Alternatives to InstaVM

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.

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.

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.

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.

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.

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.

OpenFang is an innovative open-source Agent Operating System developed in Rust, designed to deliver a cohesive runtime for the creation, deployment, and oversight of autonomous AI agents at a production level. It features a comprehensive architecture bundled into a single executable, which allows developers to deploy agents that run continuously, construct knowledge graphs, and send updates to a centralized dashboard without the need for ongoing user interaction. Central to OpenFang are its "Hands," which are pre-configured autonomous capability packages that function on predetermined schedules to carry out various tasks, including lead generation, research activities, browser automation, and social media management. The platform offers numerous pre-built agents along with native tools and channel adapters, facilitating seamless operation across various platforms such as Slack, WhatsApp, Discord, and Teams from a unified interface. Engineered with security at its core, OpenFang incorporates multiple layers of defense, including WASM sandboxing, cryptographic signing, taint tracking, and tamper-proof audit trails, ensuring robust protection for users. This comprehensive approach not only enhances the functionality of AI agents but also fosters trust and reliability in their operations.

CreateOS Sandbox serves as a cloud-based computing solution designed specifically for developers focused on creating AI agents, code-execution environments, and various developer utilities. The service utilizes isolated Firecracker micro-virtual machines that each operate under their own Linux kernel, allowing teams to securely execute untrusted code or code generated by models. Developers have the flexibility to set up environments via a TypeScript SDK, command-line interface, MCP tools, or REST API, enabling them to run commands and establish connections between sandboxes within private networks. These sandboxes can easily be paused and resumed while maintaining the guest state, are customizable using reusable templates, and can be integrated with customer-owned storage solutions such as Amazon S3, MinIO, or Cloudflare R2. It's important to note that usage is charged per second based on compute, memory, and disk space, with paused environments still accruing costs for memory and storage. The service is available in both EU and US regions, and there is an enterprise option that allows for deployment on the customer's own infrastructure, enhancing flexibility and control for businesses. Overall, CreateOS Sandbox presents a robust platform that caters to the needs of modern developers.

nono is a novel open-source sandbox that utilizes kernel enforcement to create a secure environment for AI coding agents and LLM tasks. In contrast to traditional policy-based guardrails that merely monitor and filter operations, nono leverages operating system security features—specifically Landlock on Linux and Seatbelt on macOS—to render unauthorized operations impossible at the syscall level. With just a single command, you can encapsulate any AI agent, including Claude Code, OpenCode, OpenClaw, or any command-line interface process. The system automatically enforces a default-deny policy for filesystem access, restricts harmful commands (such as rm, dd, chmod, and sudo), isolates sensitive credentials and API keys, and extends all imposed restrictions to any child processes, ensuring there's no avenue for escape once limitations are set. Built-in profiles allow for rapid deployment, and secrets can be injected from the system keystore in a secure manner, with automatic zeroization upon exit. Additionally, future enhancements such as audit logging, atomic rollbacks, and Sigstore-attested policy signing are planned, offering robust tracking and security features. It operates under the Apache 2.0 license and is developed by the same creator behind Sigstore, further emphasizing its credibility and reliability in securing AI workloads.

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.

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.

InstaClaw is a platform for consumer AI agents that enables individuals to set up a fully autonomous personal AI assistant in just minutes, requiring no coding or technical knowledge, and it offers a dedicated infrastructure for the agent to operate continuously, performing a variety of real-world tasks on the user's behalf. Each AI agent is hosted on its own virtual machine, ensuring constant availability, and can undertake actions like sending emails, managing schedules, browsing the internet, organizing files, conducting research, and automating tasks through simple natural language commands. The platform seamlessly integrates with popular messaging apps such as Telegram, WhatsApp, and iMessage, allowing users to communicate with their agents as if they were sending texts, while the system efficiently manages the execution of tasks in the background. InstaClaw comes equipped with essential pre-installed skills, including web browsing, file organization, and research functionalities, and it offers options for further expansion through additional features and integrations, empowering agents to tackle more complex assignments. This innovative approach not only enhances user productivity but also simplifies the interaction between technology and everyday tasks.

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.

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.

