Weights & Biases’ Post

When you're building AI for healthcare, "good enough" can be dangerous. Hallucinations aren't just bugs; they are serious safety risks. So how do you prove your system is grounded, citable, and ready for production? This is why Simon (Xi) Ouyang's new guide on building a production ready healthcare RAG is such a must read. Evaluation wasn't just an afterthought for him; it was the core of his process. He used the Weights & Biases Evaluation Suite for continuous quality assurance, which is brilliant. Here’s how he used W&B: - Tracked custom metrics that actually matter in healthcare: think grounding_rate and citation_rate, not just generic scores. - Logged complete audit trails using wandb. Tables, capturing every single question and answer. This is huge for compliance. - Used W&B as a quality gate in his automated workflow, preventing bad models from ever reaching production. - Compared experiments side by side to show exactly how he improved his model's grounding rate by 20%! This is an amazing blueprint for building safe, auditable, and reliable AI. Read the full technical deep dive by Simon Ouyang here: wandb.me/xiouyang