Phoenix-4: Real-Time Human Rendering with Emotional Intelligence
Phoenix-4 is the first real-time model to generate and control emotional states, active listening behavior, and continuous facial motion as a single, unified system. It is a real-time behavior generation engine, built from the ground up, that goes beyond photorealism to transform conversation data into emotionally responsive, context-aware facial expression and head motion with millisecond-level latency.
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Face-to-face conversational AI use cases | 2026
Conversational AI use cases across industries: where text and voice work, and where face-to-face changes trust, presence, and outcomes.
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AI conversations in 2026: what makes them feel human
Better language models haven't fixed AI conversations. Discover the three behavioral signals that shape whether people feel heard, and how to deliver them.
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Intelligent virtual agents: from scripted to sentient-feeling
Trace three generations of intelligent virtual agents, from rule-based scripts to perceptive AI Personas that see, hear, and respond like a person in the conversation
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Conversational AI for finance: building advisor-quality conversations at scale
Text and voice fall short in high-stakes finance conversations. Learn how video AI Personas read nonverbal cues to build trust and retain clients.
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Face-to-face conversational AI in insurance: scaling claims and policy conversations without scaling headcount
Learn how face-to-face conversational AI in insurance handles claims, renewals, and coverage conversations at infrastructure cost.
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Conversational AI for product adoption: how AI video agents drive feature discovery and activation
Tooltips and tours hit a ceiling. See how conversational AI for product adoption uses face-to-face video agents to drive feature discovery and activation.
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Virtual recruiters guide: Deploying AI video agents for always-on candidate screening
Virtual recruiters are deploying AI video agents to screen candidates in real-time conversations around the clock. Learn how to scale hiring without adding headcount.
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Latency in conversational AI: a testing guide for sub-second response
Learn how to test and reduce the latency of response in conversational AI across text, voice, and video.
AI Personas: designing personality, voice, and behavior for video agents
AI personas shape how video agents sound, respond, and emote. Learn the five design layers that turn conversational AI into a believable interaction.
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Benefits of conversational AI: why video multiplies the impact
The benefits of conversational AI multiply when agents can see, hear, and respond in real time. Eight reasons enterprise teams are making the shift to video.
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Agentic AI explained: what happens when your agent has a face
Agentic AI systems can act, but most fail at the conversation. Learn why face-to-face video closes the trust gap and improves completion rates.
Enterprise conversational AI: build vs. buy for AI Personas
Enterprise conversational AI now extends to video. See why AI Personas require a new build-vs-buy decision and how they drive better outcomes.
Multimodal AI agents: why voice + vision outperforms text alone
Learn how a multimodal AI agent processes voice, video, and text together to understand what customers really mean, and why that changes results.
What is an AI agent? Types, architecture, and the role of video
Learn what an AI agent is, explore the key types and architecture, and discover why the perception layer matters most for conversational AI experiences.
Immersive learning with AI video: why presence improves retention
Discover how immersive learning with real-time AI video creates presence, drives active retrieval, and improves training retention across your organization.
