From Prototype to Production: How Perk Built a Voice AI Agent That Makes 10,000 Calls a Week
Notes de l’épisode
Guests
- Steven Payne, Product Manager, Perk
- Gabriel Stock, Senior Engineering Manager, Perk
- Philipe Steiff, Senior Software Engineer, Perk
What we cover in this episode
- How Perk's team identified an AI use case by connecting prior experimentation with a real operational problem
- Why they chose Make.com for prototyping—and shipped to production without touching backend code
- The evolution from a single prompt to structured conversation stages (IVR handling, booking confirmation, payment request)
- How breaking up the agent's task dramatically improved reliability
- Building two eval systems: classification for success rates and LLM-as-judge for conversational behavior
- Why the team still listens to calls manually even with automated metrics
- The challenge of prompt engineering for voice: numbers, booking references, and text-to-speech markup
- Lessons learned from expanding to German (prompts in native language improve results)
- How this project uncovered other operational problems they didn't know existed
Resources & Links
- Perk
- Make.com – No-code automation platform used for the prototype
- Twilio – Voice/telephony provider
- 11 Labs – Text-to-speech provider (used in early experiments)
Chapters
00:00 Introduction to the Team 01:54 Understanding PERK's Mission 02:59 Challenges in Travel Booking 07:27 AI Solutions for Customer Care 09:52 Prototyping with AI and Voice 17:00 Implementing AI in Production 25:51 Learning Through Trial and Error 26:40 Prompting Challenges and Solutions 27:58 Iterating on Prompts and Evaluations 30:08 Scaling and Production Challenges 32:43 Advanced Evaluation Techniques 35:32 Real-World Applications and Success 49:07 Future Directions and Expansion 53:53 Conclusion and Team Reflections