Output Filtering And Content Restriction

via “output-filtering-and-content-moderation”

AgenShield — AI Agent Security Platform

Unique: Implements post-generation output filtering with multiple moderation strategies (pattern-based, API-based, custom rules) that can be composed and weighted, rather than relying on a single moderation approach. Supports both rejection and sanitization modes.

vs others: Provides comprehensive output moderation including data leakage detection and policy compliance checking, whereas most agent security focuses primarily on harmful content filtering

via “guardrails and safety filtering with custom rules”

An open-source framework for building production-grade LLM applications. It unifies an LLM gateway, observability, optimization, evaluations, and experimentation.

Unique: Integrates safety filtering directly into the inference gateway with both built-in rules and custom rule engine, so safety is enforced consistently across all inferences without application code changes

vs others: More comprehensive than post-hoc moderation because it filters both inputs and outputs, whereas application-level filtering typically only catches output issues