The Model Gets Intelligence. STRATUM Provides Control.

The STRATUM AI runtime gives the model generic operational capabilities such as infrastructure discovery, console observation, keyboard and mouse input, Guest Tools, secure credentials, approvals, execution, and verification. Skills add the specialized knowledge needed for a particular job, whether that means installing an operating system, configuring a network service, or applying a security procedure.

The principle is simple: the LLM decides what to do, Skills provide relevant expertise, and STRATUM enforces what is allowed and verifies what actually happened. The model can request a tool call or propose a change, but the harness validates the request against the real environment before anything is allowed to affect infrastructure.

Credentials follow the same model. The LLM never needs to see the secret value. STRATUM can expose a credential reference while keeping the username, password, token, or other protected value inside the platform. The model can still complete the mission without becoming the place where infrastructure secrets live.

Our design rule has become straightforward: specialists advise, the main AI investigates, STRATUM validates, and the user approves material changes. If a specialist produces malformed output, STRATUM treats that as an AI response that needs recovery. It does not turn a bad model response into a fake switch failure, VM failure, or datacenter failure.