Vapi Engineers Share Lessons on Deploying Voice AI at Enterprise Scale

Vapi's Forward-Deployed Engineers say the demo-to-production gap is where most enterprise voice AI initiatives stall, requiring extensive testing, guardrails and intent-based design rather than exact phrase matching. The team warns of "personality drift," where agents adopt callers' speech styles, and notes LLMs are non-deterministic, so deployments need defined error tolerance and continuous iteration. They advise starting with cost optimization but targeting revenue generation, and benchmark a good interaction at under a minute.