LLM Guard Alternatives

Teams that want open-source guardrails running inside their own stack with the option of an inexpensive managed tier, and who value published pricing and unlimited seats.

Regulated enterprises that need guardrails running inside their own environment, particularly those already running predictive ML alongside LLM systems, and who can work with enterprise procurement.

Teams that want composable, permissively licensed output validation living next to their application code, especially those who prefer plain Python over a policy DSL.

Enterprises and government buyers who need model supply chain security, AI asset discovery and airgapped operation, rather than application-layer output filtering.

Teams that want managed, low-latency prompt injection defence with enterprise support and are comfortable with a proprietary API and an enterprise sales process.

Teams building conversational products where the risk emerges across a dialogue rather than in one message, and who want programmable, self-hosted, permissively licensed guardrails.

Existing Coralogix customers, and teams that want AI observability and guardrails correlated with full-stack logs, metrics and traces rather than as a standalone layer.

Enterprises already buying F5 for application delivery and security, who want AI guardrails integrated into that platform rather than as a separate vendor relationship.