# How SigmaMind AI uses Deepgram

**~300ms**: “~300ms reduction in end-to-end agent response time after integrating Deepgram’s streaming STT”

As published on [deepgram.com](https://deepgram.com/customers/sigmamind-ai). Captured by usedby on 2026-10-09.

- Company: [SigmaMind AI](https://www.usedby.ai/companies/sigmamind-ai.md)
- Tool: [Deepgram](https://www.usedby.ai/tools/deepgram.md)

## What the story says

SigmaMind AI uses Deepgram's Nova-3 and Flux models as the default real-time speech-to-text engine in its no-code platform for building voice AI agents. Transcripts, including interim results, feed its orchestration engine so agents can start acting before a speaker finishes.

Summary written by usedby from the source page, in English. The figures are those of Deepgram and SigmaMind AI, not ours.

> By integrating Deepgram’s Nova-3, and Flux speech-to-text models as the default real-time transcription engine, SigmaMind reduced end-to-end agent response latency by roughly 300 milliseconds and enabled a new class of voice workflows where agents act on speech before a sentence is even finished.

- **50%**: “50% increase in outbound call conversion for a call center customer that migrated to SigmaMind, going live in just two weeks”
- **1 million+**: “1 million+ calls per month processed through SigmaMind’s platform, with 200+ hours of speech transcribed daily”
- **150**: “150 peak concurrent voice sessions handled per customer deployment without degradation”
- **Sub-1-second**: “Sub-1-second voice-to-voice latency including telephony overhead, enabling natural conversational pacing”

> When we began acting on interim transcripts and combined that with word timestamps, the agent could trigger API calls and follow-ups mid-utterance,” said Pratik Mundra, co-founder of SigmaMind AI. “That shift unlocked much richer, multi-step voice workflows.
>
> Pratik Mundra, co-founder of SigmaMind AI

Source: [deepgram.com](https://deepgram.com/customers/sigmamind-ai), captured 2026-10-09.

## What usedby checked

We compared the story with its live page on 2026-10-09.

- Checked: the figure ~300ms is printed word for word on the page, near the name of SigmaMind AI.
- Checked: the passage quoted above is copied word for word from the page, near the name of SigmaMind AI.
- Checked: SigmaMind AI uses Deepgram. Confirmed line. Latest check across sources: 2026-10-09.
- Not checked: the result itself. We quote it; we did not measure it.

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Source: https://www.usedby.ai/case-studies/sigmamind-ai-deepgram · How we check: https://www.usedby.ai/methodology