The architecture behind ~700ms voice AI in every Indian language.
A 32-page technical deep-dive into GRX10’s audio-native voice pipeline — how we skip cascaded STT→LLM→TTS, tune VAD for 8 kHz Indian telephony, benchmark Hindi-English code-switching, and hold a ₹7.99/min platform rate.
~32 pages · For CTOs, Heads of CX & BFSI risk teams
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Download the PDFThe parts nobody publishes.
Cascaded pipelines hit a wall.
Why STT→LLM→TTS bottoms out at a 1,200–2,000 ms floor — and how an audio-native model breaks it.
VAD for 8 kHz telephony.
Speech-detection thresholds, barge-in and echo handling tuned for real Indian phone lines, not studio audio.
Hindi-English code-switching.
A 1,400-utterance benchmark with accuracy and latency results for mid-sentence language switches.
The telephony bridge.
The slin16-vs-μ-law detection that quietly breaks every container build — and the fix.
The cost model.
What a ₹7.99/min platform rate actually breaks down into: model inference, telco, storage, infra.
Compliance-ready.
RBI Fair Practices alignment, DPDP data-residency notes, audit logging and recording-retention SOPs.
“The latency math alone made the architecture decision obvious. We stopped evaluating cascaded vendors after page 8.”
Read the whitepaper, then hear it live.
The 32-page technical whitepaper
Architecture, benchmarks, telephony and the cost model — the full engineering picture in one document.
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Describe your use case, take a call in minutes, and hear the ~700ms latency in your own language.
Start freeAlso see Voice AI, the latency benchmark and Voice AI for India.