Content moderation API options in 2026, and when moderation needs the live web

Content moderation APIs classify text, images, video, or audio against predefined categories such as hate, harassment, sexual content, violence, self-harm, and toxicity, with providers including OpenAI, Azure AI Content Safety, AWS Rekognition and Comprehend, Hive/Deploy, and the soon-to-retire Perspective API. These tools are well suited to screening content based on what is directly present, but they cannot reliably determine external facts such as whether a seller is authorized, a product is recalled, a domain is official, or a brand claim is legitimate. Custom decision models can apply organization-specific policies to supplied content, while web-grounded decision systems add live search evidence and citations for fact-dependent checks. Examples involving recalled DREO heaters and an ASICS authorized-retailer list illustrate both the usefulness of live evidence and the limitations of model-based retrieval for exact list membership, which may require deterministic extraction and matching. The recommended approach is to use inexpensive in-content classifiers for clear violations, reserve web-grounded checks for higher-risk factual claims, set conservative thresholds, route uncertain cases to human reviewers with evidence, and calibrate policies using logged review outcomes.

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