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Treadstone

Updated July 24, 2026

Overview / Description

Treadstone offers an agent-native sandbox platform designed for running AI agents through longer-duration tasks in isolated environments. This platform allows developers and researchers to execute complex AI workflows securely, preventing interference with external systems. Each Treadstone sandbox functions as an all-in-one runtime, providing agents with capabilities like code execution, a command-line shell, a dedicated file system, and browser-facing surfaces. Agents can also treat these sandboxes as callable tools, extending their operational reach on demand.

The platform supports scenarios where AI agents need to maintain long-running state or interact with various system components without compromising stability. For instance, an AI agent could use Treadstone to autonomously browse the web, scrape data, process it with custom code, and store results, all within its confined, dedicated space. Treadstone is open source and self-hostable, built on Kubernetes, making it a flexible choice for those who prefer to manage their own infrastructure. It provides a reliable and controlled environment for developing, testing, and deploying sophisticated AI agents that require extensive op

Used For

Developers and researchers use Treadstone to run AI agents on long-duration tasks in isolated, all-in-one sandboxes with code execution, a shell, files, and a browser.

Pricing

Free

$0/month

Metered free tier; the platform is also open source and self-hostable on your own Kubernetes infrastructure.

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Paid

Free

Usage-metered paid plans beyond the free tier — see the website for current pricing.

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Pros & Cons

Pros

• Agent-native sandboxes for running AI agents on long-duration tasks in isolation • Each sandbox is an all-in-one runtime: code execution, shell, file system, and browser surfaces • Agents can treat sandboxes as callable tools to extend their reach • Open source and self-hostable, built on Kubernetes • Control plane via CLI, Python SDK, or REST, with a metered free tier

Cons

• Self-hosting on Kubernetes requires infrastructure and DevOps knowledge • Aimed at developers and researchers rather than non-technical users • Running long-lived sandboxes consumes compute resources you manage

Questions & Answers

Alternatives

E2B, Daytona, Modal, Runloop

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Treadstone | AI Tools Directory