Azure AI Content Safety

Azure AI Content Safety is a cloud API service that detects harmful text and images, flags prompt injection, and helps organizations moderate AI and user-generated content.

Overview

Azure AI Content Safety provides moderation capabilities designed for both user-generated content and generative AI pipelines. Its models classify text and images across categories such as hate, violence, self-harm, and sexual content with adjustable severity thresholds, and a prompt-shields feature detects jailbreak and injection attempts aimed at LLM applications. The service integrates natively with Azure AI Studio and the broader Azure ecosystem, letting teams wire moderation into chat applications, content platforms, and copilots with a few API calls. Groundedness detection helps teams verify that generated answers stay faithful to source material. As a managed service, it carries Azure’s compliance certifications, which simplifies procurement for organizations with strict regulatory obligations. Custom categories allow organizations to enforce house rules beyond generic harm taxonomies, and the analyze API returns category scores and flagged spans so applications can make granular moderation decisions.

Key Features

• Text and image classification across harm categories with severity levels
• Prompt shields detecting jailbreak and injection attempts
• Groundedness detection for generated-answer verification
• Custom categories for organization-specific moderation rules
• Native integration with Azure AI Studio and Azure services
• Flagged-span responses enabling granular, application-level moderation decisions

Pricing

Azure AI Content Safety includes a free tier for evaluation and development. Standard pricing bills per unit of text and image processed, with regional availability and Azure enterprise agreements applying.

Who Is It For

Developers and enterprises building chat applications and content platforms on Azure that need reliable, certified content moderation and LLM input protection. It fits teams that want moderation as a managed, auditable service rather than maintaining custom classifiers and their ever-growing rule sets in-house. Operations teams gain consistent moderation policies across applications that would otherwise each implement their own filtering.