Learn how to build production-ready voice agents that achieve both low latency and high trust through a sophisticated MLOps pipeline that combines LLM annotation with human quality assurance. Discover HappyRobot's three-stage approach: generating large-scale synthetic labels using reasoning LLMs, implementing human-in-the-loop validation to correct drift and refine prompts using DSPy-style methodologies, and distilling knowledge into specialized, domain-tuned models through LoRA and distillation techniques. Explore the complete MLOps stack from observability systems to AI-assisted data generation and model optimization, with practical insights on transforming raw production audio into high-accuracy, low-latency voice AI models for real-world applications.