Seamlessly connect your MCP clients to isolated cloud sandboxes — purpose-built to execute AI-generated code and handle files securely.
Enable agents to securely process internal datasets for insights, with built-in access control and output tracing.
Render AI-generated dashboards and visuals, inside isolated and auditable environments.
Grant agents access to browser or UI automation inside isolated desktop-like environments for testing and simulation.
Enable agents to securely process internal datasets for insights, with built-in access control and output tracing.
Render AI-generated dashboards and visuals, inside isolated and auditable environments.
Grant agents access to browser or UI automation inside isolated desktop-like environments for testing and simulation.
Enable agents to securely process internal datasets for insights, with built-in access control and output tracing.
Render AI-generated dashboards and visuals, inside isolated and auditable environments.
Grant agents access to browser or UI automation inside isolated desktop-like environments for testing and simulation.
Enable agents to securely process internal datasets for insights, with built-in access control and output tracing.
Render AI-generated dashboards and visuals, inside isolated and auditable environments.
Grant agents access to browser or UI automation inside isolated desktop-like environments for testing and simulation.
Support complex workflows across multiple agent steps, with persistent memory and event-triggered reactivation.
Let agents interact with Git, execute pipelines, and automate deployment in controlled, reviewable sessions.
Evaluate code generation quality, test prompts, and assess autonomous behavior — at scale and in isolation.
Support complex workflows across multiple agent steps, with persistent memory and event-triggered reactivation.
Let agents interact with Git, execute pipelines, and automate deployment in controlled, reviewable sessions.
Evaluate code generation quality, test prompts, and assess autonomous behavior — at scale and in isolation.
Support complex workflows across multiple agent steps, with persistent memory and event-triggered reactivation.
Let agents interact with Git, execute pipelines, and automate deployment in controlled, reviewable sessions.
Evaluate code generation quality, test prompts, and assess autonomous behavior — at scale and in isolation.
Support complex workflows across multiple agent steps, with persistent memory and event-triggered reactivation.
Let agents interact with Git, execute pipelines, and automate deployment in controlled, reviewable sessions.
Evaluate code generation quality, test prompts, and assess autonomous behavior — at scale and in isolation.
Key Features
Security, Speed, and Scale — All in One Platform
✔ Preflight checks.✔ Verifying framework. Found Next.js.✔ Validating Tailwind CSS.✔ Validating import alias.✔ Writing components.json.✔ Checking registry.✔ Updating tailwind.config.ts✔ Updating app/globals.css✔ Installing dependencies.ℹ Updated 1 file:- lib/utils.tsInstant Startup
Cold-start latency as low as 100ms. Sandboxes are deployed in-region for maximum speed.
Enterprise-Grade Security
Backed by lightweight VMs (e.g. Firecracker) with SOC2 and GDPR compliance built-in — battle-tested for running untrusted AI code.
Stateful Execution
Support for long-running tasks with snapshot recovery, storage persistence, and streaming output.
MCP-Powered Cloud Sandboxes
Connect with your MCP clients to run code and process files in a secure cloud sandbox.
Private Deployment
Deploy in your own cloud (AWS, GCP, on-prem) with full compliance and network isolation.
Model & Language Agnostic
Supports any LLM or runtime — from Python to TypeScript, from codegen to control agents.
Use Cases for Enterprise AI
Built for AI-Native Infrastructure. Trusted by Enterprise.
Secure Enterprise Code Execution
Enable LLMs to write and run code safely in finance, healthcare, or government scenarios.
Agent-Driven DevOps Automation
Deploy self-healing, self-executing agents that operate in secure environments across your CI/CD flow.
Large-Scale Model Evaluation
Scale your eval benchmarks with isolated, reproducible sandboxes and real-time monitoring.
Agent Runtime Core for AI Products
Use the sandbox as the execution backbone for your AI-native apps, copilots, or autonomous systems.
import{ Swarm, Agent }from'ai-agent-sdk';const client = new Swarm()const transferToAgentB = (): Agent => { return agentB;};const agentA = new Agent({ name: "Agent A", instructions: "You are a helpful agent.", functions: [transferToAgentB],});const agentB = new Agent({ name: "Agent B", instructions: "Only speak in Haikus.",});AgentSphere
Why This Platform?