Take control of the agents on your endpoints
Monitor, govern, and secure every agent on every laptop and workstation with a single binary, rolled out through the MDM you already use
Roll out with the tools you already have
Qpoint ships as a single binary. Push it out with the tools you already use, or with the Qpoint installer.
Push the binary
Deploy through Jamf, Intune, a script, or the Qpoint installer to a pilot group or the whole fleet.
Register
Qpoint connects and registers the endpoint with the control plane.*
service running · checked inStart monitoring
Every agent shows up in the fleet view, attributed to the signed-in user.
claude-code · alice@acme* The control plane runs within your environment.
Every action, checked before it completes
Qpoint runs on the endpoint between the agents and the OS. It sees every agent start, checks each action against the rules you set, and stops the ones that break them before they complete.
If a laptop leaves the network, nothing changes. Policies are enforced locally, and events buffer until it reconnects. Alice never sees a prompt or a pop-up.
Why the endpoint, not the gateway
An AI gateway sees inference: the calls to frontier models, and nothing else. A GitHub API call, an S3 upload, or a shell command goes around it. Your corporate network sees that traffic, but can't tell an agent from a person using the same tools. Once execution crosses from the model into tools and scripts, there's no attribution and nothing to trace back.
Once an agent acts, it looks like a user
The model calls a tool, the tool runs a script, the script calls an API. To the network, that's a user, a service, or a process on the machine. There's no chain back to the agent, the session, or the prompt that started it.
Secrets never cross a gateway
SSH keys, .env files, and credential stores are read locally. Secret reads can only be prevented on the endpoint.
Local tools make no network call
Shell commands, subprocesses, and local MCP servers run without touching the wire. Qpoint sees them anyway.
Laptops leave the network
Coffee shops, home offices, planes. Enforcement that lives on the device works wherever the device is.
Know what's running. Prove what happened.
Fleet-wide coverage for the teams that own the endpoints, and the evidence for the teams that answer for them.
Agent activity, not just inventory
The tools they use, the MCP servers they connect to, the data they touch, on every host.
Usage and cost reporting
Tokens and spend over time, by team, provider, and agent, down to the session.
Policy evidence
Every violation and every block, with the agent, session, and user attached.
No changes for users
No wrappers, no proxies, no new workflow. Qpoint starts in the background and places itself between each agent and the OS as the agent runs. The agent doesn't know the difference, and neither does the person using it.
Nothing leaves your environment
The control plane and the event stream run where you run them. Qpoint never sees your data.
Policies as plugins
Run the built-in plugins or write your own against the same hooks: log, tag, rewrite, or block any file read, tool call, or outbound request.
Run Qpoint wherever your agents run
Laptops, servers, and other people's products. One binary, one event stream, deployed where the agents are.
Seconds, not sprints
Qpoint deploys as a single binary directly on the endpoint. No gateways to route through, no enterprise infrastructure to provision, no SDK integration to schedule.
Install, run, and start seeing every AI agent on the machine — in under a minute.