Alternatives to CreateOS Sandbox

Sandbox0 serves as an Apache-2.0 compliant runtime environment designed for executing AI agents and services that handle untrusted code over extended periods. It offers secure, isolated Linux environments capable of command execution, maintaining stateful contexts, performing file operations, facilitating SSH access, managing supervised sessions, and enforcing network controls. The architecture allows sandboxes to preserve a durable writable RootFS through successful pause-and-resume checkpoints, alongside features such as snapshots, restoring capabilities, and forks that enable the creation of reusable workspaces. Developers can leverage the Python, JavaScript/TypeScript, and Go SDKs, along with an HTTP API and the s0 CLI, to efficiently create and manage their sandboxes. For those seeking hosted solutions, Sandbox0 Cloud offers convenient access, while organizations have the option to self-host the runtime on dedicated Nomad infrastructure. By default, pausing the system preserves the filesystem state but does not maintain live process memory or external connections, although experimental memory recovery is available, contingent upon the necessary deployment infrastructure. This multi-faceted approach ensures flexibility and security for various user needs when working with AI technologies.

Codex is an advanced AI coding assistant from OpenAI that helps developers streamline the entire software development process from start to finish. It functions as a powerful pair programmer capable of understanding repositories, writing code, and generating production-ready pull requests. The platform supports complex workflows, including debugging, refactoring, testing, and code reviews, all within a unified environment. One of its standout features is computer use, which allows Codex to operate your computer directly by seeing the screen, clicking, and typing within applications. This capability enables it to interact with tools and software that lack direct integrations or APIs. Codex also includes an in-app browser, allowing developers to iterate on web applications and provide precise instructions directly on live pages. It integrates with a wide range of tools and plugins, enhancing its ability to gather context and take action across workflows. The platform supports multi-agent collaboration, enabling parallel work across projects to accelerate development timelines. Codex also offers automation features that allow it to schedule and complete recurring tasks without manual input. With memory capabilities, it can remember preferences and past actions to improve future performance. Overall, Codex delivers a comprehensive AI-powered solution that combines coding, automation, and real-world computer interaction to boost developer efficiency.

Agent Substrate serves as an open-source runtime that facilitates the operation of isolated, stateful agent and code-execution sandboxes within Kubernetes environments. It effectively manages the lifecycle of actors and workers, allocates active workloads to a common pool of available resources, and has the ability to pause idle sandboxes while maintaining their memory and filesystem states for potential future use. Utilizing gVisor or Cloud Hypervisor microVM for isolation, these sandboxes incorporate unique identity and networking controls for each actor. This platform is specifically tailored for infrastructure and platform teams who are developing services for hosting agents, creating coding environments, and handling other tasks that may involve untrusted or sporadic execution. The primary framework is designed to be portable across Kubernetes, with Google Cloud providing specialized deployment tools optimized for GKE. Additionally, users can implement optional Filestore agent volumes to ensure that workspaces remain intact and accessible through suspension and resumption cycles, enhancing the reliability of the development environment. This versatility makes Agent Substrate an essential tool for modern cloud-native applications.

Agent Compute Engine is a fully managed compute service offered by Google Cloud that creates execution environments specifically for AI agents. Each agent operates within its own hardware-isolated microVM, complete with a dedicated guest kernel and root-level management capabilities. Users can benefit from features such as rapid startup, pausing, checkpointing, creating snapshots, and resuming workflows. Persistent workspaces are available to maintain agent files and context throughout different sessions, and the platform utilizes copy-on-write memory sharing to enable parallel environments derived from shared images. Agents have the capability to execute code, run shell commands, and perform browser actions within secure sandboxes, with carefully regulated access to enterprise data through Google Cloud's networking and identity frameworks. Developers have the flexibility to customize environment images, manage identity protocols, control network access, and oversee the lifecycle of their agents, all while Google takes care of the underlying compute infrastructure. The platform is particularly well-suited for interactive assistants, coding agents, browser-based tasks, and extensive evaluation and reinforcement learning tasks, showcasing its versatility and efficiency in handling a wide range of AI applications. This comprehensive management allows developers to focus on building and optimizing their AI solutions without the burden of infrastructure concerns.

Sprites by Fly.io is a stateful sandbox environment platform designed to run arbitrary code in isolated Linux computers. Each Sprite is a hardware-isolated execution environment that can persist across runs, making it useful for AI agents, uploaded binaries, developer tools, and application workloads. The platform is built around checkpoint and restore, allowing workloads to pause, resume, and keep state instead of rebuilding the environment repeatedly. Sprites provide a fast NVMe filesystem that syncs continuously to durable external object storage. This tiered storage approach gives users compatibility with normal Linux filesystem behavior while only charging for the data they actually use. Developers can start with the Sprites CLI by logging in, creating a Sprite, executing commands, and connecting to the console. The platform also supports REST API access and SDKs for JavaScript, Go, Elixir, and Python. Pricing is usage-based across CPU time, memory time, hot storage, and cold storage. By combining sandbox VMs, persistent filesystems, checkpointing, APIs, network policy, and pay-as-you-go pricing, Sprites gives developers a practical runtime for AI agents and untrusted code execution.

