How DeepL Built a Translation Powerhouse with AI with CEO Jarek Kutylowski
In this episode of Gradient Dissent, Lukas Biewald talks with Jarek Kutylowski, CEO and founder of DeepL, an AI-powered translation company. Jarek shares DeepL’s journey from launching neural machine translation in 2017 to building custom data centers and how small teams can not only take on big players like Google Translate but win.
They dive into what makes translation so difficult for AI, why high-quality translations still require human context, and how DeepL tailors models for enterprise use cases. They also discuss the evolution of speech translation, compute infrastructure, training on curated multilingual datasets, hallucinations in models, and why DeepL avoids fine-tuning for each individual customer. It’s a fascinating behind-the-scenes look at one of the most advanced real-world applications of deep learning.
Timestamps:
[00:00:00] Introducing Jarek and DeepL’s mission
[00:01:46] Competing with Google Translate & LLMs
[00:04:14] Pretraining vs. proprietary model strategy
[00:06:47] Building GPU data centers in 2017
[00:08:09] The value of curated bilingual and monolingual data
[00:09:30] How DeepL measures translation quality
[00:12:27] Personalization and enterprise-specific tuning
[00:14:04] Why translation demand is growing
[00:16:16] ROI of incremental quality gains
[00:18:20] The role of human translators in the future
[00:22:48] Hallucinations in translation models
[00:24:05] DeepL’s work on speech translation
[00:28:22] The broader impact of global communication
[00:30:32] Handling smaller languages and language pairs
[00:32:25] Multi-language model consolidation
[00:35:28] Engineering infrastructure for large-scale inference
[00:39:23] Adapting to evolving LLM landscape & enterprise needs
#263 Jarek Kutylowski: How DeepL Is Using AI to Break Language Barriers
What if language was no longer a barrier to global business?
In this episode, DeepL CEO Jarek Kutylowski joins Craig Smith to unpack how AI-powered translation is reshaping the way companies communicate across borders.
From real-time speech tools to enterprise-grade language workflows, Jarek shares DeepL's journey, the tech behind their LLMs, and why accuracy, nuance, and localization matter more than ever. If you're building for a global audience, this conversation is a must-listen.
About Jarek: Dr. Jaroslaw "Jarek" Kutylowski is the founder and CEO of DeepL, the Cologne-based Language AI company transforming global communication and breaking down language barriers for businesses worldwide.
Born in Poland and having spent a large part of his life in Germany, Jarek brings an international perspective and a lifelong passion for technology - a developer at heart, he began coding at just 10 years old, building tools he found useful in daily life. He holds a PhD in Computer Science with a focus on mathematics and has held roles at several tech companies prior to founding DeepL.
Under his leadership, DeepL has grown rapidly, expanding its Language AI platform to offer highly accurate and nuanced human-like translation in both written and spoken formats, as well as a contextual AI writing assistant. Today, over 200,000 businesses and governments - and millions of individuals across 228 global markets - trust DeepL for secure, seamless and effective communication.
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(00:00) Introduction to DeepL and Jarek's Vision
(05:09) DeepL's Technology Evolution
(08:17) The DeepL Platform: Products, APIs, and Enterprise Use Cases
(12:39) Why DeepL Outperforms Consumer Tools
(15:14) How Enterprises Use DeepL
(17:05) DeepL's Translation Accuracy
(21:20) Breaking Language Barriers in Global Workforces
(23:46) A Future Without Language Barriers
(27:19) Expanding Language Coverage and Industry Verticals
(31:44) DeepL's Role in High-Compliance Sectors
(34:04) Tackling Latency and Real-Time Use Cases
(38:38) DeepL as the Translation Engine Behind Other Products
(42:40) Partnering with News Media and Government
(45:40) Pricing Models and Accessibility
(46:24) The Human Impact of AI-Powered Language Tools
(49:22) What's Next for DeepL and Global Communication