AI-based language translation startup DeepL has spent a good chunk of the millions it has raised on hiring, growing its headcount nearly seven-fold in three years as it tries to maintain its edge over deep-pocketed big tech companies.
Expansion and Innovation
The German startup, which recently raised $300 million on a $2 billion valuation, pioneered the AI technology that will help create a world where language barriers hardly matter. On Wednesday, it announced it’s adding 165 new markets for its translation product for businesses in Asia, Africa, Europe, and the Americas.
Competition from Big Tech
But Apple, Amazon, Google, Microsoft, and Meta are all investing in similar technology. They also have an edge in the consumer market. Phones, earbuds, smart speakers, and other products could be the translation interfaces of the future. As hardware and software improves, real-time translation on those devices could soon become a reality.
DeepL’s Strategy
In an interview with Semafor, DeepL co-founder and CEO Jarek Kutylowski said the only answer is to continually get better, faster.
“It’s all about the pace of innovation,” he said. “We’ve been able to convince our customers of our superior quality.”
Kutylowski said the company devotes up to 100 employees to research, tasked with improving and expanding DeepL’s machine translation capabilities, out of around 1,000 total staffers. “It’s a pretty significant part of a company of our size, maturity and revenue,” he said. Its clients include Nikkei, Deutsche Bahn, and Zendesk.
Enterprise Focus
Katharina Wilhelm, a partner at Index Ventures, which led the recent investment round in DeepL, said consumers love DeepL, but the real value is in enterprise. “You probably won’t be willing to pay $50 a month for your private translations,” she said. “But you might be as a journalist or as a business because accuracy and security are so important to you.”
Kutylowski declined to say whether big tech companies have approached DeepL about partnering or acquiring its technology. He also said DeepL is not planning on building its own hardware device to compete with those firms.
“Obviously if there’s an insanely attractive acquisition offer, you’ll have to look at it,” Wilhelm said. “We would not have invested if it were a near-term acquisition by a big platform. This will be a generational company.”
Challenges Ahead
Kutylowski said the best translation models are still too large to run on-device and must access the cloud, meaning hardware devices that conduct real-time translation are still a ways off.
Rather than focus on the consumer market, DeepL has turned to enterprise, selling seven-figure accounts to large corporations like international law firms, or to those that need diplomatic translations.
For example, one customer, a Japanese carmaker that he declined to name, has its research and development in Japan and its commercial operations in the US. “Communication between those parts of the business are extremely important, and so much can go wrong if it doesn’t work out,” he said.
New Ventures
The company is also moving into the literature space, with its products available to publishers. “We have a shelf of books in our office that have been translated using DeepL,” he said. “There’s even a machine learning neural network book.”
For more details, visit the full article at Semafor.
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