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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. Checked by usedby on Oct 9, 2026.

What happened

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.

  • 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”

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.

From the page. deepgram.com

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

What the story claims, and what we checked

What we compared with the page.

  • The figure: ~300msCheckedPrinted word for word on the page, near the name of SigmaMind AI.
  • The passage quoted aboveCheckedCopied word for word from the page, near the name of SigmaMind AI.
  • SigmaMind AI uses DeepgramCheckedConfirmed line.
  • The result itselfNot checkedWe quote it; we did not measure it.

Same company, same tool or same industry.

30%“the time spent per audit has been reduced by 30%”Abby Connect uses Deepgram. Another customer of Deepgram58%“measured a shocking 58% reduction in transcription latency”BIGVU uses Deepgram. Another customer of Deepgram10%“produced a 10% increase in recovery rates and smarter workforce deployment”Creditas uses Deepgram. Another customer of Deepgram