> ## Documentation Index > Fetch the complete documentation index at: https://docs.freyavoice.ai/llms.txt > Use this file to discover all available pages before exploring further. # Core Concepts > Understanding the fundamental building blocks of Freyavoice AI ## Introduction Freyavoice AI is built on several core concepts that work together to create powerful voice AI applications. Understanding these concepts is essential for building effective solutions. ## Agents **Agents** are the heart of Freyavoice AI. They are intelligent voice assistants powered by advanced AI models that can understand natural language, maintain context, and execute actions. ### What Makes an Agent An agent consists of several key components: **System Prompt**: The agent's instructions and personality. This defines how the agent behaves, what it can do, and how it should respond to different situations. A well-crafted system prompt is crucial for agent performance. **Model Configuration**: The AI model that powers the agent (GPT-4, Claude, etc.). Different models have different strengths - some are better at reasoning, others at speed or cost efficiency. **Voice Settings**: How the agent sounds. This includes the voice provider, specific voice selection, speaking speed, and voice stability. The right voice can significantly impact user experience. **Functions**: Actions the agent can take. Functions allow agents to interact with external systems, query databases, make API calls, and perform other operations beyond just conversation. **Context Management**: How the agent maintains conversation history and context. This includes conversation length limits, context window management, and memory strategies. ### Agent Lifecycle When a call comes in, the agent goes through several stages: 1. **Initialization**: The agent loads its configuration, system prompt, and any required functions 2. **Context Loading**: Previous conversation history is loaded if available 3. **Listening**: The agent receives and processes audio input 4. **Understanding**: Speech is converted to text and analyzed 5. **Reasoning**: The AI model processes the input and generates a response 6. **Action Execution**: Any required functions are called 7. **Response Generation**: The response is converted to speech and delivered 8. **Context Update**: The conversation is saved for future reference ## Workflows **Workflows** are visual, node-based systems that allow you to create complex call routing and processing logic. They enable you to build sophisticated applications that go beyond what a single agent can do. ### Workflow Components **Nodes**: The building blocks of workflows. Each node represents a specific action or decision point: * **Agent Nodes**: Connect to AI agents to handle conversations * **Function Nodes**: Execute custom functions or API calls * **Condition Nodes**: Route calls based on conditions (time of day, caller ID, etc.) * **Transfer Nodes**: Transfer to human agents or other systems * **Wait Nodes**: Pause execution for a specified duration * **Loop Nodes**: Repeat actions based on conditions **Connections**: The lines between nodes that define the flow of execution. Connections can be conditional, allowing different paths based on node outputs. **Variables**: Data that flows between nodes. Variables can store user input, function results, or any other data needed during call processing. ### Workflow Execution When a workflow is triggered: 1. **Entry Point**: Execution starts at the initial node 2. **Node Processing**: Each node executes its logic 3. **Data Flow**: Variables are passed between nodes 4. **Conditional Routing**: Conditions determine which path to take 5. **Parallel Execution**: Some nodes can execute simultaneously 6. **Completion**: The workflow completes when reaching an end node or transfer ### When to Use Workflows vs Agents Use a **single agent** when: * Your use case is straightforward * You need a simple conversation flow * You want to get started quickly * The agent can handle everything independently Use **workflows** when: * You need complex routing logic * Multiple agents need to work together * You require conditional branching * You need to integrate with multiple systems * You want to add human-in-the-loop capabilities ## Telephony Layer The **telephony layer** connects your agents and workflows to the real world through phone numbers and call handling infrastructure. ### Phone Numbers Phone numbers are your connection point to the telephony network. They can be: * **Imported**: Brought in from providers like Twilio * **Purchased**: Acquired through Freya's marketplace (if available) * **Configured**: Set up with specific capabilities (voice, SMS, etc.) ### Call Routing When a call comes in, Freya routes it through several stages: 1. **Inbound Reception**: The call is received at the phone number 2. **Number Resolution**: Freya identifies which agent or workflow to use 3. **Session Creation**: A call session is created with unique identifiers 4. **Agent/Workflow Invocation**: The configured agent or workflow is activated 5. **Call Processing**: The agent/workflow handles the conversation 6. **Call Completion**: The call ends and data is saved ### Outbound Calling For outbound calls, the process is similar but initiated by your application: 1. **Call Request**: Your application requests an outbound call 2. **Number Selection**: Freya selects the appropriate phone number 3. **Call Initiation**: The call is placed to the destination 4. **Connection**: Once connected, the agent/workflow takes over 5. **Processing**: Same as inbound calls from this point ## Integration Points Freyavoice AI integrates with various external systems: **Telephony Providers**: Twilio, and other SIP providers for call handling **AI Models**: OpenAI, Anthropic, and other LLM providers for agent intelligence **External APIs**: Webhooks and function calls to integrate with your systems **Storage**: Conversation history, call recordings, and analytics data ## Data Flow Understanding how data flows through Freyavoice AI helps you build better applications: 1. **Audio Input**: Phone call audio is received 2. **Speech-to-Text**: Audio is converted to text 3. **Agent Processing**: The agent analyzes the text and generates a response 4. **Function Execution**: Any required functions are called 5. **Text-to-Speech**: The response is converted back to audio 6. **Audio Output**: The audio is sent back to the caller 7. **Data Storage**: All interactions are logged for analytics and improvement ## Next Steps Learn how these core concepts come together in Freyavoice AI's architecture.