Co-founder at a tech services company with 1-10 employees
Real User
2025-10-13T23:08:23Z
Oct 13, 2025
I use Deepgram for a company that requested me to implement an AI voice agent for a security application that warns other neighbors of near alerts of some incidents that may occur in their neighborhoods. I implemented this in January 2025, using Deepgram as a transcriber for those conversations for three months, and I love the technology because it transcribes very well all the conversations, making the implementation relatively easy. My main use case for Deepgram is just for transcribing, and since this company is a Spanish company, I got deep into some use cases and settings configurations to adjust those transcriptions that include both Spanish and English words. Deepgram handled one of these bilingual conversations by adjusting some settings, such as the name of the company being in English while the conversation was in Spanish, so we needed to configure it to transcribe accurately because Vapi utilized that transcription for the LLM agent to speech those words through an agent voice. Regarding my experience with those bilingual transcriptions, I think the transcriptions were quite precise, and while there is room for improvement, the results met expectations, making Deepgram a good fit for that work.
I use Deepgram for audio transcriptions and speech recognition. I am working on a feedback survey app where users provide verbal feedback that Deepgram transcribes into text. We receive the results and implement features like punctuation and Smart Format.
Deepgram stands out for its speed in transcribing videos and speech to text, leveraging cutting-edge models like Whisper and Nova for exceptional performance and accuracy. Its latency is remarkably low, enabling swift transcription that users find superior to alternatives.Deepgram provides an efficient solution for transforming video and audio content into text, benefiting from its advanced ability to recognize industry-specific terminology. Users experience faster results compared to IBM...
I use Deepgram for a company that requested me to implement an AI voice agent for a security application that warns other neighbors of near alerts of some incidents that may occur in their neighborhoods. I implemented this in January 2025, using Deepgram as a transcriber for those conversations for three months, and I love the technology because it transcribes very well all the conversations, making the implementation relatively easy. My main use case for Deepgram is just for transcribing, and since this company is a Spanish company, I got deep into some use cases and settings configurations to adjust those transcriptions that include both Spanish and English words. Deepgram handled one of these bilingual conversations by adjusting some settings, such as the name of the company being in English while the conversation was in Spanish, so we needed to configure it to transcribe accurately because Vapi utilized that transcription for the LLM agent to speech those words through an agent voice. Regarding my experience with those bilingual transcriptions, I think the transcriptions were quite precise, and while there is room for improvement, the results met expectations, making Deepgram a good fit for that work.
I use Deepgram for audio transcriptions and speech recognition. I am working on a feedback survey app where users provide verbal feedback that Deepgram transcribes into text. We receive the results and implement features like punctuation and Smart Format.
We use the solution for TTS (Text-to-Speech) and STT (Speech-to-Text) purposes.
We primarily use the solution for transcribing speech to text. We use it to record phone calls and meetings and then transcribe them.
I run Deepgram on my local system to transcribe videos.