LlamaIndex and Vellum have partnered to enhance the integration of large language models (LLMs) with private data and improve the prompt engineering process for developers. LlamaIndex serves as a popular open-source framework for LLM data augmentation, while Vellum offers a developer platform that includes advanced tools for prompt engineering, unit testing, regression testing, and model fine-tuning. This collaboration aims to address the challenges of ensuring reliable LLM output in production by offering features like sandbox environments, prompt versioning, and comprehensive testing suites. Developers can use Vellum to register and manage prompts within LlamaIndex, leveraging tools to test and optimize prompts and receive feedback on LLM performance in real-world applications. The approach encourages detailed prompt customization, iterative testing across multiple scenarios, and consideration of different foundational models to achieve optimal results. Additionally, evaluation metrics are tailored to specific use cases, such as classification, data extraction, and creative output, with Vellum providing tools to track and assess model quality using both explicit and implicit user feedback.