Ovrin serves as a cloud-based computing platform tailored for developers who are creating AI agents and other software that necessitates execution within regulated environments. Users can leverage a REST API, alongside Python and TypeScript SDKs, or an MCP server to establish temporary Linux sandboxes, execute shell commands and stateful code, handle file management, configure scoped API keys, and access execution results. The platform features preconfigured setups such as Claude Code, OpenAI Codex, Gemini CLI, and DeepSeek Harness, while browser workflows are compatible with Chrome and Playwright. Additionally, it provides functionalities like persistent memory, controls for sandbox lifecycles, usage tracking, and limits on concurrency. Common applications of Ovrin include executing coding agents, automating browser tasks, and running code generated by models. Notably, Ovrin offers a free tier alongside several paid options that provide increased concurrency and usage-based compute costs. Overall, the platform aims to streamline the development process for AI solutions by providing a robust and flexible environment.

AgentComputer is an innovative cloud infrastructure platform tailored for operating AI agents in secure and fully operational virtual spaces. It offers "cloud computers" as lightweight Ubuntu-based sandboxes that can be set up in less than a second, enabling developers to swiftly create, access, and control their environments through a command-line interface. These virtual spaces come with persistent storage, ensuring that any installed applications, files, or settings are preserved even after restarts, which facilitates ongoing and consistent workflows. The platform is founded on an agent-first design, allowing AI agents to perform tasks directly within these spaces via SSH, which reduces the barriers between issuing commands and executing them. Furthermore, it features a built-in AI harness that accommodates various agents, including Claude, Codex, and additional coding assistants, thus promoting seamless collaborative multi-agent operations within the same environment. This integration not only enhances productivity but also streamlines the development process for AI-driven projects.

Daytona is a modern cloud-based runtime designed to let developers and AI systems launch secure, isolated workspaces for any project in seconds. Each environment runs inside a lightweight microVM that includes full Linux support, networking, and persistent storage. Through Daytona’s Python and TypeScript SDKs, users can automate code execution, file uploads, and environment lifecycle management directly from their apps. By shifting development to the cloud, Daytona eliminates the need for complex local setups and enables fully reproducible sandboxes accessible via SSH, APIs, or live preview URLs. Built for speed, automation, and scalability, it supports everything from simple prototypes to production-grade agent workloads.

ComputeSDK is an open-source toolkit available at no cost, specifically crafted to empower developers to execute external or user-generated code within their applications through a cohesive and standardized interface. With a TypeScript-native API, it simplifies the process by seamlessly integrating various compute providers, enabling developers to transition between platforms such as E2B, Vercel, Daytona, Modal, and others while keeping their primary codebase intact. This toolkit is constructed around isolated sandbox environments, which guarantee that the executed code operates securely without affecting the host infrastructure, thereby making it ideal for applications that necessitate controlled execution of potentially untrusted code. Additionally, ComputeSDK offers essential functionalities, including the execution of code and shell commands, filesystem management, the ability to create and dismantle sandboxes, and compatibility with modern web frameworks like Next.js, Nuxt, and SvelteKit. Furthermore, its design ensures that developers can focus on building robust applications without worrying about security vulnerabilities associated with running external code.

Runx is a command-line and open-source runtime tool designed for the creation, discovery, and execution of governed skills tailored for AI agents. It allows developers to establish defined workflows, assign specific permissions and credentials, and execute skills on their own provider accounts locally. The system is capable of pausing runs for necessary approvals or inputs, and it retains a signed receipt that can be reviewed and validated. Skills can be sourced from a public registry and integrated with various compatible agents, including Claude Code, Cursor, and Codex. Additionally, an optional hosted service can facilitate managed OAuth connections, scoped grants, API-based run submissions and inspections, handling of approvals, and notarization of receipts. The command-line interface can function in both local and self-hosted setups. Runx is specifically designed for developers and platform teams focused on building and managing AI-agent workflows that require clear authority boundaries along with auditable execution processes. Furthermore, its capabilities support enhanced collaboration and security measures for the development of AI-driven solutions.

Composio is an advanced platform designed to empower AI agents with the ability to execute real-world tasks across multiple applications. It connects agents to over 1,000 tools, enabling seamless interaction with platforms like Slack, Gmail, Notion, and GitHub. The platform automates key processes such as authentication, permission management, and tool execution, reducing development complexity. Composio uses intelligent tool selection to match user intent with the appropriate actions, improving accuracy and efficiency. It also provides secure sandbox environments where workflows can run safely and independently. Developers can create multi-step workflows and automate complex tasks with minimal setup. The platform supports parallel execution, allowing agents to perform multiple operations simultaneously. Composio is model-agnostic, enabling flexibility in choosing AI models without reworking integrations. Its context-aware sessions ensure agents maintain continuity across tasks and interactions. Overall, Composio transforms AI agents into fully functional systems capable of executing real-world workflows.

