Put enterprises and people in control of AI
Discover every AI agent running in your environment, trace what it does, and stop it in real time when it crosses a line.
- Find shadow AI your perimeter never sees — including local models on developer machines
- Full interaction graph: human to agent, agent to agent, agent to tool
- Inline enforcement, DLP and human-in-the-loop approvals
- 13 regulatory frameworks, audit evidence out of the box
Your data is training AI models right now, without your consent and without paying you. Privify SHIELD gives you the switch.
- Opt out of AI training datasets
- See which services are harvesting your data
- Earn rewards when your data is licensed ethically
- Works with Google, LinkedIn, Amazon and more
The agents your gateway will never see
An MCP gateway only sees traffic that chooses to speak MCP. Local models, direct API calls, and an employee pasting into a chat window all reach the internet without ever routing through one — and that's exactly where AI risk actually shows up. Privify FORGE runs on the endpoint, where the agent actually executes, so it catches all three.
See the full coverage mapShadow AI you can't attest to
A control you cannot evidence will not survive an audit — and no one can evidence a model they never knew was running.
Coverage numbers that flatter you
A gateway can only report the traffic that reached it, so the gap never appears in the percentage you take to the board.
Detection is not prevention
Auditors separate a control that stops an action from a log that records one — only one of them satisfies a preventive requirement.
Your largest exposure is human
Most AI incidents begin with an employee and a chat window, not an autonomous agent — the same policy has to reach both.
How Privify FORGE actually works
Three stages, running continuously on every endpoint in your environment — discover every agent, observe what it touches, govern what it's allowed to do. No agent registry to maintain, no cooperation required from the tools you're trying to govern.
See how each stage worksPricing tailored to your organization
Privify FORGE is priced per deployment, not per seat off a rate card. Environment size, deployment model and enforcement scope all move the number — so we quote it properly instead of guessing publicly.
Let's scope it together
Tell us how many endpoints you're covering and where your agents run. We'll come back with a deployment plan and a price, typically within two business days.
Questions we get from security teams
Something not covered here? Ask us directly — it reaches the founding team, not a queue.
Where does Privify FORGE run, and does our data leave our network?
Privify FORGE is designed to run inside your own environment. The management plane, database and event store are yours, and the discovery probes execute on the endpoint and report to your management plane — not to us.
In a self-hosted deployment, your agent activity, traces and DLP findings never reach Privify. That is the point of putting the control plane where your data already lives.
Which platforms do you support?
Inline blocking on Windows, macOS and Linux. Policy is evaluated at the moment an agent acts, and a blocked call is stopped before it reaches the provider rather than logged after the fact.
On Windows, enforcement additionally runs in the OS network stack via a kernel driver, evaluating policy at the TCP connect boundary — which applies regardless of how the agent routes its traffic. If unconditional enforcement is a control requirement for you, that's the deployment to ask about.
How is this different from the DLP or CASB we already own?
Those tools were not built for AI. A CASB governs sanctioned SaaS. A DLP inspects data leaving a known channel. Neither was designed for one agent calling another, a tool invocation on your behalf, or a model running locally on a developer's laptop.
Privify FORGE watches the layer they were never pointed at — and then feeds what it finds back into the stack you already run, across 17 SIEM platforms. You don't replace your existing controls. You make them see what they were blind to.
How does your system deploy?
Through several protection points, and the right combination depends on where your agents actually run: an endpoint agent, a browser extension for AI used in the browser, a proxy for CLI-based AI tools, and host probes for discovery.
Some teams start with discovery only and add enforcement once they've seen what turns up. Others go straight to inline policy. Worth a conversation rather than a checkbox — tell us about your environment and we'll map it out with you.
You never agreed to be training data
Every photo you post, every review you write, every message you send is feeding a model somewhere. You weren't asked. You weren't paid. And there's no obvious way to say no.
Privify SHIELD is being built to change that — a single place to see who's taking your data, opt out where you can, and get paid when you choose to share it.
AI is moving faster than governance. We are closing that gap.
Enterprises are deploying hundreds of AI agents with no visibility into what they do, who they talk to, or what data they handle. Individuals are training AI models with their most personal data without knowing it. Privify builds the infrastructure layer that makes both of these problems solvable.
See what's already running in your environment
Most teams are surprised by what turns up in the first scan. We'll walk you through a live deployment on your infrastructure.