Mistral Moderation API: What Its Documented Text Guardrails and Scores Actually Cover

Mistral AI's publicly documented moderation offering is a text-focused API for policy enforcement . It classifies content against defined safety categories, returns category-level scores and lets developers use thresholds or the underlying scores in their own guardrail workflows. The product is relevant to enterprises building content controls, but its documented scope is more specific than a general-purpose policy interpreter or a unified text-and-image moderation interface. Mistral's official Moderation announcement describes the service as a moderation API built to help developers identify potentially unsafe text. For teams evaluating the platform, the practical distinction matters: the available public materials center on predefined policy categories, text inputs and configurable enforcement logic. What Mistral Moderation documents Mistral Moderation is designed to return scores for a defined set of content categories. The published materials reference categories including Sexual, Hate, Violence, PII and Jailbreaking . Those scores can support an application decision, such as allowing content, routing it for review or blocking it when a category score passes a chosen threshold. This approach gives organizations a degree of implementation flexibility. A single threshold can make sense for a straightforward safety filter, while raw scores can be more useful when a business needs different handling for different risks. For example, a workflow may treat possible personal-information exposure differently from a possible jailbreak attempt, provided the organization has established its own policy and response process. Two endpoints for text workflows The public documentation describes two primary moderation paths: one for raw text and another for conversational content. The distinction is useful because an isolated text string and a multi-turn exchange can require different application handling, even when the underlying goal is content classification. Documented elemen