
Sign up to save your podcasts
Or


While Voice AI is all the rage now, it wasn't a hot sector in 2017. After Dylan graduated from YC, VCs rejected him. He couldn't raise a round. They all assumed Google would do it. So he raised what he could from angels and made it work for the next 3 years.
He's now built the world's most accurate Speech AI model. He's grown to 5,000 customers and raised $115M in venture capital. Last quarter, he raised a $50M Series C from Accel.
Just this week, Assembly launched Universal-1, their most powerful speech recognition model to date. Trained on over 12.5 million hours of multilingual audio data, Universal-1 is 22% more accurate than APIs from Azure/AWS/Google and has 30% fewer hallucinations than competing models.
In this episode, we go through how Dylan came up with the idea, how he saw Gen AI coming long before others, and what he did in the early days to grow to $1M in ARR.
Send me a message to let me know what you think!
By Mistral.vc5
8181 ratings
While Voice AI is all the rage now, it wasn't a hot sector in 2017. After Dylan graduated from YC, VCs rejected him. He couldn't raise a round. They all assumed Google would do it. So he raised what he could from angels and made it work for the next 3 years.
He's now built the world's most accurate Speech AI model. He's grown to 5,000 customers and raised $115M in venture capital. Last quarter, he raised a $50M Series C from Accel.
Just this week, Assembly launched Universal-1, their most powerful speech recognition model to date. Trained on over 12.5 million hours of multilingual audio data, Universal-1 is 22% more accurate than APIs from Azure/AWS/Google and has 30% fewer hallucinations than competing models.
In this episode, we go through how Dylan came up with the idea, how he saw Gen AI coming long before others, and what he did in the early days to grow to $1M in ARR.
Send me a message to let me know what you think!

1,290 Listeners

532 Listeners

171 Listeners

702 Listeners

1,100 Listeners

185 Listeners

236 Listeners

188 Listeners

206 Listeners

133 Listeners

515 Listeners

35 Listeners

22 Listeners

37 Listeners

41 Listeners