The Agents API enables developers to create and operate cloud agents utilizing the same framework and infrastructure that supports Codex, all under the management of OpenAI. By making a simple API request, users can establish a fully operational agent by defining the specific task, model, tools, and environment, with OpenAI overseeing the agent's infrastructure. Developers have the flexibility to select where their agents are deployed: whether in an OpenAI-managed sandbox, on personal servers, or via authorized sandbox partners. The OpenAI-managed sandboxes offer secure environments for agents to execute code, interact with files, utilize packages, skills, and plugins, and generate outputs. Designed for tasks that require extended operation, the API features automatic context compaction to retain pertinent information across multiple context windows within sessions. Additionally, the tool search function efficiently loads relevant definitions only as needed, while programmatic tool invocation allows agents to execute calls simultaneously, chain related tasks, and filter or merge results seamlessly in code. This comprehensive approach not only enhances efficiency but also empowers developers to create more sophisticated applications.

OpenComputer provides a cloud-based platform designed specifically for creating and launching TypeScript AI agents. Developers can customize the behavior of these agents, choose from various models and tools, and deploy them with features like persistent sessions, real-time data streaming, scheduled tasks, memory management, and version-controlled environments. Furthermore, the integration of APIs and service connections enables teams to seamlessly incorporate these agents into their applications and workflows, facilitating tasks like coding support and automated background processes. This flexibility allows for a diverse range of applications, enhancing productivity and efficiency in software development.

InstaVM offers a robust production sandbox and cloud solution designed specifically for AI agents, equipping them with immediate access to computing resources including runtime, storage, networking, secrets, and policy management. Unlike traditional sandboxes, it utilizes hardware-isolated virtual machines instead of containers, ensuring that teams can provide AI agents with secure environments that feature complete Linux filesystems, networking capabilities, package management, RESTful API access, and the ability to maintain persistent states. The platform's support for snapshots enables users to create forks of any sandbox and revert to previous states, while its persistent volumes ensure that data is retained across executions. Additionally, egress control allows teams to manage which connections can be made externally, and features like secrets injection and Vault work to safeguard sensitive information from potential prompt injections. Moreover, public URL deployments can make any port accessible on the public web, enhancing its versatility. It is specifically tailored for various agent patterns, including code interpreters, deployment agents, deep research agents, AI evaluations, reinforcement learning applications, computer usage, and vibe coding applications, making it a comprehensive tool for developers. With its innovative architecture and extensive features, InstaVM solidifies its position as a leading solution for AI-driven projects.

Firejail is a SUID application designed to enhance security by isolating untrusted programs through the use of Linux namespaces and seccomp-bpf. This tool enables a process and its child processes to maintain a distinct view of shared kernel resources, including the network stack, process table, and mount table. Developed in C with minimal dependencies, Firejail is compatible with any Linux system that operates on version 3.x of the kernel or later. Its sandboxing solution is efficient, resulting in minimal overhead. Users benefit from its simplicity, as there are no intricate configuration files to manage, no open socket connections, and no background daemons to contend with. All security mechanisms are built directly into the Linux kernel, making them accessible on any Linux machine. This combination of features makes Firejail an appealing choice for those looking to bolster their system's defenses against potential threats.

Boat delivers robust cloud-based virtual machines and persistent sandboxes specifically designed for managing long-lasting AI agents, empowering users to effortlessly create thousands of cloud instances equipped with web browsers and persistent storage while alleviating the burden of infrastructure management. Each sandbox functions as a comprehensive Ubuntu Linux virtual machine, providing SSH and SCP access, Docker compatibility, dedicated IPv4 or IPv6 addresses, a smooth 60 fps virtual desktop, and rapid disk-level forking capabilities from snapshots. Pre-installed tools such as Docker, VS Code, Chrome, Ghostty, GitHub CLI, Rust, Node.js, and Bun allow users to execute any development language, tool, or workflow seamlessly. Boat is compatible with various agents including Claude Code, Codex, and OpenCode, and it offers functionalities to prompt, observe, and manage agent environments remotely via its command-line interface, HTTP API, and SDKs available in both Python and TypeScript. Users can run commands, transfer files, and monitor agent communications, while also hosting applications accessible through public HTTPS links and utilizing integrated desktops and web browsers for enhanced productivity. This comprehensive solution not only simplifies the management of AI agents but also fosters a more efficient development experience for users across diverse projects.

Flue is an innovative agent framework designed for creating robust AI agents utilizing a customizable TypeScript environment. Developed by the creators of Astro, it incorporates a React-like hooks API for constructing agent functionalities, including persistent state, lifecycle events, various models, tools, sandboxes, subagents, skills, and MCP servers within the codebase. These agents maintain state and can be addressed via HTTP, preserving context throughout interactions and adapting their abilities as tasks evolve. Flue ensures that every session is logged in a reliable stream, allowing for the recovery of accepted tasks even after crashes, restarts, or deployments; this means that interrupted sessions can seamlessly resume, and clients can reconnect without needing to start anew. Developers have the flexibility to operate agents locally, through continuous integration, from their own backend systems, or coordinate them using platforms like Cloudflare Workflows and Inngest. The secure sandboxes allow agents to execute commands, modify files, and perform meaningful tasks, while integrated tools facilitate connections to various APIs and data sources. Flue is powered by Pi and offers compatibility with multiple LLM providers, enabling teams to select the models that best suit their needs. Ultimately, this framework empowers developers to create versatile AI agents that can adapt to changing requirements and environments.

