Technology

The infrastructure
behind a warm call

A proprietary voice AI pipeline and a real-time database interlock at sub-500ms end-to-end latency — so all a senior ever feels is one seamless, natural conversation.

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Sub-500ms latencyCo-located model architecture99.9% uptime SLA

An elder calm on a call — the infrastructure behind a warm conversation

Pipeline specifications

The latency and availability our vertically integrated voice AI stack reaches in production. Language and voice counts reflect the underlying voice provider integrated into our pipeline.

Sub-500ms end-to-end latency
From voice capture to spoken reply, conversation, analysis, and alerts all run at once while holding consistent sub-500ms end-to-end latency — so a senior only ever experiences an uninterrupted talk.
90+ STT languages (provider)
The speech recognition provider integrated into our pipeline handles 90+ languages at ~80ms latency. Predictive transcription generates text before speech even finishes.
5,000+ TTS voices (provider)
The voice synthesis provider integrated into our pipeline offers 5,000+ multilingual voices synthesized at ~75ms inference latency. Streaming response delivers the first audio byte immediately.
99.9% uptime SLA
Infrastructure operated to a 99.9% uptime SLA stands behind every daily check-in call. Real-time monitoring and automatic fallback keep it reliable.

From voice to reply, in three steps

A co-located model architecture — speech recognition, synthesis, turn-taking, and voice activity models on the same infrastructure — binds this flow into a single beat.

1
Listen — capture & recognize
Encrypted real-time audio is captured, a proprietary VAD detects speech boundaries, and ~80ms STT transcribes mid-utterance.
2
Understand — context & reasoning
Conversation history, mood, and medication are injected from the real-time DB in <20ms, and a streaming LLM yields its first token in ~150ms.
3
Respond — synthesize & stream
~75ms TTS synthesizes the voice and streams it in real time, so the whole loop closes consistently within sub-500ms.

Co-located Model Architecture

Voice AI Pipeline

Speech recognition, synthesis, turn-taking, and voice activity models run on co-located infrastructure. Streaming LLM integration delivers consistent sub-500ms end-to-end latency.

Voice Capture

<100ms

Encrypted Real-time Transport

Captures real-time audio from the browser microphone with end-to-end encryption. P2P streaming with sub-100ms transport latency.

VAD / Turn Detection

Real-time

Voice Activity Detection

Proprietary VAD model detects speech start/end boundaries. Co-optimized with turn-taking for natural conversation timing with elderly users.

Speech-to-Text

~80ms

Real-time Recognition

Real-time speech recognition engine with ~80ms latency across 90+ languages. Predictive transcription generates text before speech completes.

Context Injection

<20ms

Memory + Mood + Medicine

Fetches conversation history, mood state, and medication info from real-time DB instantly. Generates personalized, contextual responses.

AI Reasoning

~150ms

Large Language Model

Streaming-connected LLM generates first token in ~150ms. Handles emotion classification, crisis detection, and response generation in parallel.

Text-to-Speech

~75ms

High-quality Synthesis

Multilingual voice synthesis at ~75ms inference latency. Streaming response delivers first audio byte immediately.

Real-time Audio Output

<500ms E2E

Real-time Streaming

Synthesized voice streams to the user in real-time. High-quality audio delivered reliably at low bandwidth.

Parallel Processing

Async Processing Channels

Parallel analysis systems running alongside the main voice pipeline.

Emotion Analysis Engine

Voice transcript → Emotion classification → Mood journal storage

Psychology-based model analyzes conversation tone and topics in real-time. Results are automatically logged as mood journal entries.

Loneliness Detection System

Conversation pattern analysis → Loneliness scoring → Family alert trigger

Applies validated clinical scales to conversation data. When thresholds are exceeded, real-time alerts are sent to the family dashboard.

Conversation Persistence Layer

Conversation transcription → Summary generation → Real-time DB storage

AI auto-generates conversation summaries. Real-time sync reflects changes instantly on the dashboard.

Medicine OCR Pipeline

Camera capture → Vision AI → Drug info extraction → Voice guidance

Vision AI model performs OCR analysis on prescriptions. Extracted medication info is injected into voice conversation context.

