Atmee

Ziddny is an AI-driven platform for creating lifelike, interactive 3D conversational avatars that can engage users in customer service, healthcare, education, training, and more. It supports over 40 languages and brings natural emotions, gestures, and on-screen cards to each avatar, with an optimized pipeline that ensures high scalability and low latency. Users can choose from realistic, stylish, futuristic, or animal-inspired designs, or request fully custom avatars, tailoring visuals, voices, and personalities to their brand or application. Avatars can be deployed instantly via a website widget or shared link after a simple three-step setup: crafting a creative prompt and knowledge base, configuring analysis and summary behaviors, and selecting the desired voice and language. With intelligent agent capabilities, Ziddny’s avatars not only converse but also process and present information dynamically, making digital interactions more engaging and personalized.

HunyuanVideo‑Avatar supports animating any input avatar images to high‑dynamic, emotion‑controllable videos using simple audio conditions. It is a multimodal diffusion transformer (MM‑DiT)‑based model capable of generating dynamic, emotion‑controllable, multi‑character dialogue videos. It accepts multi‑style avatar inputs, photorealistic, cartoon, 3D‑rendered, anthropomorphic, at arbitrary scales from portrait to full body. Provides a character image injection module that ensures strong character consistency while enabling dynamic motion; an Audio Emotion Module (AEM) that extracts emotional cues from a reference image to enable fine‑grained emotion control over generated video; and a Face‑Aware Audio Adapter (FAA) that isolates audio influence to specific face regions via latent‑level masking, supporting independent audio‑driven animation in multi‑character scenarios.