model · open source
Voice AI Agents with Deepgram
Voice AI Agents built on Deepgram, chosen where it genuinely fits, and swapped where it does not.
- Category
- model
- Vendor
- Open source
- Alternatives we also use
- 8
Why Deepgram for this
We replace IVR trees with agents that just ask what you need. The measurable outcome is usually containment and average handling time. Both of which we baseline before building.
Deepgram is strongest at low-latency streaming accuracy, which is what voice agents live on. For voice ai agents 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. Integration comes before intelligence. A model that cannot reach your systems of record is a demo with good manners.
Six weeks to something running in production, not six quarters to a strategy document.
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
- Telephony integration with your existing numbers
- Indian-language speech recognition and synthesis
- Sub-second turn latency with barge-in support
- Live transfer to a human with context
- Call recording, transcription and QA scoring
- Compliance with calling and consent regulations
Questions
Which Indian languages are supported?
Hindi, Tamil, Telugu, Kannada, Malayalam, Marathi, Bengali, Gujarati and Punjabi among others, including code-mixed English. We test on recordings of your real callers, not studio audio.
How fast does it respond?
We target sub-second turn latency end to end, with barge-in so callers can interrupt naturally. Anything slower and callers assume the call has dropped.
Can it transfer to a human?
Yes, warm transfer with the transcript and caller context handed over, so the agent does not ask the customer to repeat themselves.
Alternatives for voice ai agents
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