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The most configurable API to build leading voice AI products and scale phone operations.

Vapi is a developer platform for building voice AI agents, providing the infrastructure to create voice experiences. It allows for natural conversations, making and receiving phone calls, integrating with existing systems and APIs, and handling workflows like appointment scheduling and customer support. Vapi combines speech-to-text conversion, intelligent response processing, and text-to-speech conversion, with control over components like OpenAI, Anthropic, Google, Gladia, Deepgram, and ElevenLabs. It offers two main primitives: Assistants for fast iteration and common use cases, and Squads for multi-assistant setups. Key capabilities include real-time conversations, phone and web integration, tool integration, and multi-assistant orchestration, deployable via CLI and SDKs.
Vapi is a developer platform for building voice AI agents, providing the infrastructure to create voice experiences.
Explore all tools that specialize in api configuration. This domain focus ensures Vapi delivers optimized results for this specific requirement.
Supports over 100 languages with automatic language detection, cross-language conversation, and localized voices.
Allows voice agents to intelligently fetch data and perform actions on external APIs, enhancing their capabilities.
Provides simulated voice agent test suites to identify hallucination risks before production deployment.
Enables testing different variations of prompts, voices, and flows to continuously optimize performance.
Built-in conversation guardrails prevent model hallucinations and ensure data integrity.
Sign up for a Vapi account.
Install the Vapi CLI: `curl -sSL https://vapi.ai/install.sh | bash`.
Choose a workflow template or create a custom one.
Integrate Vapi with your telephony system, website, or app using the API or SDK.
Configure your voice agent's speech-to-text, LLM, and text-to-speech models.
Deploy and test your voice agent using simulated calls.
Monitor performance and optimize prompts, voices, and flows using A/B experiments.
All Set
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