Runtime visibility into the AI your employees use

Teams spend their energy arguing about plumbing — proxy versus endpoint agent versus kernel hook — as if getting on the path were the hard part. It isn’t. Whatever carries the bytes, the question that decides whether regulated data leaks is the same: at the instant AI sends or receives something, does anything inspect the content and act? That is what we mean by runtime — inline, at the moment of the call, not a report compiled after the fact.

Getting on the path is table stakes

There are a few honest ways onto the path, and BlueAspen uses the right one for each surface:

• Employees using AI — a TLS-inspecting forward proxy paired with a lightweight endpoint agent, covering browser, desktop and app traffic to AI across 40 providers and roughly 6,000 AI domains
• Agents you run — an inline Agent Proxy for egress to MCP tools, other agents and models, and an MCP Gateway that fronts the servers you expose
• Linux workloads — the endpoint agent can attach at the OS level, so coverage doesn’t depend on every service remembering to route through anything

Each of these is a solved problem. None of them, on its own, stops a leak. They just put you in the one position from which you can.

Runtime is where the outcome is decided

Once you’re on the path, runtime control is the whole game — and it’s four things working together:

• Data, not traffic — inspect and redact the content, especially on the result leg where the sensitive part usually is
• Audit-grade detection — real validators (Luhn, NPI, IBAN, Shannon entropy) across 60+ context-scored patterns, each finding explained, tuned for low false-block
• Fail-closed where it guards data — on ingress and agent-to-tool paths a call we can’t judge never reaches the data; a misconfigured gateway refuses to start
• Find what’s undeclared — the AI apps, MCP servers and agents nobody registered, surfaced from the traffic itself

Any interception point can log that a tool was called. Runtime control inspects what it returned — and redacts the SSN or account number in place, so the reply stays valid and the AI keeps working.

Postures, not one switch

Runtime also means the enforcement posture can differ by surface, on purpose. Where an agent acts on data, BlueAspen fails closed — deny what you can’t judge. Where an employee is just trying to work, it fails open — a policy outage must never block a person. Same engine, opposite defaults, each correct for its path. That distinction is a runtime decision; it has nothing to do with how you got on the wire.

Two surfaces, one engine

Behind both the employee and the agent paths sits one policy engine and one detection stack, with twelve analyzers running on local ONNX models so that by default no customer data goes to a third-party LLM. BlueAspen is data security for AI, and it complements the DLP, CASB and AI gateway you already run rather than replacing them.

So by all means pick the interception that fits your environment — then judge a platform on what it does in the millisecond that follows.