Secure LLM Gateway with Compliance & PII Control

LLM security is the practice of protecting large language model applications from data leakage, unauthorized access, unsafe outputs, prompt abuse, and operational misuse. In production, it typically includes PII controls, model access policies, guardrails, request logging, audit trails, monitoring, and budget limits. A secure gateway applies these controls consistently across every model, provider, application, and team.

An LLM gateway sits between your applications and AI providers, enforcing policies before requests reach models and before responses reach users. For compliance, FastRouter can centralize access control, PII masking, data-privacy controls, compliance logging, and audit trails. This creates one governed control plane instead of relying on every application team to implement safeguards separately.

PII control reduces the risk of sensitive personal data being sent to models or exposed in responses. FastRouter’s enterprise governance capabilities include PII masking and data-privacy controls at the gateway layer, so policies can apply across OpenAI, Anthropic, Google Gemini, xAI Grok, and other providers without duplicating logic in each application.

FastRouter Guardrails validate and monitor both inputs and outputs. They can catch unsafe content, policy violations, non-compliant responses, and malformed outputs before they reach users or downstream systems. Because guardrails run at the gateway, the same rules apply regardless of which model or provider serves the request, improving consistency across production AI workflows.

Yes. FastRouter captures logs for LLM requests and responses, including model, provider, latency, token counts, cost, and outcome. These records support debugging, operational review, and compliance workflows. Centralized logging is especially valuable for regulated teams because it creates a uniform activity trail across multiple providers instead of fragmented vendor-specific records.

FastRouter lets organizations apply project-level and API-key-level limits, assign member roles, and configure access controls. This helps ensure only authorized teams can use sensitive, expensive, or restricted models. Enforcing these rules at the gateway also limits the impact of leaked or misused keys and keeps policies consistent across applications.

FastRouter is designed to drop into existing OpenAI SDK workflows by pointing the base URL to the FastRouter endpoint. Applications can continue calling an OpenAI-compatible API while gaining multi-provider routing, observability, failover, governance, and guardrails. This reduces migration effort because teams do not need to rebuild separate integrations for each provider.

FastRouter offers free credits for testing and exploring the platform, with no credit card required for initial access. Teams can evaluate routing, guardrails, logging, governance controls, and multi-model access before adopting it in production. Ongoing pricing details are not specified in the provided information.