ZeroClaw is a framework for autonomous AI agents developed in Rust, tailored for teams that need a rapid, secure, and highly customizable agent infrastructure. This framework is crafted as a streamlined, production-ready runtime that initiates promptly, operates efficiently, and scales seamlessly through various providers, channels, memory systems, and tools. With a trait-based architecture at its core, ZeroClaw empowers developers to easily switch model backends, communication protocols, and storage solutions simply by adjusting configurations, which minimizes vendor lock-in and enhances maintainability over time. Its design prioritizes a minimal resource footprint, being packaged as a single binary of roughly 3.4 MB and achieving startup times of less than 10 milliseconds while maintaining low memory consumption, making it ideal for servers, edge devices, and low-power systems. Security is inherently prioritized, featuring built-in sandbox controls, filesystem restrictions, allowlists, and encrypted handling of secrets, all activated by default. This combination of agility, efficiency, and robust security measures positions ZeroClaw as a leading choice for teams looking to implement cutting-edge AI solutions.

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.

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.

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.

Omnara is an open-source API for building and running AI agents in your product or internal workflows. It handles agent execution and state, so developers can focus on what each agent needs to do instead of building the infrastructure around it. You can use Omnara to add agents to a customer dashboard, create internal Slack agents, or run workflows such as code review. Launch agents, send instructions, and follow their work through a REST API, TypeScript SDK, or CLI. Agents preserve their state and can resume after interruptions. Choose the models, tools, and environments that fit your project. Omnara supports providers such as OpenAI, Anthropic, and OpenRouter, as well as compatible endpoints for models you host yourself. Agents can use managed sandboxes or connect to your own machines. MCP integrations and reusable skills let them work with external tools and data. For teams, Omnara provides project access controls, encrypted secrets, activity history, and approval steps for sensitive tool actions. You can start with Omnara Cloud or self-host the platform in your own environment.

Gemini Computer Use is an agentic computer interaction capability built into Gemini 3.5 Flash. It enables developers and enterprises to create AI agents that can work across browser, desktop, and mobile environments by seeing interfaces, reasoning through tasks, and taking action. The capability was previously offered through a standalone Gemini 2.5 computer use model, but is now natively integrated into Gemini 3.5 Flash. This gives developers access to stronger performance for agentic computer use tasks while also combining with Gemini’s existing strengths in function calling, Search grounding, Maps grounding, and built-in tools. Gemini Computer Use is designed for long-horizon automation, continuous software testing, enterprise knowledge work, and workflows that span multiple professional applications. Developers can start building with the feature through the Gemini API or Gemini Enterprise Agent Platform. Google also provides a demo environment through Browserbase for testing the capability. Safety controls include targeted adversarial training for live-environment risks, optional explicit user confirmation for sensitive or irreversible actions, and automatic task stopping when indirect prompt injection is identified. Gemini Computer Use helps organizations build practical AI agents that can complete complex digital tasks while supporting sandboxing, human review, and strict access controls.

Recent and more sophisticated cyber-attacks have increasingly focused on infiltrating organizations by embedding malware or harmful files within web applications and emails. These attacks facilitate the dissemination of malware that often evades detection by standard security measures; thus, they are referred to as Advanced Persistent Threats (APTs). Despite this growing concern, many organizations continue to utilize traditional security approaches, such as antivirus programs, firewalls, and intrusion prevention systems, to counteract evolving malware threats. As a result, numerous organizations find themselves still exposed to these Advanced Persistent Threats. It is well-known that the repercussions of such attacks can lead to significant financial losses due to compromised intellectual property, theft of sensitive information, damage to infrastructure, and operational downtime. To combat these complex threats, AhnLab MDS (Malware Defense System) offers a robust APT protection solution that utilizes a hybrid of on-premise and cloud-based analytics, effectively addressing advanced targeted threats throughout the organization and enhancing overall cybersecurity resilience. Moreover, this comprehensive approach empowers organizations to proactively defend against the ever-changing landscape of cyber threats.

Tines 3B is a robust platform designed for intelligent workflows, enabling users to efficiently create and implement AI agents, applications, and automation in a single, secure environment at scale. Users can initiate their projects using natural language prompts, articulate their processes conversationally, collaborate with an integrated LLM for brainstorming, or develop workflows through coding with integrated Git and branching capabilities. As users construct their workflows, the platform suggests tests, generates placeholder data when necessary, and prompts for confirmation before utilizing any live data or applications. The Dedicated Spaces feature ensures that the appropriate connectors, permissions, and skills are in place, while LLM Skills facilitate consistency in the development practices across various teams. Each step within a workflow operates in a secure, isolated sandbox, and credentials are dynamically injected during runtime via a transparent proxy to ensure that sensitive information remains protected from builders, AI systems, or stored code. Furthermore, these workflows can be executed in self-hosted, on-premises, or hybrid configurations, providing flexibility and adaptability for any organizational needs. This comprehensive approach allows teams to innovate rapidly while maintaining high standards of security and efficiency.

