engineering and Computer Science department at UC Berkeley. Before that, he was a research scientist at Google working on Translate. He received a PhD in Computer Science from UC Berkeley in 2010 under the direction of Dan Klein.
Trusted by Leading Companies Around the World
Our Investors
A New Vision for Localization
The localization industry enables companies around the world to interact with global customer bases that speak a wide range of languages, but doesn't take full advantage of technology to augment human ingenuity and automate repetitive tasks that bog down the process. Lilt is changing this with our AI-powered translation platform that helps companies grow faster and improve the customer experience.
The localization platform for modern enterprises
The Lilt Platform vertically integrates the entire localization supply chain. This means faster turnaround times, higher quality, lower costs, and a simpler localization experience for you.
Careers
We’re on a mission to make the world’s knowledge accessible to everyone. Come and join us.