Benchmarks

Latency & availability

The latency and availability our vertically integrated voice AI stack reaches in production. Language and voice counts reflect coverage from the underlying voice provider integrated into our pipeline.

STT Latency~0ms

TTS Latency~0ms

End-to-End Latency<0ms

STT Languages (provider)0+

TTS Voices (provider)0+

Uptime SLA0%

Vertically integrated voice AI stack architecture

WelVoice Voice AI Platform

STT, TTS, VAD, and turn-taking models run on co-located infrastructure. WelVoice connects its optimized LLM and RAG context on top of this platform.

Transport Layer

Real-time Transport

End-to-end encryption, high-quality audio codec, NAT traversal

Fallback Transport

Bidirectional streaming, inactivity auto-close

SDK

Web and Mobile (iOS/Android) multi-platform support

Voice Processing Layer

Real-time STT

~80ms latency, 90+ languages, predictive transcription, auto VAD

High-quality TTS

~75ms inference, multilingual voices, Expressive Mode

Turn-Taking Model

Proprietary conversation timing, optimized for elderly users, natural interruption handling

Intelligence Layer

LLM Server

Streaming response, real-time function calling support

Large Language Model

Fast first-token generation, strong instruction following, Vision support

RAG Knowledge Base

Conversation memory, mood state, medication info — real-time injection

Application Layer

Emotion Analysis

Clinically validated loneliness scale + emotion classification

Family Dashboard

Real-time mood tracking, loneliness alerts, auto-sent conversation summaries

Medicine Guide

Vision AI OCR → drug info extraction → voice guidance integration

Full Stack

Full Technology Stack

Expand each of the six domains to see the core technologies behind the service.

Integrated Voice Platform

STT + TTS + VAD all-in-one agent

Real-time STT

~80ms latency, 90+ languages, predictive transcription

High-quality TTS

~75ms inference, multilingual voices

Expressive Voice

Natural intonation and emotion in speech

Real-time Transport

End-to-end encrypted, high-quality audio streaming

VAD + Turn-Taking

Proprietary speech/turn detection models

Experience it yourself

Try sub-500ms AI voice conversations on the free plan.

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How is this different?

Unlike a generic voice bot stitched from separate APIs or a legacy IVR, WelVoice unifies the voice stack and the data on one infrastructure.

How is this different?
	WelVoice	Generic voice bot	Legacy IVR
Sub-500ms end-to-end latency	Supported	Not supported	Not supported
Co-located model architecture	Supported	Not supported	Not supported
Real-time DB context injection	Supported	Not supported	Not supported
Proprietary VAD & turn-taking	Supported	Not supported	Not supported
90+ language real-time STT	Supported	Supported	Not supported
99.9% uptime SLA	Supported	Not supported	Not supported

We carry the infrastructure, so the call stays warm

The hard technology stays invisible. Try sub-500ms AI voice conversation yourself on the free plan.

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The infrastructurebehind a warm call

Pipeline specifications

Sub-500ms end-to-end latency

90+ STT languages (provider)

5,000+ TTS voices (provider)

99.9% uptime SLA

From voice to reply, in three steps

Listen — capture & recognize

Understand — context & reasoning

Respond — synthesize & stream

Voice AI Pipeline

Voice Capture

VAD / Turn Detection

Speech-to-Text

Context Injection

AI Reasoning

Text-to-Speech

Real-time Audio Output

Async Processing Channels

Latency & availability

WelVoice Voice AI Platform

Transport Layer

Voice Processing Layer

Intelligence Layer

Application Layer

Full Technology Stack

Experience it yourself

How is this different?

We carry the infrastructure, so the call stays warm

Voice AI Pipeline

Voice Capture

VAD / Turn Detection

Speech-to-Text

Context Injection

AI Reasoning

Text-to-Speech

Real-time Audio Output

Async Processing Channels

Latency & availability

WelVoice Voice AI Platform

Transport Layer

Voice Processing Layer

Intelligence Layer

Application Layer

Full Technology Stack

Experience it yourself

The infrastructure
behind a warm call