Free technical whitepaperPatent-pending architecture

The Architecture Behind~700ms Voice AI in 22 Indian Languages

A 32-page deep dive into GRX10's patent-pending audio-native voice pipeline — how we skip cascaded STT→LLM→TTS, the Silero VAD tuning for 8 kHz Indian telephony, the Hindi-English code-switching test bench, and the cost model that gets us to ₹7.99/min platform rate.

What's inside

  • ›Why cascaded STT/LLM/TTS hits a 1,200-2,000 ms floor — and how audio-native models break the wall
  • ›Silero VAD tuning for 8 kHz Indian telephony — speech-detection thresholds, barge-in, echo handling
  • ›Hindi-English code-switching benchmark — 1,400 utterance test set, accuracy + latency results
  • ›Asterisk + AudioSocket bridge — the slin16 vs μ-law detection that breaks every Docker build
  • ›Cost model — what ₹7.99/min platform rate actually breaks down into (Gemini, telco, S3, infra)
  • ›RBI Fair Practices alignment — guardrails, audit logging, recording retention
  • ›DPDP-readiness — data residency, DPA template, Grievance Officer SOP
~32 pages•Architecture + benchmarks•For CTOs, Heads of CX, BFSI risk teams

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Sample data inside

~700ms
p95 first-word latency
Production, last 30 days
22
Indian languages
Hindi + 21 regional
1,400
utterance test set
Hindi-English code-switch
8 kHz
native telephony
No upsample, no quality loss

“The latency math alone made the architecture decision obvious. We stopped evaluating cascaded vendors after page 8.”

— CTO · Tier-1 NBFC (early reader)