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.

BrowserAct is a cloud-based platform that harnesses AI to automate browser tasks and extract data, allowing users to engage with websites and gather information using natural language without the need for coding. Its user-friendly interface enables users to articulate their needs, such as tracking competitor prices, observing industry trends, or supplying data to AI systems, while the platform automatically sets up the necessary workflows. With features like intelligent routing, multi-step task management, real-time data access, and a worldwide residential IP network, BrowserAct adeptly handles complex scenarios, including scraping from restricted sites, managing human verification, and ongoing content observation. The platform provides high-quality structured data that is perfect for training and improving AI agents, making it easier to conduct market research and analyze competitors. Furthermore, by streamlining repetitive online tasks through a simple interface, BrowserAct effectively connects the world of manual browsing with comprehensive automation, enhancing productivity and efficiency for its users. In this way, it not only simplifies the process of data collection but also empowers users to make more informed decisions based on real-time insights.

omp (oh my pi) is an AI coding agent platform designed to give developers a fully integrated environment for software development, debugging, automation, and collaboration. Built as an enhanced evolution of the Pi coding harness, it connects AI models directly to language servers, debuggers, shells, browsers, memory systems, GitHub repositories, and local development tools without relying on separate plugins or external workflows. The platform supports more than 40 AI providers, allowing developers to switch between frontier models, coding plans, local models, and self-hosted AI services from a unified interface. omp includes advanced capabilities such as structural code editing, intelligent code review, persistent Python and JavaScript execution, browser automation, workflow orchestration, subagents, and collaborative live coding sessions. Developers can debug applications using integrated DAP support, perform semantic code analysis through LSP integration, and automate complex development tasks with specialized built-in tools. Its local memory system allows the agent to retain project knowledge across sessions while maintaining developer control over stored information. omp also introduces innovations such as hash-based code editing, deterministic context compaction, time-traveling stream rules, and content-aware retrieval that improve AI coding accuracy while reducing token usage. Built on a native Rust engine with support for Windows, macOS, and Linux, the platform emphasizes speed, low overhead, and deep integration with local development environments. As an MIT-licensed open-source project, omp gives developers an extensible AI coding platform that can be customized, audited, and expanded to match their own engineering workflows.

The NVIDIA Open Agent Safety Platform serves as an open reference framework designed to monitor and manage the behavior of AI agents continuously, ensuring that organizations can maintain agents that are isolated, observable, auditable, and operate within set boundaries. This platform integrates real-time governance, ongoing threat detection, and the enforcement of policies through hardware isolation, providing robust protection for enterprise AI agents from the initial testing phases all the way to deployment. The NVIDIA OpenShell contributes to this by offering an open-source runtime that differentiates the execution of agents from their access to data, tools, and outside systems, utilizing sandboxed environments and a zero-trust policy approach to strictly regulate agents' visibility, actions, and interactions. Policies are enforced externally to the agent process, effectively mitigating the risks associated with unpredicted behavior. Furthermore, NVIDIA Sentry enhances security by adding an extra layer that meticulously monitors agent requests and responses, verifies agent identities, and continuously manages access to data, tools, APIs, and services while also having the capability to isolate agents when necessary. This comprehensive approach ensures that organizations can safeguard their AI agents while promoting a secure and controlled operational environment.

AgentSky is a comprehensive platform that offers agent-as-a-service solutions for deploying persistent, always-active AI agents in the cloud, eliminating the need for Mac minis, extensive setups, or any infrastructure management. Users are able to select an agent harness, such as Claude Code, Codex, Hermes, or OpenClaw, pair it with an appropriate model, enhance its capabilities, and initiate it effortlessly with a single click. These agents are accessible through various platforms including WhatsApp, iMessage, Telegram, Slack, Discord, web chat, the A2A protocol, and the CLI, ensuring consistent history, tools, and state across different communication channels. Additionally, local setups of Claude Code, Codex, or OpenClaw can be seamlessly transferred to the cloud, maintaining all instructions, model configurations, and MCP servers while avoiding the transfer of sensitive information like secrets, API keys, or session history. Every agent operates as a managed worker featuring a durable state, ongoing history tracking, snapshots, backups, restoration capabilities, and an isolated sandbox environment that starts up with only the tools that are attached, ensuring both security and efficiency. This innovative approach allows for greater flexibility and scalability in deploying AI solutions tailored to user needs.

