Right where AI runs.
Your team is already running AI tools you never approved and most of the sensitive data going into them slips through undetected. APE gives you real-time visibility into AI running directly on your endpoints, and lets you enforce policy right where the activity happens.
APE is the AI-governance module of the Raven platform. AI now runs directly on the endpoint, where network-based tools like DLP, CASB, and EDR can't see it. APE watches AI activity on the device the moment it starts and ties it to the files being accessed, so you can enforce policy before sensitive data is ever read in.
APE builds a live, per-endpoint inventory of the AI running directly on your devices, and the file activity and actions it's performing. You finally see the local models and coding assistants that never show up on the network.
Set what each AI process is allowed to touch. Raven can scope an assistant to approved locations and deny it your credential store or customer-data directory outright. The moment a process crosses the line, Raven steps in with no human in the loop needed.
Raven plants decoy files in sensitive locations. If an AI process opens one, it fires a real-time alert with full context and can stop the process on the spot, while your real data stays concealed the whole time.
Every AI-process-to-file access is logged with full context: which AI tool touched which data, when, and in what order. That's the evidence trail regulators and cyber insurers increasingly expect.
APE runs on the same Raven sensor you already deploy, so adding AI governance doesn't mean another tool to roll out. It works alongside your existing security stack, and every AI event flows into the Arms Cyber dashboard or your SIEM, including Splunk and Microsoft Sentinel.
of employees use AI tools their employer never approved
UpGuard, 2025AI policy enforcement is how security teams see and control the AI tools running across their organization, and prove that control to auditors. Arms Cyber's APE module does it at the endpoint, where local AI runs: it inventories the AI on each device and enforces what each AI process is allowed to touch, with a full log of every access.
Shadow AI is AI your team runs without approval or oversight, often local models and coding assistants operating directly on the endpoint. Most of it runs on the endpoint, so network-based security never sees it, which is exactly the gap APE was built to close.
Start by seeing it. APE gives you a per-endpoint inventory of the AI running directly on your endpoints, then lets you set what each one is allowed to touch. You get visibility and control from the same sensor.
Most AI controls, including DLP, CASB, and EDR, watch network traffic, but local models and coding assistants run right on the device and send no observable network signal. APE watches AI activity on the endpoint itself, so it sees what those network-based tools miss.
Yes. You can scope an AI assistant to approved locations and deny it sensitive ones like your credential store or customer-data directory.
Yes. APE logs every AI-process-to-file access with full context, so you can show auditors which AI tool touched which data, when, and in what order. That evidence trail is what regulators and cyber insurers increasingly ask for, from the EU AI Act to SEC guidance.
No. APE is delivered through the Raven endpoint sensor you already run, with no new software to deploy and no rip-and-replace. It works alongside your existing stack and reports into your dashboard and SIEM.
See every AI tool running on your endpoints and enforce your policy right where the data lives, before anything sensitive is exposed.
