How to Build an AI Agent for Inbound Calls (That Actually Works)

Did you know you can create your voice AI agent that can listen, understand, respond, and act like a human? Thanks to AI, you are not required to learn full-stack AI technologies, but with a simple approach, you can create a real AI agent for inbound calls. With AI agents, you can answer calls 24/7, even on weekends and holiday, and handle repetitive questions.

Tech Stack

• Telephony Integration: Twilio, SignalWire, or Vonage
• Speech-to-Text (STT): Google Cloud Speech, Microsoft Azure Speech, or AssemblyAI
• Natural Language Understanding (NLU): Dialogflow CX, Rasa, Microsoft Copilot Studio, or OpenAI GPT
• Text-to-Speech (TTS): Amazon Polly, Google Cloud TTS, ElevenLabs for lifelike voices
• Orchestration/Logic Layer: Your code (Node.js, Python) r a visual flow builder like Voiceflow
• Optional: CRM/API integrations, databases, analytics

Inbound call flow

The Twilio Studio receives your call and passes it off to your AI. Google Speech-to-Text or Microsoft Azure Speech transcribes spoken input within milliseconds.

Caller Intent

Now it’s time to figure out what the caller wants:

• Use Dialogflow CX for flow-based intent handling.
• GPT-4 API for learning.

How You Respond

Use a dialog tree, dynamic templates, or AI to craft the response, and convert it to audio.

Monitor, Train, Improve

• Use call analytics to see where people drop off.
• Retrain NLU models with real-world transcripts.
• A/B test responses to reduce friction.
• Human-in-the-loop review for edge cases.

An AI-powered inbound voice agent works 24/7, doesn’t get tired, and gets smarter over time.