Tavus: AI Avatars

What is Tavus?

Tavus is an AI avatars platform that lets developers and enterprises deploy real-time, face-to-face video agents capable of seeing, hearing, and responding with human-like emotion. The platform solves the gap between text or voice AI and genuinely human-feeling interaction by rendering photorealistic digital humans that hold live, two-way video conversations. Tavus covers three core capability groups: real-time rendering and facial animation, multimodal perception of the user’s expressions and tone, and conversational flow management that handles natural turn-taking and interruptions.

The platform is built around three proprietary models. The rendering model produces high-fidelity facial animation including micro-expressions and emotion-driven reactions. The perception model analyzes facial expressions, gaze, tone, and emotional state in real time and feeds that context into the AI’s reasoning. The turn-taking model uses lexical, prosodic, and acoustic signals to decide when the agent should speak versus listen. Developers access all of this through a Conversational Video Interface (CVI) API, and non-technical users can build AI avatars with a no-code tool called PAL Maker.

Features & Benefits

• Real-Time Avatar Rendering: produce full-face animation at 1080p and 40+ FPS with context-aware micro-expressions, active listening reactions, and explicit control over more than 10 distinct emotions.
• Multimodal Perception: read the user’s facial expressions, gaze direction, tone of voice, and emotional state in real time using the Raven perception model; feed those signals directly into the connected LLM.
• Natural Turn-Taking and Interruption Handling: detect when a speaker has finished using lexical, semantic, prosodic, and acoustic cues; configure patience thresholds and interruptibility so conversations feel natural rather than robotic.
• Bring-Your-Own LLM: connect any OpenAI-compatible language model to power the agent’s reasoning; keep proprietary model logic private.
• Bring-Your-Own Voice: integrate any text-to-speech provider including ElevenLabs and Cartesia, or supply a custom voice model.
• Function Calling Mid-Conversation: trigger external actions during a live session such as booking meetings, pulling records, submitting forms, or calling third-party APIs; the LLM decides autonomously when to invoke each tool.
• Knowledge Base with RAG: upload PDFs and documents or crawl websites so the agent answers from verified source content with 30ms retrieval.
• Cross-Session Memory: persist conversation context across multiple sessions and tie memories to individual users, sessions, or shared contexts like classrooms.
• Multilingual Support: deploy agents in 50+ languages with native-quality voices and automatic speaker language detection.
• Conversational Override: inject responses verbatim or directionally into a live session, force topic changes, or adjust turn-taking behavior without interrupting the conversation.
• Conversation Data Layer: generate structured output from every session including full transcripts, emotion timelines, perception events, and sentiment shifts for export or real-time analysis.
• Stock and Custom Replicas: choose from 100+ pre-built avatar replicas or train a custom replica from two minutes of recorded video.
• No-Code PAL Maker: create and deploy an AI avatar from a single text prompt without writing code; publish directly to a website or app.
• WebRTC Transport: deliver video conversations over WebRTC with sub-500ms average response latency.
• White-Label Deployment: remove Tavus branding for enterprise use cases requiring a fully branded experience.

What can Tavus do?

• Build real-time AI video agents for websites and apps
• Create a custom AI avatar from a short video recording
• Add face-to-face AI interviews to a recruiting platform
• Deploy a multilingual video concierge for hospitality or travel
• Build an AI patient intake agent that reads facial expressions
• Conduct structured video interviews scored against a rubric
• Power an adaptive AI tutor that remembers past sessions
• Add a 24/7 property concierge that books viewings mid-conversation
• Generate full conversation transcripts with emotion timelines
• Trigger CRM or calendar actions from within a live video call

Real-World Applications

Healthcare platforms can use Tavus AI avatars to handle patient intake before a clinical visit. The agent reads facial cues for signs of distress or confusion, adjusts its communication style in response, and submits completed intake forms to an EHR system and books follow-up appointments without any human intervention. The emotion detection and function-calling capabilities combine to reduce administrative burden while giving patients a more responsive first interaction.

Recruiting and HR teams can deploy a structured interview agent that conducts consistent, rubric-scored video interviews across large candidate pools. The agent follows a fixed question flow, scores responses in real time, and automatically submits evaluations to an applicant tracking system. Cross-session memory stores context for panel debriefs, making it practical to run multi-stage interview processes at scale.

Financial advisory services can use the platform’s data layer and perception capabilities to run compliance-ready client review calls. Every session is logged with a full transcript, emotion timeline, and sentiment analysis. The perception model flags hesitation before a client commits to a risk decision, giving advisors a reviewable record that meets regulatory requirements.

Real estate teams and property management companies can stand up a 24/7 property concierge loaded with listing data via RAG. The agent answers detailed questions about specific properties, detects buyer interest through visual and tonal signals, and books viewings directly into a calendar without requiring a live agent on call.

Software teams building customer-facing products can embed AI avatars into their own apps using the CVI API and a React component library. A chat or support feature that previously used text or voice gets replaced with a face-to-face video agent that perceives user frustration, adjusts its tone, and escalates to a live human when needed. The modular pipeline lets engineering teams swap in their own LLM, voice provider, and knowledge base without rebuilding core infrastructure.