F5 AI Gateway Solution Overview

Deploy AI applications anywhere – and ensure security and optimization to deliver ideal user experiences.

AI Applications Present a Multitude of Protection and Operational Challenges

The launch of OpenAI in late 2022 started widespread research into and development of artificial intelligence (AI) applications. It is estimated that by 2023, 30% of enterprise applications will use generative AI (GenAI) labeling to reshape their branding in the pursuit of new revenue.*

AI applications are different from previous generations of applications that were built on the expanded usage of application programmer interface (API). AI applications still use APIs for interaction, but the inputs and outputs are non-deterministic, meaning incoming data requests and responses from the application can vary greatly from user to user. Add to this the lack of visibility and correlation of inbound prompts with outbound responses and you have a serious security risk that could wipe away the business value AI aims to deliver.

Open access to AI applications and their models, whether available internally to restricted groups or externally to anyone, presents security risks. Users can craft their own prompts which could lead to a variety of attacks, manipulations, or inadvertent misuse. Examples of attacks or manipulations include model denial-of-service (DoS), prompt injection, sensitive information disclosure, and model theft. Sensitive information disclosure can be in the form of confidential company data or customer personal identifiable information (PII) which proves to be extremely damaging and can lead to lawsuits or loss of customer confidence. Furthermore, AI hallucinations can cause issues with employees and customers alike and readily consume expensive resources.

* Gartner’s Top Strategic Predictions for 2025 and Beyond: Riding the AI Whirlwind; October 21, 2024

Maximize AI Applications while Mitigating Risks with AI Gateway

F5 AI Gateway is designed to secure and optimize access to AI applications while mitigating attacks and preventing exposure of critical information.

Protect against AI attacks

AI Gateway inspects, identifies, and blocks inbound attacks such as prompt injection, insecure output handling, model denial-of-service, sensitive information disclosure, and model theft. For outbound responses, AI Gateway identifies and scrubs PII data and prevents hallucinations. Software development kits (SDKs) enable additional enforcement of operational rules and compliance requirements for both prompts and responses to further align to operational needs.

Maximize AI-application performance and reduce costs

AI Gateway provides traffic routing and rate limiting for local and third-party large language models (LLMs) to maintain service availability and performance and control costs. The user experience is further enhanced by semantic caching which drives faster response time and reduces operational costs by removing duplicate tasks from LLMs.

Deploy AI security anywhere

AI Gateway is Kubernetes-based thereby making it deployable to public cloud, private cloud platforms, or on-premises data centers. Popular AI models such as OpenAI, Anthropic, Ollama, and generic HTTP upstream LLMs and small language model (SLM) services are supported.

Observability and audit trail for governance and compliance

OpenTelemetry support enables visibility on all metrics, logs, and traces of transactions and security events. It also delivers comprehensive metrics such as LLM/SLM token counts, request volumes, system resource utilization, and performance. For security compliance, AI Gateway configurations are readily available via export of audit data.

AI gateway diagram

AI Gateway Secures and Optimizes AI Applications

AI represents the next wave in the evolution of applications but also presents serious challenges that could easily surpass the benefits. Given that incoming prompts to AI applications could be attacks on resources or designed to exfiltrate data, securing the AI applications becomes paramount. Flexibility in deployment and LLM/SLM support are just as important as time-to-market and managing costs. AI applications require an evolved security solution to mitigate attacks via incoming prompts and to stop the leakage of sensitive data or hallucinations. Visibility over all transactions ensures that cost management, governance, and compliance are built into day-to-day operations.

Key Benefits
Secure your AI apps
  • Identify and block both inbound attacks such as prompt injection, insecure output handling, and sensitive information disclosure, as well as model theft.

Optimize AI interactions

  • Maintain performance, increase service availability, and control costs with traffic routing, caching, and rate limiting for local and third-party SLMs and LLMs. 

AI security anywhere

  • Deploy AI Gateway onto Kubernetes instances anywhere to quickly build security and performance services.

Key Features
Protect against attacks
  • Inspect and enforce security and operational policies on incoming prompts and outgoing responses.

Stop data leakage

  • Prevent unintended information disclosure with real-time identification and scrubbing of sensitive or PII data.

Optimize responses and reduce operational costs

  • Semantic caching enables fast answers to prompts without consuming SLM and LLM tokens. 

Customizable to meet business needs

  • Software development kits (SDKs) enable custom processing of inbound prompts and outbound responses for better alignment to organizational and compliance needs.