Speech Recognition AI Startup Deepgram Closes $72M Funding Round
AI speech recognition technology startup Deepgram has closed a $72 million Series B funding round after raising $47 million in equity funding led by Madrona. The new money completes the funding round nearly two years after Deepgram raised the first portion of cash in February 2021.
Deepgram provides enterprise voice transcription and analytics in batches and in real time. The platform records and analyzes conversations, customer interactions, internal meetings, and presentations with more than 95% accuracy, according to the company. End-to-end deep learning and tunable models based on industry and environment are why Deepgram claims it can outperform the standard heuristic models and offer more flexibility, adapting to a wide range of companies. The seven-year-old startup boasts that it has transcribed more than a trillion words from over 10,000 years of audio data.
“We’re building the foundational AI models for understanding human speech,” Deepgram CEO Scott Stephenson said. “Understanding speech at scale starts with accurate transcriptions, but it doesn’t stop there. At Deepgram, we view accurate transcription as an increasingly solved problem for many of the more than 100 languages we work with. That’s the groundwork upon which we’re building the future of speech understanding: to give our customers insight into not just what was said, but how it was said, which can result in an actionable understanding of why it was said.”
Deepgram has continually upgraded its services, most recently with the ability to identify topics and languages, as well as translate among those languages for better analytics. That follows the addition of a tool that enables a trained AI to teach speech recognition to other AI. Last year, Deepgram debuted the Deepgram Startup Program, offering $10 million worth of customized speech models and software after previously enticing potential clients with a free version of its enterprise speech recognition platform. The startup has raised $86.4 million total, including a strategic investment from the U.S. intelligence community-founded venture capital firm In-Q-Tel.
“Voice is the dark matter of enterprise data. Trust me on this… I have a Ph.D. in particle physics and worked two miles underground architecting systems to detect dark matter with deep neural networks. And I left particle physics to tackle what feels like a bigger and more tangible problem: transforming dark data into something both humans and computers can understand,” Stephenson wrote in a blog post. “We already offer the fastest, most accurate, and cost-effective speech AI models on the market. Now we’re extending past transcription that tells you what was said, to understanding that tells you why it was said. And, in classic Deepgram fashion, we want to engineer it properly so that we remain the market’s first and best choice for speech AI.”