Realism depends on the quality of the reference video and the rendering model used. With a well-lit, high-resolution reference and state-of-the-art models like MuseTalk or SadTalker, the output is photorealistic with natural-looking blinks, subtle head movements, and expression variance. For production deployments, CentEdge validates the output against naturalness benchmarks and iterates with you before go-live.

Reference video capture takes 10-15 minutes. Training and validation typically takes 24-48 hours. Post-training adjustments and voice clone validation add another 24 hours. Total avatar creation timeline from reference video to approved production avatar is typically 3-5 business days.

Real-time avatar rendering requires at minimum an NVIDIA A100 or H100 GPU for sub-200ms latency at production quality. For lower-quality or cached-response deployments, an RTX 4090 is sufficient. CentEdge sizes the GPU recommendation based on your expected concurrent session count and target quality level. The full inference stack is containerised and runs on standard Ubuntu with CUDA drivers.

Yes. The voice cloning model (XTTS v2) generates the cloned voice in 20+ languages from a single 30-second sample, preserving the speaker's tone, pace, and prosody across languages. This is particularly valuable for multilingual customer communication — the same brand avatar can speak English, Hindi, Tamil, and Spanish with a consistent voice identity.

The avatar is rendered as a standard WebRTC video track. This track can be injected into any WebRTC-based platform — Samvyo, Zoom SDK, a custom conferencing platform, or a browser-based video call — as a virtual camera input. No changes to the host platform are required. For batch video generation, a REST API delivers MP4 files directly.