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Personas are the ‘character’ or ‘AI agent personality’ and contain all of the settings and configuration for that character or agent. For example, you can create a persona for ‘Tim the sales agent’ or ‘Rob the interviewer’. Personas combine identity, contextual knowledge, and CVI pipeline configuration to create a real-time conversational agent with a distinct behavior, voice, and response style. They are the main place you configure CVI behavior before you start a Conversation. At a glance
  • Persona — The agent’s identity (name, voice, behavior) plus pipeline mode, default replica, layers, documents (Knowledge Base), objectives, and guardrails.
  • Relationship to CVI — Personas hold the settings that drive a real-time CVI session; see the What is CVI? for the full stack (WebRTC, layers, Phoenix, and latency characteristics on the default path).
  • Layers (order of guides below) — Perception → STT → Conversational Flow → LLM → TTS; each has its own configuration page.

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Persona Customization Options

Each persona includes configurable fields. Here’s what you can customize:
  • Persona Name: Display name shown when the replica joins a call.
  • System Prompt: Instructions sent to the language model to shape the replica’s tone, personality, and behavior.
  • Pipeline mode: Controls which CVI pipeline layers are active and how input/output flows through the system. See Pipeline modes for how the full pipeline, Echo, integrations, and custom LLM paths differ.
  • Default Replica: Sets the digital human associated with the persona.
  • Layers: Perception, STT, conversational flow, LLM, and TTS—each processes part of the interaction and can be tuned independently (see Layers below).
  • Documents: A set of documents that the persona has access to via the Knowledge Base (retrieval-augmented generation, RAG).
  • Objectives: The goal-oriented instructions your persona will adhere to throughout the conversation.
  • Guardrails: Conversational boundaries that can be used to strictly enforce desired behavior.

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Objectives & Guardrails

Provide your persona with robust workflow management tools, curated to your use case

Objectives

The sequence of goals your persona will work to achieve throughout the conversation—for example gathering a piece of information from the user.

Guardrails

Conversational boundaries that can be used to strictly enforce desired behavior.

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Layers

Explore our in-depth guides to customize each layer to fit your specific use case:

Perception Layer

Defines how the persona interprets visual input like facial expressions and gestures.

STT Layer

Transcribes user speech into text using the configured speech-to-text engine.

Conversational Flow Layer

Controls turn-taking, interruption handling, and active listening behavior for natural conversations.

LLM Layer

Generates persona responses using a language model. Supports Tavus-hosted or custom LLMs.

TTS Layer

Converts text responses into speech using Tavus or supported third-party TTS engines.