Real-time AI faces
Streams expressive photorealistic avatars during live conversations.
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A real-time face layer, streaming infrastructure, and API for adding expressive photorealistic avatars to conversational AI products.
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Streams expressive photorealistic avatars during live conversations.
Supports responsive listening, speaking, and reactions for natural dialogue.
Lets teams select or create faces and configure presentation and voice.
Coordinates facial movement with generated speech in real time.
Provides programmable interfaces for embedding avatars into AI products.
Offers integration tooling for building and managing live avatar sessions.
Works with established real-time audio and conversational AI platforms.
Provides a workspace for creating, testing, and refining avatar experiences.
Give support and service assistants an expressive visual presence.
Build interactive coaches for communication, wellness, or professional practice.
Create realistic role-play scenarios for employee learning.
Deliver conversational screening or practice interviews with a visual agent.
Add a speaking guide to onboarding, education, commerce, or information products.
Anam provides real-time AI avatar models and streaming infrastructure for developers building conversational products. Its expressive, photorealistic faces can listen, speak, and react with low latency, giving voice agents a visible human-like interface.
Teams can create customer-facing agents, coaches, trainers, interviewers, and guides using production APIs and SDKs. Anam also connects with conversational AI infrastructure such as LiveKit, Pipecat, ElevenLabs Agents, Agora, and VideoSDK so the face layer can fit an existing voice and agent stack.
