See every agent.
Control what they do.
Runtime governance for the AI agents already running in your environment.
QControl instruments the agent from the inside out — every file it reads, every tool it calls, every request it makes, every process it spawns. Captured at the source. No gateway, no sidecar, no SDK to adopt.
No layer of your stack was built for the agent.
Identity sees users. The perimeter sees encrypted flows. EDR sees processes. None of them see the agent itself — the thing actually reading files, calling tools, and reaching out to the network.
You can't see them
Agents don't register in your asset inventory. They run inside node, python, and shell — instrumented on some boxes, completely dark on others.
You don't know what they're doing
File reads, tool calls, outbound requests, spawned subprocesses — none of it surfaces in your SIEM, your EDR, or your compliance evidence.
You can't secure them
You can't write policy for something you can't see. Today, agents act with whatever permissions the host process happens to carry.
Three verbs. One binary.
Audit before you arm. Every control runs Audit → Assist → Enforce, so you can see exactly what a policy would block before it blocks anything.
Discover
Find every agent on the box — by process signature, file fingerprint, and embedded-runtime detection. Including the ones that have gone dark.
Observe
Watch what they do in real time. File access, tool invocations, network requests, subprocesses — normalized into one stream, attributed to the agent.
Enforce
Decide what happens next. Redact a credential before it's read, block a destination, gate a dangerous action — same hot path, same plugin shape.
Everything an agent does, made governable.
Agent inventory & shadow detection
A live roster of every agent — owner, model, credential, last activity — ranked by risk, with the installed-but-uninstrumented blind spots called out by name.
Behavioral findings, mapped to frameworks
Dangerous behavior — running as root, unbounded consumption, excessive capability, credential reads — auto-mapped to OWASP LLM, MITRE ATLAS, and NIST AI RMF.
Machine-identity governance
Where each agent's credential came from, whether it meets your standard (org-backed OAuth vs. a static key), how old it is, and its blast radius if leaked.
Policy dry-run before you enforce
See the names, not just the counts: which agents an enforcing policy would block, which tool calls it would gate. Try it before you arm it.
The numbers you'd see on day one.
See what your agents are doing.
One binary. Ten minutes to install. Works against the agents already running.