See What Your AI is
Actually Doing

AI agents now execute code.

Run terminals.

Modify repositories.

Access your system.

Most of it is invisible.

We make it visible.

Try Free Learn More
agent-session-04a
$ npm install axios express dotenv
added 58 packages in 3.2s
$ git checkout -b feature/auth-layer
Switched to new branch 'feature/auth-layer'
$ cat > src/middleware/auth.js
...
$ _

What just happened?

3 packages installed • 12 files modified • 1 outbound connection

You saw none of it.

Agentic Usage ● LIVE
agent-session-04a cursor-copilot 2m ago
5 cmds 12 files 1 external
npm install axios express dotenv
+3 packages · 58 files added
2m 14s
git checkout -b feature/auth-layer
Branch created
2m 08s
src/middleware/auth.js
File created · 47 lines
1m 55s
12 files modified across 4 directories
Bulk write detected
1m 41s
Outbound connection: api.external-service.io:443
External transmission · HTTPS
1m 30s
3 packages installed
axios, express, dotenv
Branch created
feature/auth-layer
12 files modified
Bulk write across 4 dirs
External connection detected
api.external-service.io:443
|

Built for Every AI That Touches Your Machine

AI agents don’t live in one place. They operate across your entire machine.

Cursor, Windsurf, IDE copilots that execute

These tools don't just autocomplete anymore. They open terminals. Install packages. Rewrite directories. Run git commands.

You see the result.
You don't see the execution trail.

We provide:

  • ◆ Every command executed
  • ◆ Every file modified
  • ◆ Every dependency installed
  • ◆ Every background process
  • ◆ Every outbound network call

Deep terminal and file-system visibility — without plugins.

Autonomous, multi-step operators

These systems plan tasks, break them into steps, retry on failure, and run for extended sessions.

The risk isn't a bad suggestion.
It's invisible autonomy.

We provide:

  • ◆ Full session replay
  • ◆ Step-by-step action chains
  • ◆ Process and job lineage
  • ◆ Loop + retry detection
  • ◆ API and network tracing

If an agent touches it, you see it.

System-level AI operators

These agents operate your OS like a user. Open applications. Read documents. Move data across tools.

This is system-level execution.

We provide:

  • ◆ Application launch tracking
  • ◆ Cross-app activity visibility
  • ◆ Sensitive file access alerts
  • ◆ External transmission logging
  • ◆ Clear session boundaries

OS-level observability — purpose-built for AI.

Every Platform Shift Adds a Visibility Layer

Cloud → Observability
Containers → Runtime Security
CI/CD → Pipeline Monitoring
AI Agents → ?

There is no execution visibility layer for AI agents.
That's the gap.

Designed for the AI-Native Stack

Works with
Cursor Windsurf Claude Codex Antigravity OpenClaw
✓ Local-first by default
✓ Minimal performance overhead
✓ No IDE plugins required
✓ Works across tools
✓ Enterprise audit-ready

Security without friction.

Why This Matters

AI agents now have real permissions.

Access secrets

Modify production code

Spawn persistent processes

Transmit data externally

And most teams are running them blind.

That's acceptable in a demo.

It's unacceptable in production.

The Shift Is Already Happening

AI is no longer assistive.
It's operational.

Developers are deploying tools that:

  • Run shell commands
  • Install dependencies
  • Rewrite large codebases
  • Execute multi-step workflows
  • Control operating systems

We've moved from

"AI suggests"

to

"AI executes."

The control layer hasn't caught up.

What You Always See

Files

Opened, modified, deleted

Commands

Shell, scripts, git

Processes

Spawned, chained, persisted

Network

Outbound calls + destinations

Attribution

Which agent, which session, which time

Permissions

Secrets accessed, env vars read

Complete execution transparency.

The Risk Curve

AI Capability
Execution Power
Adoption
Visibility

Every month without guardrails increases the surface area of invisible automation inside your company.

The longer you wait, the harder it becomes to audit what has already happened.

Who This Is For

  • AI-native startups deploying agents in real workflows.
  • Security teams evaluating AI rollout.
  • Engineering orgs that want control without slowing down.

If AI can execute on your machine,
you should be able to see it.

Why Now

AI agents are moving from novelty to infrastructure.

  • Coding agents are shipping into IDEs.
  • Agentic workflows are entering production.
  • Computer-use systems are crossing into enterprise environments.

The companies that add visibility early will scale safely.

The ones that don't will discover blind spots the hard way.

Ready to see what your AI is really doing?

Try Free Request Early Access