How to Build Explainable Image Moderation Using Multimodal AI Chat Models

Developers can moderate uploaded images for NSFW and violent content by combining a vision-capable chat model with a strict JSON schema, rather than relying on a dedicated moderation endpoint. The approach uses a policy prompt, schema validation, and a conservative fallback, with decisions stored as normalized statuses like allow, review, or block for auditability. Content categories such as nudity, graphic violence, and hate symbols should reflect each application's specific rules, since thresholds differ across platforms like medical forums, marketplaces, and social products. A key engineering lesson highlighted is cost management: one evaluation run consumed 18.7 million input tokens — about 3.4 times the estimate — largely due to duplicated policy text across retries and image variants. The recommended fix is to measure prompt tokens upfront, run small batches first, and track cost per accepted decision rather than cost per raw request.