{"type":"video","version":"1.0","html":"<iframe src=\"https://www.loom.com/embed/ccb88c40fb4f4e2b85cd9145a6612bce\" frameborder=\"0\" width=\"1778\" height=\"1333\" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>","height":1333,"width":1778,"provider_name":"Loom","provider_url":"https://www.loom.com","thumbnail_height":1333,"thumbnail_width":1778,"thumbnail_url":"https://cdn.loom.com/sessions/thumbnails/ccb88c40fb4f4e2b85cd9145a6612bce-75cfc0a8cdf5b9e6.gif","duration":401.36,"title":" Walkthrough of Voice AI Agent for Medical Patient Intake","description":"In this video, I walk through my implementation of my custom-built voice AI agent, detailing my approach to the problem and the technologies I used, including LiveKit, Deepgram, Llama.3.3 LLM, Twilio, and SendGrid. The voice AI agent successfully handles medical patient intake by asking a series of questions (including address validation), finds and schedules an user-selected doctor appointment, and sends an confirmation email. I faced challenges with tool calling and email validation, which I addressed through testing and documentation review. I also share insights on future improvements, particularly regarding email collection. Please let me know if you would like to demo the voice AI agent!"}