Labelbox's Model Foundry leverages GPT-4 to automate data labeling processes, offering a robust solution for machine learning teams to overcome the challenges of starting from scratch. By using pre-labeling techniques, teams can accelerate model development and reduce costs. GPT-4's capabilities in tasks such as text summarization, language translation, and classification make it a versatile tool that outperforms traditional crowd-sourced labeling methods. Through prompt engineering, users can craft inputs that guide GPT-4's output to align with specific business needs, enhancing the model’s performance. Model Foundry provides access to a variety of models and simplifies the prompt engineering process with templates, allowing users to preview and modify predictions before final submission. This approach is demonstrated in applications such as movie plot classification, product categorization, travel review classification, and tweet sentiment analysis, showcasing the potential of GPT-4 in improving AI workflows across different industries.