Cloudflare has unveiled VibeSDK, an open-source, full-stack vibe coding platform that can be deployed with a single click to facilitate the creation of AI-driven application builders. This innovative platform seamlessly integrates LLMs through an AI Gateway, enabling real-time code generation, debugging, and iteration. It also offers secure, isolated sandboxes for each user session, allowing for the safe execution of untrusted code. Users can benefit from live previews and streaming logs, which aid in testing and troubleshooting during the development process. Additionally, VibeSDK employs worker-based platforms to ensure that each generated application can be deployed at scale while maintaining tenant isolation. The platform comes with various project templates and supports exporting projects to GitHub or users' Cloudflare accounts. Moreover, it features observability for cost and performance, caching for frequently accessed requests, and multi-model support via routing across different AI providers. Designed specifically for teams, VibeSDK empowers them to create internal or customer-facing “no-code/low-code” solutions, allowing even those without programming skills to easily develop landing pages, prototypes, or applications from simple natural language prompts. This makes it an incredibly versatile tool for organizations looking to enhance their development capabilities.

Archestra serves as an open-source, self-hosted AI platform designed for the deployment and management of agents within an organization. It features agentic chat functionalities tailored for non-developers, along with applications, skills, collaborative projects, a server-side agent runtime, MCP orchestration, permission-aware RAG, LLM and MCP proxies, security guardrails, and comprehensive observability, all integrated into a single platform. Users can authenticate through SSO, ensuring that every tool interaction occurs under the individual’s personal identity rather than through a common service account. Projects are organized to consolidate chats, files, scheduled tasks, and instructions, while agents operate within isolated containers, triggered by schedules, emails, or webhooks. MCP servers are hosted within the organization's Kubernetes environment, navigating through security-reviewed promotion processes that enforce distinct credentials and network policies. Furthermore, knowledge bases can interface with Confluence, Jira, drives, and internal documents while maintaining source-system ACLs, ensuring that users can access only the content for which they possess permissions. This comprehensive suite of features makes Archestra an invaluable resource for organizations looking to streamline their AI deployments and governance.

E2B is an open-source runtime that provides a secure environment for executing AI-generated code within isolated cloud sandboxes. This platform allows developers to enhance their AI applications and agents with code interpretation features, enabling the safe execution of dynamic code snippets in a regulated setting. Supporting a variety of programming languages like Python and JavaScript, E2B offers software development kits (SDKs) for easy integration into existing projects. It employs Firecracker microVMs to guarantee strong security and isolation during code execution. Developers have the flexibility to implement E2B on their own infrastructure or take advantage of the available cloud service. The platform is crafted to be agnostic to large language models, ensuring compatibility with numerous options, including OpenAI, Llama, Anthropic, and Mistral. Among its key features are quick sandbox initialization, customizable execution environments, and the capability to manage long-running sessions lasting up to 24 hours. With E2B, developers can confidently run AI-generated code while maintaining high standards of security and efficiency.

As you navigate the internet, your device faces potential malware threats, making advanced appliance-based sandboxing an invaluable resource. A sandboxing tool acts as a shield, confining viruses and malware within a controlled virtual space. SHADE Sandbox enables the safe execution of potentially harmful code without jeopardizing the integrity of your network or the host device. This program establishes a segregated environment, proving to be the leading shareware sandboxing solution available. By downloading and installing SHADE Sandbox, you can enhance protection against previously undetected cyber threats, particularly elusive malware. The remarkable feature of a sandbox is that any activity conducted within it remains contained, thereby preventing system failures and halting the spread of software vulnerabilities. With SHADE Sandbox, you not only protect your PC but also gain peace of mind in your online activities, ensuring a safer browsing experience.

Sandboxie is a software that offers sandbox-based isolation for 32- and 64-bit Windows NT-based systems. It has been under the development of David Xanatos since its transition to open-source status; prior to that, it was managed by Sophos, which obtained it from Invincea, the company that previously acquired it from its original creator, Ronen Tzur. By creating an isolated operating environment, Sandboxie allows users to run or install applications without making permanent changes to the local or mapped drives. This virtual isolation enables safe testing of untrusted applications and secure web browsing. Following its open-source release, Sandboxie is available in two versions: the classic build featuring a MFC-based user interface and the Plus build that comes with enhanced features and a completely new Q't based interface. Most of the new functionalities are directed towards the Plus version, but many can also be accessed in the classic version by modifying the sandboxie.ini file. This flexibility makes it easier for users to benefit from updates while still maintaining a preference for the traditional interface.

Eve serves as a framework for creating agents, akin to how Next.js functions for web applications, offering a specialized environment for agent development. It employs Markdown to articulate instructions and skills, while TypeScript is utilized for implementing tools, ensuring durable execution by default. An agent is essentially a directory that outlines its instructions and skills using Markdown, defines tools through TypeScript, and facilitates deployment. Eve meticulously compiles this directory, orchestrates durable workflows, and integrates various channels, providing developers with a systematic approach to construct production-ready agents without the need to piece together disparate solutions. An instructions.md file can represent a fully functional agent, and the agent.ts file empowers teams to select a model or adjust the runtime configuration. Skills can be reused as Markdown playbooks that are loaded when needed, allowing the agent to receive targeted guidance without the burden of carrying unnecessary information in every prompt. Tools are introduced as TypeScript files, with their filenames serving as the tool names, eliminating the requirement for any registration process. Each agent operates within its own isolated sandbox and includes file tools, and there is also the option for custom sandbox configurations, enhancing flexibility for developers. This robust framework not only streamlines agent creation but also fosters innovation by allowing developers to focus on building unique functionalities.