Gobii is a cloud-based service that allows users to deploy fully managed browser automation agents through an API, facilitating the automation of web research, form submissions, data extraction, and complex workflows on a large scale. These agents function like perpetual employees, capable of navigating websites—even those without APIs—managing dynamic content, executing JavaScript, and automatically rotating proxies when necessary. Users have the ability to create these agents, assign them specific prompts or tasks, and obtain structured JSON outputs or real-time previews of the agents' browser activities. Gobii also accommodates both synchronous and asynchronous task execution, offers secret management for sensitive information like login credentials, and ensures output validation through schema enforcement. Furthermore, it integrates with widely used programming languages such as Python and Node.js for easy implementation. The platform places a strong emphasis on scalability, allowing for the execution of hundreds of tasks simultaneously, while also providing enterprise-level security features like audit logs, proxy management, and comprehensive task oversight. As a result, developers benefit from a streamlined experience that makes it easier to integrate complex automation into their workflows.

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.

Mistral Medium 3.5 stands out as a premier 128B dense model that integrates instruction-following, logical reasoning, and coding capabilities into a unified framework. Featuring a remarkable 256K context window, it allows for adjustable reasoning effort and supports multimodal input, showcasing robust agentic functionalities, particularly suited for long-duration tasks that necessitate dependable multi-tool utilization and structured results. This innovative model fuels remote agents within Mistral Vibe, enabling coding tasks to be executed in the cloud, autonomously addressing lengthy assignments, and managing several sessions simultaneously. Users have the flexibility to initiate agents through the Vibe CLI or Le Chat, ensuring that local command-line interface sessions can transition to the cloud without losing history, task status, or approvals. As work unfolds, users can monitor file changes, tool interactions, progress updates, and queries. Each coding endeavor operates within a distinct sandbox, adeptly managing module refactors, generating tests, upgrading dependencies, conducting CI investigations, and resolving bugs, ultimately culminating in the creation of a GitHub pull request for assessment. This model represents a significant advancement in how complex coding tasks are approached and handled in a collaborative environment.

NSFOCUS employs advanced Intelligent Detection technology that transcends traditional signature and behavior-based detection methods, enhancing the identification of threats to networks and applications. The NGIPS integrates artificial intelligence with leading-edge threat intelligence to pinpoint malicious websites and botnets effectively. Additionally, users can enhance the NGIPS system with an optional virtual sandboxing feature through the NSFOCUS Threat Analysis System. This TAS incorporates a range of innovative detection engines, including IP reputation, anti-virus, and both static and dynamic analysis engines, as well as virtual sandbox execution that simulates real hardware environments. Collectively, the NSFOCUS NGIPS merges intrusion prevention, threat intelligence, and the optional sandboxing capability, providing a comprehensive solution to combat known, unknown, zero-day, and advanced persistent threats while ensuring robust security measures are in place. This multi-layered approach enables organizations to stay ahead of evolving cyber threats and maintain a resilient defense strategy.

DeepSeek Harness is a versatile open-source framework crafted to ensure that AI agents can effectively operate in dynamic real-world situations by enhancing their understanding of context, tool utilization, and the ability to manage intricate tasks. Utilizing the Cordis plugin architecture, it allows for the selection, modification, and reconfiguration of various capabilities without necessitating any alterations to the underlying source code. Each plugin contributes essential features, such as models, tools, skills, and session management, while Cordis oversees the integration of plugins, along with their dependencies, services, and event handling. A comprehensive session log, which is append-only, captures each run's details, documenting system prompts, reasoning processes, tool interactions, results, scheduling of subagents, and context adjustments. Developers can analyze these logs through the Trajectory view, which organizes records by their source, and they have the ability to utilize functions like resume, fork, search, and replay that interact seamlessly with the same event stream. This structured approach not only aids in troubleshooting but also enhances the overall efficiency of AI development and deployment.

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.

