Your ML model’s success requires more than data. It needs a comprehensive approach to quality control that engages with an annotation partner who’s well-versed in the latest research-driven practices, a smart quality strategy that balances annotation precision with practical needs, and the agility to recognize and propose process enhancements in real-time.