F5 , the global leader in delivering and securing every app and API, introduced F5 AI Guardrails integrated with NVIDIA NeMo Guardrails, an AI-native solution that brings F5’s enterprise-grade AI security capabilities to production AI applications.
Security remains a primary reason enterprises struggle to move AI from pilot to production. Organizations adopting multiple AI models and frameworks across hybrid multicloud infrastructures face fragmented security controls, inconsistent policy enforcement, and governance gaps that widen with every new AI application. Most AI frameworks include basic safety checks, but those controls are embedded inside individual applications rather than enforced centrally. Security and compliance teams are left stitching together visibility across tools and applications with no single place to inspect AI traffic, apply policy, or audit what happened.
F5 AI Guardrails integrated with NVIDIA NeMo Guardrails brings centralized, consistent security and governance across AI applications by separating security enforcement from the AI framework. Organizations can standardize on NVIDIA NeMo Guardrails while F5 AI Guardrails handles security inspection of prompts and LLM responses, applying enterprise policies centrally without requiring changes to AI applications. The result is a layered architecture where the framework library, microservices, orchestration, and security each do what they do best and evolve independently.
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“Enterprises do not have a shortage of AI applications. They have a shortage of consistent security and governance across them,” said Kunal Anand, Chief Product Officer at F5. “As AI moves into production, fragmented controls create risk, complexity, and delay. This integration gives security teams a unified point to inspect AI traffic, enforce policy, and govern AI applications across their environments, while giving developers the freedom to keep building.”
Centralized security inspection for production AI
F5 AI Guardrails secures AI systems, inspecting prompts and responses between users and applications, and helping prevent prompt injection, PII exposure, data leakage, and malicious outputs. Security policies are applied centrally rather than built into each AI application, so organizations can enforce enterprise security requirements without modifying application code. Key capabilities include:
- Prompt and response inspection: Security policies are enforced on AI traffic in real time, helping detect and reduce prompt injection, unauthorized data disclosure, and harmful outputs before they reach users or downstream systems.
- Centralized policy enforcement: Security teams apply and manage AI security policies across applications from one place, without rewriting application code or modifying workflows.
- Consistent visibility across AI applications: A single view into AI application behavior across models, frameworks, and business units lets security teams monitor, audit, and act from one operational layer.
- Independent, layered architecture: F5 security inspection layers on top of the NVIDIA AI framework. Each can be updated, scaled, or replaced independently as requirements change.
This approach eliminates the tension between development speed and security requirements, enabling AI platform teams to move fast on orchestration while security teams maintain independent control over inspection, policy, and governance. With this solution, neither must wait for the other.
“NVIDIA NeMo Guardrails provides an open, programmable framework for applying safety and security policies to AI applications,” said Ash Bhalgat, Senior Director of AI Networking and Security Solutions, Ecosystem and Marketing at NVIDIA. “The integration with F5 AI Guardrails expands the range of protections customers can use to secure LLM prompts and responses as they move AI agents into production.”
SOURCE: Businesswire