AGBCLOUD is a cloud-based sandbox platform designed for AI that offers developers and organizations secure and isolated environments to create and manage autonomous software agents. This platform provides agents with fully-equipped cloud development environments that facilitate multilingual code generation, compilation, and debugging through easily accessible browser sandboxes. By allowing advanced functionalities such as web browsing, computer interactions, and data analysis, AGBCLOUD ensures that AI systems can engage with files, applications, and the internet safely within a controlled space. Furthermore, it incorporates plug-and-play MCP tools alongside LLM-driven analytics to convert raw data into meaningful insights and dynamic applications. The sandbox architecture supports cross-platform capabilities, enabling agents to transition effortlessly between coding, browsing, and system-level tasks, all while upholding stringent security and isolation measures. This versatility opens up new possibilities for developers seeking to enhance their AI solutions.

Construct Computer serves as a cloud-centric AI agent workspace tailored for individual entrepreneurs and small groups. Users can delegate tasks using either a browser-based desktop or a chat-optimized web interface. The agents within the platform have the capability to search the internet, navigate interactive websites, execute code in a secure sandbox environment, manage files, create documents, and utilize various connected applications. This workspace is equipped with features such as persistent files and memory, an email inbox for agents, a calendar, reusable workflows, records of activities, and shared resources for teams. Users have the ability to review or modify memory and can monitor or halt the agents' progress. Construct Computer integrates seamlessly with platforms like Slack, Telegram, and Discord, along with a selection of services from its Composio integration catalog; additionally, workspaces can employ custom MCP servers and private applications. Agents are able to assign limited subtasks and execute scheduled jobs in the cloud environment. Subscription plans impose restrictions on agents, including limits on task steps, scheduled activities, concurrent jobs, command execution time, and storage space. Furthermore, a mobile web interface is accessible through smartphone browsers, although the vendor clarifies that it is not an App Store application. Overall, Construct Computer aims to streamline workflow management for its users by offering a diverse array of functionalities and integrations.

Ausca delivers on-demand infrastructure tailored for AI agents and developers via a comprehensive public service catalog and API. Its range of services encompasses document OCR and analysis, transcription of audio and video, bounded remote browser sessions, and temporary email inboxes for receiving messages only. Each service comes with clear specifications regarding inputs, limitations, pricing, and user instructions. Developers have the flexibility to connect using HTTP with X402 payments, tools compatible with the MCP, command-line utilities, or typed clients. Users can explore services without needing an account or API key, while paid executions necessitate explicit payment approval. The pricing structure is based on either per invocation or lease agreements, and users can receive a verifiable receipt upon completion of work. Ausca is specifically crafted for developers and operators of AI agents who wish to integrate document, media, browser, or inbox functionalities into their automated workflows without the need to deploy these services independently. This innovative approach streamlines the integration process, enabling a more efficient workflow for developers.

NullClaw is a highly efficient, ultra-lightweight AI assistant framework crafted in Zig and distributed as a single static binary, enabling it to operate seamlessly on nearly any type of hardware. Its focus is on delivering exceptional performance while minimizing resource consumption, as evidenced by its compact size of approximately 678 KB and a typical RAM usage of around 1 MB, with boot times of less than two milliseconds. By steering clear of traditional runtime overhead associated with virtual machines, interpreters, and complicated dependency chains, it allows developers to deploy agents effortlessly by executing the compiled binary. In spite of its minimal footprint, NullClaw boasts a comprehensive autonomous agent architecture that accommodates over 22 model providers, 18 communication channels, hybrid vector and FTS5 memory, as well as capabilities for streaming, voice, and multi-layer sandboxing. Moreover, security features are inherently integrated, including workspace scoping, explicit command allowlists, encrypted secrets, and robust sandbox isolation through tools like Landlock, Firejail, or Docker. Its design ensures that users can trust the integrity and functionality of their autonomous agents while maximizing efficiency across various applications.

Command Code is an advanced coding assistant that operates within the terminal, enabling the creation of comprehensive full-stack applications, deploying new features, troubleshooting issues, writing test cases, and optimizing code, all while adapting to the unique workflows of individual developers. It harnesses the power of the meta neuro-symbolic taste-1 model alongside continuous reinforcement learning, interpreting every suggestion, rejection, and modification as valuable feedback, which allows it to identify and cultivate recurring preferences, structures, patterns, and tools into enduring skills and memories for each project. Rather than simply adhering to standard best practices, it assimilates developers' code review techniques, stylistic inclinations, architectural choices, as well as their preferred package managers and libraries, even those minor conventions that often go undocumented, thereby applying this contextual understanding in future interactions. Command Code is equipped with features that facilitate interactive command-line interface operations, headless prompts, automated task execution, planning capabilities, background sandboxes, customizable agents, checkpoints, and memory retention across different sessions, providing a truly personalized coding experience. This innovative tool not only streamlines the development process but also empowers developers to enhance their productivity and maintain consistency in their coding practices over time.

