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End-to-End Conversational Voice Agent Deployment Workflow
A comprehensive guide to building, testing, and deploying real-time voice agents and LLM-driven chatbots handling complex customer interactions.
7-step workflow4 KBUpdated 3/13/2026
Conversational AIVoice AgentsAutomationLLMOutbound Automation
End-to-End Conversational Voice Agent Deployment
3.5 hours
Advanced
7 steps (showing 2)
1
Initialize the Application Codebase
Input:
System requirements and project architecture plan
Action:
Use AI-assisted coding to bootstrap a local repository and create robust webhook endpoints to handle call state updates and function calling.
Prompt:
Create a FastAPI server to handle incoming webhooks from Vapi and Bland AI. Include endpoints for /inbound, /outbound, and /call-status. Include comprehensive logging.
Output:
A fully functioning local dev environment and webhook server.
30 minutes
→ Next: Build the knowledge base to power the agent's logic.
2
Establish the Knowledge Base & LLM Logic
Workflow·End-to-End Conversational Voice Agent Deployment Workflow