# create an isolated microVM$ sandbox create demo --image ubuntu:24.04→ demo · running # run code inside it$ sandbox run demo -- python3 solve.py→ done · exit 0 # hand it to a coding agent$ sandbox claude demo
Isolation, control, and audit — in one boundary.
Firecracker microVM per sandbox
A real hardware-virtualized kernel boundary, not a shared-kernel container. Untrusted, AI-generated code stays contained.
Fine-grained egress policy
Control outbound traffic per project by IP/CIDR, port, protocol, direction, and domain. Default-deny as the baseline.
Built-in audit & logs
Structured logs, a per-sandbox timeline, and one request ID across edge, control plane, and workers. Know who ran what.
Self-host & BYOC
Run the whole platform in your own cloud or on-prem, or the data plane in your subscription. Keep code and data in your boundary.
Snapshots & fast wake
Persistent sandboxes, an incremental Image Store, and snapshot-based wake for services keep cold starts short and state durable.
Multi-tenant by design
Projects, scoped API keys, per-project quotas, and network policies isolate teams and tenants on a shared, managed cluster.
The sandbox boundary is the permission boundary.
Your app declares a verified principal. GX Sandbox runs the agent with exactly that user’s permissions, gates every outbound connection, and streams a durable audit trail.
- Runs the agent with the user’s permissions
- Gates every outbound connection
- Streams a durable audit trail
// drive Claude Code from your appawait using claude = await sb.claude({ anthropicApiKey: process.env.ANTHROPIC_API_KEY,})for await (const ev of claude.turn("Fix the failing test and commit")) { if (ev.type === "result") console.log(ev.result)} // or OpenAI Codex — same one-call surfaceawait using codex = await sb.codex({ version: "0.139.0", apiKey: process.env.OPENAI_API_KEY,})for await (const ev of codex.turn("Refactor src/parse.ts and add tests")) { if (ev.method === "item/completed") console.log(ev.params)}
Claude Code & Codex, built into your product.
Don’t just run code — run the coding agents themselves. GX Sandbox starts Claude Code or OpenAI Codex inside an isolated microVM, and your app drives the session programmatically: stream every event, gate every approval, resume any session.
- One SDK call opens an agent session inside the sandbox
- Stream agent messages, tool calls, and file edits as typed events
- Approve or decline commands and file changes from your own code
- Resume sessions and read back full transcripts
- Same boundary: egress policy and audit apply to the agent too
Drive it from your first line of code.
Create sandboxes, run commands, move files, forward ports, and deploy services — from the REST API, the Python and TypeScript SDKs, the CLI, or VS Code Remote-SSH.
- REST API + Python & TypeScript SDKs + CLI
- Commands, files, ports, processes, metadata
- Deploy long-running services with a stable URL
- SSH & VS Code Remote-SSH into any sandbox
# create a sandbox — REST, SDK, or CLI$ curl -X POST $SANDBOX_API_URL/api/sandboxes \ -H "Authorization: Bearer $SANDBOX_API_KEY" \ -d '{"alias":"demo"}'→ {"sandbox_id":"sbx_…","state":"running"} # or with the TypeScript SDKimport { SandboxClient } from "@generativex/sandbox-sdk"const client = new SandboxClient()const sb = await client.sandboxes.create({ alias: "demo" })const out = await sb.run("python3 solve.py")
Market-rate usage. Governance when you scale.
$0.0504 / vCPU-hr · $0.0162 / GB-hr
billed per second
$50 one-time credit, 1–2 concurrent sandboxes.
For individuals. Usage credit included, 10 concurrent.
SSO/RBAC, 90-day audit, egress policies, priority support.
WORM audit, SCIM, data residency, SLA, dedicated support.
The isolation and control other sandboxes leave out.
Same market-rate usage pricing as E2B and Daytona — plus a stronger isolation model, fine-grained egress, built-in audit, and the option to self-host.
Stronger isolation by default
Firecracker microVM per sandbox — vs shared-kernel containers or a managed runtime you can’t inspect.
Self-host, or keep data in your cloud
Most managed sandboxes are cloud-only. GX Sandbox self-hosts or runs its data plane in your subscription.
Audit & egress control included
Fine-grained egress policy and a built-in audit trail — the governance regulated teams actually need.
AI agent platforms
Give each agent run its own isolated microVM with controlled egress and a full audit trail.
Code interpreters
Execute AI-generated code safely — data science, build-and-run, and long-lived devboxes.
CI & ephemeral compute
Spin up disposable environments per job, then reap them. Persistent state when you want it.
Regulated enterprises
Self-host or BYOC with egress control and audit, so AI features meet data-residency needs.
How is this different from a laptop or a plain container?
Each sandbox is a Firecracker microVM — a hardware-virtualized boundary, stronger than a shared-kernel container. Agents keep full power (bash, Python, Node.js, OCI containers inside) without putting your host, other tenants, or your network at risk.
Can I use my own toolchain and container images?
Yes. Launch sandboxes from custom images, run OCI containers inside a sandbox, and deploy long-running services from an OCI image with a stable URL.
Can I run Claude Code or Codex inside a sandbox?
Yes — first-class. One SDK call starts Claude Code or OpenAI Codex inside the microVM, and your app drives the session over a WebSocket: stream events, handle approvals, resume sessions, and read transcripts. Interactive use works too, with `sandbox claude <id>` from the CLI.
Can I embed it in my own app or agent?
Yes. Drive everything — create sandboxes, run commands, manage files, forward ports, deploy services — from the REST API and the Python / TypeScript SDKs, or the CLI.
Can I self-host or keep data in my own cloud?
Yes. Enterprise supports full self-host and BYOC (the data plane runs in your own cloud), so code and data stay inside your boundary. This is the core reason regulated teams choose GX Sandbox.
How does pricing work?
Usage is billed per second at market-rate vCPU and memory prices, with a free tier to start. Teams add per-seat governance; Enterprise is a custom annual contract. See the pricing page for details.
Run AI code at full speed — isolated, governed, and auditable.