Flo Health Leverages AI to Boost Content Moderation
AWS ML Blog · rss · 2026-07-15
Flo Health detailed their process of turning an AWS generative AI PoC into a production system to improve medical content moderation and generation efficiency while maintaining medical accuracy.
Key results: moderation time reduced by 60% and content throughput tripled, all without expanding the medical team. The system uses a layered validation approach: checking against internal medical guidelines first, then comparing with trusted external medical sources, and finally having human experts confirm via an annotated interface.
Implementation-wise, they split content into finer-grained fragments and set up multiple AI Judges for different dimensions like medical accuracy, legal compliance, and brand style. Each Judge can independently select different models to balance quality, risk, latency, and cost. The system then generates revision suggestions based on these reviews and writes them back into the Contentful CMS workflow.
The latter half of the article covers the AI content generation system:
- Using multi-stage chain-of-thought prompting for different tasks.
- Claude Haiku for lightweight classification and step counting.
- Claude Sonnet for high-fidelity generation and complex rewriting.
- Combining RAG with reliable medical sources to generate content and avoid hallucinations.
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