Ir al contenido principal
usedby
Herramientas, empresas

Cómo usa SigmaMind AI Deepgram

~300ms

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

Tal como se publicó en deepgram.com. Verificado por usedby el 9 oct 2026.

Qué pasó

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.

Resumen escrito por usedby a partir de la página de origen, en inglés. Las cifras son de Deepgram y de SigmaMind AI, no nuestras.

  • 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.

De la página. 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. Fuente

Lo que dice la historia, y lo que verificamos

Lo que comparamos con la página.

  • La cifra: ~300msVerificadoImpresa palabra por palabra en la página, cerca del nombre de SigmaMind AI.
  • El pasaje citado arribaVerificadoCopiado palabra por palabra de la página, cerca del nombre de SigmaMind AI.
  • SigmaMind AI usa DeepgramVerificadoLínea de nivel Confirmado.
  • El resultado en síNo verificadoLo citamos; no lo medimos.

Misma empresa, misma herramienta o mismo sector.

2.5x“train models 2.5x faster than previously experienced on NVIDIA H200s”Mistral AI usa CoreWeave. Mismo sector: Inteligencia Artificial75%“saving 75% in cloud costs”NovelAI usa CoreWeave. Mismo sector: Inteligencia Artificial90%“90% cost reduction”OpenAI usa CoreWeave. Mismo sector: Inteligencia Artificial