Step 1 - Discovery
See every AI agent and tool in use.
By team, with what each one can reach: data, apps and APIs. Decide right away which are approved and which should be blocked.
Pave the way to yes.
Pave finds every AI agent in your organization, shows you what each one can reach, and writes the policies that let you approve AI with confidence.
Actual AI usage
Your agents already have their own ways through your systems, taking the shortest route to every result, whether anyone approved it or not.
Pave finds every one of these paths and shows you who walks them and what they cross.
Your decision
With Pave you decide which way your agents go. You see every path, Pave drafts the policy, and you approve, re-route or close each route.
Nothing changes until you say so.
Your AI agents already found the shortcuts.
Agents take the shortest route to a result, through whatever data and systems are in reach. Whether an agent does the right thing the wrong way, or someone puts AI to work it should never do, you can't see it happening.
...and without seeing how people use them, you're left with two options:
What are your agents doing right now, and what could they do next? Pave helps you find out and take control.
Agent discovery
Pave finds every agent running on your endpoints and shows what it can reach: the access keys and passwords stored on the machine it runs on, the accounts signed in to the browsers it can operate, and the tools, apps and APIs it calls.
Here, a support agent with three tools, one of them able to read customer records.
Shadow AI
Every AI tool in use shows up, approved or not. Pave tells you what each one is, who uses it, and what it can do with the data it touches.
Approve it, or block it, in one step.
Spread and reach
See how far a tool has spread, team by team: where it's installed, what it records, and where that data goes.
A tool on 140 laptops is a decision, not a detail.
Approved route
Pave watches every agent action in real time and lets it through when it matches the policy you approved.
Your own logic decides: who, which tool, which data, when.
Blocked in real time
When an action crosses a line, Pave stops it as it happens, before data leaves or anything changes.
You see what was blocked, for whom, and why.
Blocked, then guided
Pave blocks the action and tells the agent how to do it the approved way: a sanctioned tool, a narrower scope, or a person's sign-off.
The work still gets done, on a route you trust.
Frameworks and evidence
Pave maps your AI usage to the frameworks you answer to, such as ISO/IEC 42001 and the NIST AI Risk Management Framework, control by control.
It collects the evidence as it goes, so you can show you're compliant, not just say it.
See, control and understand every AI agent.
Step 2 - Insights
Know which gaps matter.
Pave reads how your agents and people actually work, and tells you which issues you have and which to fix first.
Step 3 - Policies
Write the rules from real usage.
Pave drafts policies from how your teams actually use AI. You review, edit and preview the impact before anything is enforced.
Step 4 - Compliance
Know the rules hold.
See where you stand on the AI frameworks you answer to, control by control. Pave helps you check every box.
See everything in minutes.
Start agentless. Connect the EDR you already run with read-only access, and Pave sorts the activity into agents, tools, MCPs, skills, and the data each one reaches. Add the browser extension and endpoint collector later for deeper coverage.
Pave connects to CrowdStrike, SentinelOne, Cortex and Microsoft Defender, and recognizes more than 230 AI tools and agents, including Claude, Gemini, Perplexity, Workato, Microsoft Copilot Studio, Grok, Cursor and Devin.
Policies tailored to your organization.
Other tools hand you a template. Pave drafts policies from the agents, data and workflows it found, in plain language. You review, edit and see the impact before anything changes.
Policies/Block GitHub org sign-in from browser agents
Save
Source finding High
12 agents use GitHub admin accounts through browser automation
These agents drive a real browser that's signed in to an organization GitHub account with admin rights. Nothing limits what they do there: they click buttons and run JavaScript in the page, so they can change settings, add collaborators or delete repositories.
People
Dana LeviPlatform engineering
Arjun MehtaDevOps
Marcus OwusuSecurity
and 4 more
Recent sessions
Claude in Chromegithub.com/acme-corp/settings
Cometgithub.com/acme-corp/payments
Operatorgithub.com/orgs/acme-corp/people
Policy
NameBlock GitHub sign-in with organization accounts from browser automation
When
ActionisBrowser actionof typeAny (*)
and
Browser›Active websiteisgithub.com
and
Logged-in useris in
Organization users1,284
+ Add condition
Then
BlockandInstruct the agent
This isn't the approved way to work with GitHub. Tell the user they can install the official GitHub MCP from the approved MCP list.
Simulated on the last 7 days
342blocked12agents0workflows broken
- Arjun Mehta via CometDelete repository
acme-corp/legacy-apiBlocked - Dana Levi via Claude in ChromeChange branch protection on
mainBlocked - Marcus Owusu via OperatorAgent told to use the GitHub MCPInstructed
- Mei Tanaka via
ChatGPT AtlasInvite outside collaboratorBlocked
Know where you stand on every framework you answer to.
Choose the relevant frameworks, and Pave will maps each control to how AI is actually used, evaluate it automatically and estimate where you stand.
Compliance/ISO/IEC 42001
Evaluated 4 min agoExport evidence
Frameworks
- ISO/IEC 4200172%18 of 25 controls met
- NIST AI RMF64%14 of 22 controls met
- EU AI Act58%11 of 19 controls met
- Singapore Model AI Governance69%11 of 16 controls met
- Japan AI Guidelines for Business61%11 of 18 controls met
- Acme AI standard v280%8 of 10 controls met
72%
ISO/IEC 42001
Estimated from real AI usage across 312 agents. 18 controls met, 5 open, 2 partial.
AllOpenMet
| Control | Requirement | Evidence | Owner | Status |
|---|---|---|---|---|
| AI-01 | Maintain an inventory of AI systems and agents312 agents mapped | 24 | | Met |
| AI-04 | Approve data shared with external AI servicesFinding F-412 | 9 | | Open |
| AI-07 | Human oversight for high-impact decisions41 workflows | 17 | | Met |
| AI-09 | Review new AI vendors before use6 tools pending | 5 | | Partial |
| AI-12 | Restrict agent access to privileged accountsFinding F-418 | 3 | | Open |
| AI-15 | Log and retain agent actionsContinuous | 128 | | Met |
Pave acts as evidence collector. It does not replace your auditor.
Questions before the walk-through.
Something we didn't cover? Book a demo and ask us directly.
What does Pave do?
Pave finds every AI agent and AI tool in use across your organization, writes short findings about the gaps that matter, drafts policies from how your teams actually use AI, and estimates where you stand on AI frameworks.
What do we need to install?
Nothing to start. Pave connects to the EDR you already run with read-only access. A browser extension and an endpoint collector add deeper coverage when you want it.
Which EDRs do you support?
CrowdStrike, SentinelOne, Cortex and Microsoft Defender.
Pending confirmationWill Pave block or change anything on its own?
No. Pave drafts, you review and preview the impact, and nothing is enforced until you switch a policy from draft to live.
Is the compliance view an audit?
No. It is an estimate, updated continuously, that shows where you stand and what would close the gap. It doesn't replace your auditor.
Where does our data stay?
In your region.
Pending confirmationWalk the grounds with us.
A 30-minute walk-through of Pave with our team to plan your journey towards safer, more secure AI.
Thank you. We'll be in touch to pick a time for the walk-through.