Secure sandboxes for
AI agents
Deploy and run AI agents in isolated environments with automatic security policies, resource limits, and real-time monitoring. No infrastructure setup required.
$ sandboxkit deploy agent.py --limits cpu=2,mem=4g
⠿ Provisioning sandbox...
✓ Sandbox ready in 12.4s
ID: sbx_a1b2c3d4
Status: running
CPU: 2 cores
Memory: 4 GB
Policy: default (no-egress, ro-fs)
$ sandboxkit logs sbx_a1b2c3d4 --follow
[2026-03-06 08:12:01] Agent started
[2026-03-06 08:12:02] Loading model weights...
[2026-03-06 08:12:05] Processing task queue
[2026-03-06 08:12:06] ✓ Task #1 completed (1.2s)How it works
Upload Code
Paste your agent code or upload a file. We support Python, Node.js, and any Docker image.
Configure & Launch
Set resource limits and security policies (or use smart defaults). Sandbox is ready in under 30 seconds.
Monitor & Debug
Watch live logs, metrics, and SSH into your sandbox. Stop, pause, or delete anytime.
Built for agent safety
Everything you need to deploy agents with confidence. Security and observability out of the box.
Automatic Isolation
Every agent runs in its own sandboxed container with gVisor-level isolation. No shared kernel, no escape.
Resource Limits
Set per-agent CPU, memory, GPU, and cost caps with simple sliders. Never get a surprise bill.
Security Policies
Built-in policies: no network egress, restricted filesystem, blocked syscalls. Customize per agent.
Agent Monitoring
Real-time dashboards for token usage, API calls, execution time, and resource consumption.
Auto Teardown
Sandboxes automatically shut down after inactivity. No orphaned containers wasting resources.
Audit Logs
Full audit trail of every action, API call, and file access for compliance and debugging.
Simple, transparent pricing
Start free with 50 agent-hours per month. Pay only for what you use.
Ready to sandbox your agents?
Get started in under a minute. No credit card required.
Start Building →