Building foundational AI for speech transcription and understanding.
Deepgram is a foundational AI company on a mission to understand human language. We give any developer access to the most advanced speech AI transcription and understanding with just an API call. Our models deliver the fastest, most accurate transcription alongside contextual features like summarization, sentiment analysis, and topic detection. Beyond that, developers can: 🔊 Process live-streaming or pre-recorded audio 🌎 Transcribe in dozens of languages ⚙️ Train custom models for unique use cases 🔑 Access deep NLU with a unified API 💻 Build in any programming language with our SDKs ✅ Deploy on-prem or on DG’s managed cloud 📈 Get scalable GPU infra for training and inference Deepgram is a proud NVIDIA partner and Y Combinator company, and we recently completed a $72M Series B to define the future of AI Speech Understanding, making us the most-funded speech AI company at its stage.
Jobs at Deepgram
Active Founders
Scott Stephenson, Founder/CEO
Technical CEO, DL person, particle physicist.
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Hear from the founders
How did your company get started? (i.e., How did the founders meet? How did you come up with the idea? How did you decide to be a founder?)
Deepgram was founded in 2015 by Scott Stephenson, Adam Sypniewski, and Noah Shutty—all former physicists at the University of Michigan. Fascinated with the idea of life-streaming, Scott and Noah built wearable recording devices, on which they recorded hundreds of hours of their voice notes, conversations, and chance interactions as they went about their days. This presented a problem: how to sift through all that audio data. Translating his research work on “listening” for signatures of dark matter interactions using end-to-end deep learning, Scott built a deep learning model capable of searching through voice data. The three founders left academia to move to the Bay Area and start Deepgram.
What is the core problem you are solving? Why is this a big problem? What made you decide to work on it?
Deepgram makes voice data useful to people and usable by computers using end-to-end deep learning models. Speech is the dark matter of enterprise data and is a largely untapped source of insights and business value. We get to help our customers discover that value and advance the state of the art in deep learning and language models.