model · open source
Speech Recognition & Transcription with Deepgram
Speech Recognition & Transcription built on Deepgram, chosen where it genuinely fits, and swapped where it does not.
- Category
- model
- Vendor
- Open source
- Alternatives we also use
- 6
Why Deepgram for this
Orqent Labs builds transcription systems measured on your recordings, in your vocabulary, with the speaker labels intact.
Deepgram is strongest at low-latency streaming accuracy, which is what voice agents live on. For speech recognition & transcription that matters because the failure modes of this kind of system tend to cluster exactly there.
The honest trade-off: Indian-accent performance needs verification against your own recordings before you commit. We say that up front because a stack chosen for fashion rather than fit becomes someone's migration project two years later. We start from the constraint, not the capability, what the system must never do, who signs off, and what happens when it is wrong.
You own the code, the models where they are open-weight, and the documentation to run it without us.
The honest assessment
- What it is
- Speech recognition tuned for real-time streaming transcription.
- Strongest at
- low-latency streaming accuracy, which is what voice agents live on
- Trade-off
- Indian-accent performance needs verification against your own recordings before you commit
- Category
- model
We are not a reseller for Deepgram and hold no commission on this choice. Where a different option fits your workload better, the recommendation will say so. That is the entire value of asking us.
What is included
- Domain vocabulary tuning for your terminology
- Speaker diarisation, who said what
- Indian language and accent handling, including code-mixing
- Timestamped output linked to the audio
- Word error rate measured on your own recordings
- Integration with your EMR, CRM or case system
Questions
How accurate is it for Indian accents?
Good and improving, but the honest answer depends on audio quality, accent and domain. We benchmark word error rate on your own recordings before you commit.
Can it separate speakers?
Yes, speaker diarisation labels who said what, which is essential for clinical, legal and contact-centre records.
Does the audio leave our environment?
Only if you allow it. We can deploy fully on-premise where confidentiality or regulation requires it.
Alternatives for speech recognition & transcription
Same capability, different stack. Each page states its own trade-off.
What else we build on Deepgram
Building with Deepgram?
Bring us the workload and we will tell you whether this is the right stack for it.
Or email bd@dtrasglobal.com · call +91 74118 77878