Major is an online platform designed for the creation, deployment, and management of internal business applications, AI agents, skills, and workflows utilizing company data. Users can articulate a tool or process using natural language, prompting Major’s AI agent to generate an app within a sandbox environment for both preview and launch. Teams have the capability to link various databases, business applications, and APIs, enabling them to craft dashboards, administrative panels, scheduled automations, and elaborate multi-step workflows that incorporate branches, approvals, and human oversight. The applications that are deployed maintain persistent data and can be easily shared among team members, while AI agents are operable directly from the web app, via Slack, or on a set schedule. Additionally, teams can utilize Major through Claude and its command-line interface, which comes with source-code management via Git repositories. For businesses seeking enhanced features, enterprise plans offer options such as single sign-on (SSO), SCIM provisioning, and self-hosting capabilities, ensuring that organizations can tailor the platform to meet their specific needs. This flexibility and adaptability make Major a powerful tool for modern business environments.

Sculptor, developed by Imbue, is an innovative coding agent platform that integrates software engineering methodologies into a workflow enhanced by AI, allowing for the execution of your code within sandboxed environments. It effectively identifies various issues such as absent tests, stylistic discrepancies, memory issues, and race conditions, while also suggesting potential fixes for your review and approval. You can simultaneously launch multiple agents, each working within its own isolated container, and leverage the “Pairing Mode” to synchronize an agent's branch with your local IDE, facilitating testing, editing, or collaborative efforts. The real-time exchange of changes allows for a fluid development process. Additionally, Sculptor offers the ability to merge outputs from agents, highlighting and resolving any conflicts that arise, and features a beta Suggestions capability designed to identify enhancements or detect problematic agent activities. It also retains comprehensive session context—including code, planning discussions, chat interactions, and tool calls—enabling you to revisit earlier states, fork agents for new tasks, and effortlessly continue your work across different sessions. This continuity ensures that developers can maintain productivity without losing track of their progress.

CloakBrowser is a custom Chromium distribution for developers building browser automation with Playwright, Puppeteer, Selenium, or CDP. Instead of relying only on runtime JavaScript patches, it changes browser behavior at the Chromium source level while preserving familiar automation APIs. Teams can adapt existing Python, JavaScript, and .NET workflows with minimal code changes and run sessions on Windows, macOS, Linux, Docker, or their own VPS infrastructure. Features include persistent profiles, reproducible browser identities, proxy-aware locale and timezone configuration, human-like input timing, and CDP server mode. CloakBrowser is intended for legitimate public-web data collection, QA, monitoring, scraping, and AI-agent workflows. The developer wrapper is MIT-licensed, while current custom Chromium binaries are distributed separately under a proprietary license. Users provide their own proxies and CAPTCHA services.

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.

Dafthunk is an innovative platform designed for visual workflow automation, allowing users to create, manage, and implement serverless automation workflows effortlessly with a user-friendly drag-and-drop interface, eliminating the need for any infrastructure setup or container usage. The platform enables users to build workflows by visually linking nodes that execute various tasks involving AI, browser automation, data manipulation, media creation, integrations, and development tools, which are then processed on Cloudflare’s extensive global edge network, ensuring seamless scaling and reliable execution. It features a variety of workflow triggers, such as HTTP webhooks, queues, schedules based on cron, and options for manual initiation, facilitating automation that is responsive to events, time-sensitive, or initiated by users. The platform also offers persistent storage for workflow states and execution logs through Cloudflare's D1 and R2 storage services, ensuring data integrity and accessibility. Users can enhance their workflows by integrating AI models from well-known providers like OpenAI, Anthropic, Google, and Cloudflare AI, enabling capabilities in text generation, summarization, vision processing, natural language processing, transcription, image generation, and more. This comprehensive approach empowers users to streamline their processes and harness the full potential of automation technology.

Reasonix functions as an open-source coding agent tailored for extended autonomous sessions, ensuring that the code produced is readable, auditable, and reversible. It utilizes a single local engine that integrates with four different interfaces: terminal, desktop application, web browser, and ACP-compatible editors, sharing sessions, permissions, skills, and MCP servers among them. The plan mode retains all writes until the suggested steps undergo review and approval, while read, write, and shell commands are distinctly gated and limited within a secure workspace sandbox. Each action taken generates a checkpoint outside of Git, enabling users to revert to earlier points in a lengthy session without disrupting the commit history. