SUPERWISE Launches Sentinel to Govern Enterprise LLM Traffic at the Network Edge

Sentinel guards organization’s AI traffic, redacting secrets, PII, and toxic content before it ever leaves the perimeter

SUPERWISE, the Agentic Management Platform, announced the launch of Sentinel, an enterprise AI gateway that gives organizations a live guardrail layer over every large language model (LLM) interaction in their business. Deployed as a lightweight gateway at the network edge or locally on user’s PCs, Sentinel protects company and customer data in AI traffic by redacting secrets, personally identifiable information (PII), and toxic content in real time; all while ensuring raw data never leaves the customer’s perimeter.

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As AI adoption accelerates across engineering and business teams, most organizations have little to no visibility into how employees and applications are actually using large language models. Sentinel addresses that blind spot directly, giving security and compliance teams a single control plane to answer a question that has become increasingly difficult to answer: what is our AI allowed to say, and can we prove it?

Sentinel is built to protect against the risks defined in the OWASP LLM Top 10, including prompt injection, data leakage, jailbreaks, and unsafe output. It works across any model or provider, including OpenAI, Claude, and Gemini, and deploys via Docker, the CLI, or directly into a customer’s container cluster, without requiring security code to be added to any individual application.

“Every team we talk to is already using AI, whether IT knows about it or not. That’s the reality we built Sentinel for,” said Russ Blattner, CEO of SUPERWISE. “Organizations don’t need another policy document telling people what not to do with AI; they need a system that sees the traffic and enforces the policy in real time. Sentinel gives security teams that visibility without slowing engineering down, and it keeps the customer’s data inside their own perimeter the entire time.”

How Sentinel Works

Sentinel follows a simple three-step model: deploy a sentinel proxy at the edge, route AI traffic through it, and capture, redact, and log action. Its split-plane architecture keeps raw prompts and responses inside the customer’s own perimeter, while a real-time Activity Log streams redacted interactions for monitoring and compliance, with a full audit trail mapped to the OWASP LLM Top 10.

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