Vapi

Processes incoming voice calls and conducts natural, multi-turn conversations with human-like interruption handling and barge-in detection. Manages call state, context retention, and natural conversation flow without requiring manual turn-taking.

Automatically detects, synthesizes, and recognizes speech across multiple languages with accurate accent handling and proper phoneme pronunciation. Eliminates manual language configuration and localization overhead.

Processes dual-tone multi-frequency (DTMF) signals from phone keypads, enabling touch-tone menu navigation and numeric input collection during calls.

Detects when users are speaking versus silent, managing conversation timing, avoiding awkward pauses, and determining when to process user input.

Delivers real-time call events (speech detected, transcription, user input, call ended) to application webhooks, enabling custom business logic and integration with existing backend systems.

Provides programmatic control over voice calls through REST endpoints—initiate calls, transfer calls, end calls, and retrieve call history and metadata without complex SDK dependencies.

Allows configuration of voice characteristics, conversation behavior, and system prompts to customize how the AI responds and sounds during calls.

Automatically records voice calls and generates transcripts, storing them for later retrieval and analysis without requiring separate recording infrastructure.

Routes incoming calls to appropriate handlers and initiates outbound calls to phone numbers or SIP endpoints, managing call queuing and distribution.

Converts spoken audio to text in real-time or batch mode, maintaining context across conversation turns for accurate transcription of natural speech patterns.

Seamlessly transfers calls between AI agents, human agents, or external systems while maintaining conversation context and call state.

Collects and reports metrics on call duration, success rates, user satisfaction, and conversation quality to enable monitoring and optimization.