What is AgentSphere
AgentSphere is an AI-native cloud infrastructure that provides secure cloud sandboxes for executing AI agent code. It is designed as an alternative to E2B and offers a secure environment for Large Language Models (LLMs) to execute code and handle files.
How to use AgentSphere
While the webpage does not provide a step-by-step guide, it implies usage by connecting MCP clients to isolated cloud sandboxes for code execution and file handling.
Features of AgentSphere
- AI-Driven Data Analysis: Enables secure processing of internal datasets with access control and output tracing.
- Generative Data Visualization: Renders AI-generated dashboards and visuals within isolated, auditable environments.
- Secure Virtual Desktop Agents: Grants agents access to browser or UI automation in isolated desktop-like environments.
- Stateful Agents & Multi-Stage Tasks: Supports complex workflows with persistent memory and event-triggered reactivation.
- DevOps, GitOps & CI Integration: Allows agents to interact with Git, execute pipelines, and automate deployments.
- LLM Evaluation & Fine-Tuning: Facilitates evaluation of code generation, prompt testing, and assessment of autonomous behavior.
- Instant Startup: Offers cold-start latency as low as 100ms with in-region sandbox deployment.
- Enterprise-Grade Security: Utilizes lightweight VMs (e.g., Firecracker) with SOC2 and GDPR compliance for running untrusted AI code.
- Stateful Execution: Supports long-running tasks with snapshot recovery, storage persistence, and streaming output.
- MCP-Powered Cloud Sandboxes: Connects MCP clients to run code and process files securely.
- Private Deployment: Allows deployment in own cloud environments (AWS, GCP, on-prem) with compliance and network isolation.
- Model & Language Agnostic: Supports any LLM or runtime, including Python and TypeScript.
Use Cases of AgentSphere
- Secure Enterprise Code Execution: Safely run LLM-generated code in sensitive sectors like finance, healthcare, or government.
- Agent-Driven DevOps Automation: Deploy self-healing agents for CI/CD flow automation.
- Large-Scale Model Evaluation: Scale evaluation benchmarks with isolated and reproducible sandboxes.
- Agent Runtime Core for AI Products: Use the sandbox as the execution backbone for AI-native applications, copilots, or autonomous systems.
Pricing
Information regarding pricing, plans, or tiers is not available on the webpage.
FAQ
Information regarding FAQs is not available on the webpage.
