Why We Invested · R136 Ventures
Product
Deepgram's Nova-2 speech-to-text and Aura-2 text-to-speech models are the fastest in their categories based on independent benchmarks.
Nova-2, their speech-to-text model, and Aura-2, text-to-speech model, are the fastest in their categories by independent benchmarks.
Deepgram's Flux model cleanly handles interruptions when speakers talk over each other in real conversations.
And Flux, their newest model, solves something nobody else has cleanly handled yet: interruptions.
Traction
Over 1,300 organizations and 200,000 developers build on Deepgram's APIs.
Over 1,300 organizations and 200,000 developers build on Deepgram’s APIs.
In February 2026, IBM named Deepgram its first voice AI partner, integrating it into watsonx Orchestrate.
And in February 2026, IBM named Deepgram their first voice AI partner, integrating it directly into watsonx Orchestrate for clients in healthcare, finance, and government.
NASA, Five9, and Twilio use or embed Deepgram as core voice infrastructure.
NASA is now using it for space-to-ground communications. Five9 runs billions of call minutes through the platform. Twilio embedded it as their core voice infrastructure.
Team
Founders Scott Stephenson and Adam Sypniewski started Deepgram in 2015 while working as particle physicists in an underground physics lab.
Founders Scott Stephenson and Adam Sypniewski started Deepgram in 2015 while working two miles underground in a physics lab.
Competition
Deepgram owns its full stack from data labeling and model training to inference and application layers.
Today they own the full stack: data labeling, model training, inference, and the application layer. That vertical integration is where the performance numbers come from.
Deepgram co-designed its models and physical infrastructure, enabling hardware-level optimizations that competitors cannot easily retrofit.
They co-designed their models and physical infrastructure together since the beginning, which gives them hardware-level optimizations you can’t easily retrofit onto a system built differently.
Investment context
Deepgram raised a $130 million funding round at a $1.3 billion valuation.
The $130M round at a $1.3B valuation reflects where Deepgram is today.
What founders can learn
- The traction evidence that carried weight: R136 Ventures wrote that Over 1,300 organizations and 200,000 developers build on Deepgram's APIs.
- How the team was judged: R136 Ventures wrote that Founders Scott Stephenson and Adam Sypniewski started Deepgram in 2015 while working as particle physicists in an underground physics lab.
Source and provenance
Why We Invested published by R136 Ventures on r136ventures.substack.com (first-party source). Read the original