Fly.io is a developer-focused cloud platform that provides fast, scalable infrastructure for running applications and services globally. It introduces Fly Machines, which are hardware-virtualized containers that launch instantly and run only when needed. The platform enables developers to deploy applications quickly without managing complex cloud configurations. With support for multiple programming frameworks, Fly.io allows users to build using the tools they already know. It offers secure sandbox environments, making it suitable for running untrusted or AI-generated code safely. The platform includes global deployment across multiple regions, ensuring fast response times for users everywhere. Built-in private networking and encryption enhance security and connectivity. Fly.io also provides flexible storage options, including fast local storage and durable object storage. Its autoscaling capabilities allow applications to handle varying workloads efficiently. Overall, Fly.io simplifies cloud infrastructure while delivering performance, flexibility, and scalability.

Flowise is an open-source agentic development platform designed to help teams build AI agents and LLM-powered applications using a visual workflow interface. The platform allows users to design intelligent workflows through modular components that can be combined to create chatbots, automation systems, and autonomous AI agents. Developers can build both single-agent chat assistants and multi-agent systems that collaborate to complete complex tasks. Flowise integrates with more than 100 large language models, embedding models, and vector databases, providing flexibility in selecting AI technologies. The platform also supports retrieval-augmented generation (RAG), enabling applications to retrieve knowledge from documents and data sources. Built-in features such as human-in-the-loop workflows allow users to review and validate agent actions before execution. Observability tools provide detailed execution traces and compatibility with monitoring systems like Prometheus and OpenTelemetry. Developers can integrate Flowise with existing applications using APIs, SDKs, or embedded chat widgets. The platform supports both cloud and on-premises deployment environments for enterprise scalability. By providing visual tools and flexible integrations, Flowise accelerates the development and deployment of advanced AI-driven applications.

21st is a development platform designed to help engineers quickly build and deploy AI agents inside their applications. The platform provides a specialized SDK that simplifies the process of defining agent behavior, integrating tools, and connecting AI models. Developers can create agents using familiar technologies such as Next.js, React, TypeScript, Python, and Node.js, making integration straightforward for modern applications. Once an agent is defined, the platform allows it to be deployed with a single command while automatically handling infrastructure requirements. 21st provides sandboxed execution environments through E2B sessions, ensuring that agent operations run securely and independently. The platform includes a ready-to-use chat interface component that can be embedded directly into an app for user interaction. Additional features include token streaming, conversation history, tool execution, and built-in observability for debugging and monitoring. Developers can replay sessions and trace tool calls to better understand how agents behave during execution. The system also supports spend limits, authentication controls, and rate limiting to manage AI usage across users. By combining development tools with managed infrastructure, 21st helps teams launch scalable AI agents without building complex backend systems.

NVIDIA OpenShell serves as an open and secure runtime environment specifically designed for autonomous AI agents, regulating their execution, access rights, and the pathways for inference traffic. Instead of embedding security within the model or application, it maintains safety measures in the surrounding environment, meaning that nothing is allowed by default; permissions are assigned through established policies, and enforcement mechanisms operate outside the agent process to prevent any circumvention via prompts. Each autonomous agent operates within a confined sandbox, which restricts direct network connectivity, limits file access, and implements kernel-level monitoring of system calls to ensure rigorous oversight. Acting as the control plane, a gateway is responsible for user authentication, lifecycle management of sandboxes, and the provision of policies, settings, credentials, and inference configurations to the agents. Additionally, a supervisor operates externally to each sandbox, scrutinizing network requests according to policies at various levels—including binary, destination, method, and path—and only grants access to credentials when explicitly permitted, thus enhancing the overall security framework. This layered architecture ensures that the agents function effectively while maintaining robust security protocols throughout their operations.

CodeSandbox aims to make it easier for you to express your ideas with code, and to validate them. It also removes the hassles of setting up development tooling and sharing your project. Join us to help build the future of web coding. Over 4M developers use the platform each month. This includes organizations like Shopify and Atlassian. Since its launch, creators have created over 35M apps. It's used in thousands of open-source projects like React, Vue and Babel. You can invite your friends, colleagues, or team to join you or simply view your creation by using a URL. Use any of 1M+ packages for building real, powerful applications quickly and efficiently. Import and run repos directly from GitHub or choose from hundreds of templates to start in seconds. Boxy, CodeSandbox's AI-powered coding assistant, is now available to all Pro subscriptions.

Comodo Advanced Endpoint Protection delivers an exceptional anti-malware suite that actively safeguards your servers, workstations, laptops, and netbooks, while also providing sophisticated, real-time oversight and management of essential system resources. It can be utilized either as a comprehensive security package or as a standalone sandbox to enhance existing antivirus solutions, making Comodo ESM a top choice for endpoint protection on Microsoft Windows servers, desktops, laptops, and tablets. The complete Comodo Endpoint Security suite boasts five layers of defense—Antivirus, Firewall, Host Intrusion Prevention, Auto-Sandbox, and File Reputation—directly at the user level on the desktop. Its innovative auto-sandbox technology effectively prevents malware infections and operating system damage by executing untrusted processes in a segregated environment. Furthermore, Comodo's endpoint protection is distinguished as the only managed anti-malware solution that offers a limited warranty of $5,000 against malware infections, affirming its commitment to security. This combination of advanced features ensures that users have a robust and reliable defense against evolving cyber threats.

Epho transforms coding agents into a versatile API, enabling developers to execute Claude Code, Codex, or OpenCode in secure cloud sandboxes via a singular HTTP endpoint. Users can submit prompts, select a harness and model, link repositories and files, connect to MCP servers, and provide environment variables or provider credentials; Epho will then initiate the environment, replicate the code, integrate the necessary tools, and stream the agent's progress in real-time. The system supports both synchronous runs, which can deliver live events, tool calls, edits, final outputs, and artifacts, as well as asynchronous execution featuring polling and webhooks. Importantly, chat sessions are persistent, allowing subsequent interactions to continue from the same filesystem, checkout, agent session, system prompt, model, and MCP setup, even in the absence of the original sandbox. It accommodates private repositories from GitHub, GitLab, and Bitbucket, with agents capable of reading code, implementing changes, executing tests, and refining errors similarly to a local environment. Furthermore, every event is securely stored, ensuring that interrupted streams can reconnect seamlessly without any loss of data during a run. This robust architecture not only enhances productivity but also fosters a more efficient coding workflow.

BrowserPod serves as a virtual machine that operates directly within the browser environment. Its API offers a streamlined Linux kernel, effectively replacing costly and intricate cloud setups by shifting server operations to the user's browser through WebAssembly technology. This innovative tool allows developers to create isolated environments for AI applications, develop tools, and generate documentation without relying on cloud computing resources. It plays a significant role in broader enterprise transformation initiatives that focus on minimizing cloud expenses and reliance. Rather than investing in expensive cloud servers, BrowserPod enables users to run comprehensive workloads right in their browser tabs. Each pod is temporary, designed to adhere to the browser's security protocols, and operates independently from the host OS through a specific syscall layer. With the support of the Linux kernel, BrowserPod ensures compatibility across various native runtimes, including popular languages such as Node.js, Rust, Python, Ruby, and Go, making it a versatile choice for developers. This flexibility enhances the user experience by allowing seamless transitions between different programming environments.

Scalebrowser provides a self-hosted infrastructure designed specifically for AI agents that require the capability to accomplish genuine tasks. Each unique profile maintains consistency in identity, cookies, passkeys, memory, and tasks, regardless of whether the system is restarted or if the user switches devices. It utilizes a modified Chromium engine alongside authentic local GPU values, enabling human-like interactions and effective handling of captchas, email and SMS verification codes, and TOTP, all while allowing browser-level prompt control to ensure agents can navigate beyond the limitations faced by standard automation tools. Users can connect through various methods including MCP, REST, Node.js, Python, or even direct CDP for versatile integration. This level of functionality empowers AI agents to perform in environments that typically resist automation attempts.

HybridClaw is a robust AI agent platform crafted for enterprises, acting as a continuous digital colleague that integrates workflows seamlessly across various communication channels, tools, and execution environments into a singular intelligent system. This platform features a “shared assistant brain” that functions uniformly across platforms such as Discord, Teams, iMessage, WhatsApp, email, web interfaces, and terminal environments, guaranteeing that every user engages with the same memory, behavior, and execution logic. By utilizing persistent workspace memory, semantic recall, and knowledge-graph relationships, it effectively sustains context throughout extensive conversations and tasks, allowing it to track projects, decisions, and interactions over time. Furthermore, HybridClaw supports comprehensive task execution by securely managing tools, commands, and workflows within sandboxed environments, implementing guardrails, permission controls, and audit logs to ensure that automation is both safe and regulated. This level of integration not only streamlines processes but also enhances collaboration among team members, ultimately contributing to improved productivity.

Zunoy Sandbox serves as a platform for developers to conduct tests on various communication methods such as email, SMS, webhooks, OTP, and TOTP/MFA flows, all while ensuring that no test data reaches actual users or production environments. By integrating their current SMTP clients, SMS APIs, or webhook endpoints into the Sandbox, developers can monitor the resulting events within a secure testing framework. When it comes to email testing, the Sandbox offers dedicated inboxes that allow teams to analyze HTML content, email headers, attachments, links, and details related to delivery. For SMS testing, it facilitates OTP and transactional message flows via REST APIs, configurable sender IDs, and customizable templates. Additionally, the webhook testing capability provides distinct endpoints for capturing and analyzing JSON payloads in real time, with features to replay events and categorize them by project. Furthermore, the TOTP/MFA functionality can produce time-sensitive authentication codes derived from secrets or QR codes, enabling developers to test login and verification processes without relying on a physical authenticator, thus enhancing the testing experience significantly.

KERNEL serves as a cloud-based browser infrastructure solution tailored for developers who create AI agents and automate web interactions. By offering managed browser sessions, it enables these agents to explore websites, engage with content, and execute tasks through programming rather than depending on traditional local browser configurations. The platform is optimized for production use, featuring persistent browser profiles, live session monitoring, recording, and replay functionalities, along with tools to oversee browser access effectively. Teams can seamlessly integrate their agent workflows using KERNEL's APIs, SDKs, and hosted MCP server, making it ideal for web research, data collection, and various activities that necessitate web engagement. Additionally, KERNEL offers various subscription options for individuals, startups, and large enterprises, each providing different levels of browser concurrency, usage credits, and access to advanced features like managed authentication, stealth mode, and region-specific browsers. Ultimately, KERNEL stands out as a comprehensive solution catering to a wide range of web automation needs.

Modular is an advanced AI infrastructure platform that unifies the entire inference stack, from hardware-level optimization to cloud deployment. It allows developers to run AI models seamlessly across multiple hardware types, including NVIDIA, AMD, and other architectures. The platform eliminates the need for fragmented tools by providing a single system for serving, optimization, and scaling. Modular delivers high-performance inference with improved efficiency and reduced costs through better hardware utilization. It supports flexible deployment options, including managed cloud services, private VPC environments, and self-hosted setups. Developers can deploy both open-source and custom models with ease while maintaining full control over performance. The platform’s compiler technology automatically optimizes workloads for different hardware targets. Modular also enables real-time scaling and efficient resource allocation for demanding AI applications. Its unified approach simplifies infrastructure management while improving reliability and performance. Overall, Modular empowers teams to build, deploy, and scale AI systems more effectively.

fx is a compact, open-source coding agent and command-line interface (CLI) developed in Zig, specifically optimized for research applications, performance, and seamless integration into larger systems. Its architecture emphasizes minimalism throughout the system prompt, available tools, feature set, memory usage, and maintains a small binary size of just 6 MB, aiming for an interface experience that resembles a Unix shell rather than a cumbersome terminal IDE. With an impressive cold start time in microseconds, fx avoids unnecessary tasks or input/output operations before receiving commands, making it ideal for programmatic applications, environments with limited resources, and agent sandboxes. Developers can easily initiate it within a project to perform tasks such as reading files, searching through code, executing commands, implementing changes, running tests, and streaming tool activations in real time. The underlying framework is both model- and provider-independent, enabling compatibility with local models, API gateways, direct provider connections, and cloud-based inference options. By design, it maximizes context efficiency, utilizing a succinct system prompt and streamlined toolset to minimize token overhead and enhance the speed of response to the first token generated. In addition, this unique focus on lightweight operation and quick interaction allows developers to maintain productivity without the typical overhead associated with more complex environments.

In contrast to earlier viruses that were relatively simple and few in number, traditional antivirus solutions could adequately safeguard systems using a database of signatures. However, the landscape of modern malware has evolved, incorporating advanced techniques like exploiting vulnerabilities. When a weakness in a trusted application is exploited, it can lead to unexpected behavior, which attackers leverage to breach computer security. This method of attacking through an undisclosed software vulnerability is referred to as a zero-day attack, or 0-day attack, and prior to the adoption of sandboxing, effective prevention methods were lacking. A malware sandbox serves as a protective mechanism that restricts an application's operations, such as handling a Word document, within a controlled environment. This isolated space allows the sandbox to scrutinize the dynamic behaviors of applications and their interactions in a simulated user setting, thereby revealing any potential malicious activities. Such technology has become essential in the fight against sophisticated threats, ensuring a more comprehensive approach to cybersecurity.

happycapy serves as an agent-native AI platform that transforms your web browser into a robust "agent computer," allowing developers and users to launch and operate autonomous AI agents around the clock without relying on conventional server setups. This innovation enables the delegation of tasks to numerous large language models (LLMs) and AI services, including Claude Code, all within a secure, sandboxed environment. By facilitating the simultaneous operation of multiple AI agents, happycapy effectively manages coding, automation, data processing, and custom workflows, providing teams with a cohesive interface for orchestrating, scaling, and monitoring agent-related activities. The platform prioritizes flexibility and developer autonomy through a private sandbox, where agents can perform tasks, engage with code and data, and collaborate on intricate projects while overseeing state, logs, and outputs from various AI services. Additionally, happycapy streamlines the development and upkeep of AI-driven applications by simplifying the complexities associated with infrastructure and model management. This makes it easier for teams to harness the full potential of AI technology in their workflows.

HyperLake is designed specifically for organizations that are ready to embrace a future where AI agents are the primary users of their infrastructure. Currently, most enterprise infrastructures cater primarily to human users, relying on dashboards, applications, and pre-scheduled pipelines. In contrast, AI agents function differently by querying data, utilizing tools, triggering workflows, generating artifacts, and operating across various systems, which necessitates their continuous access to managed compute resources, data, policies, and services. To address this shift, HyperLake offers a command center that facilitates the deployment, management, operation, security, and governance of this agent-centric infrastructure. The initial offering focuses on Agentic Data Cloud Infrastructure, which includes an open-stack solution for data, analytics, semantics, workflows, and agent systems that can be deployed within the customer’s own virtual private cloud, private cloud, or on-premises setups. This innovative approach ensures that organizations can seamlessly integrate AI agents into their existing frameworks, enhancing efficiency and adaptability in their operations.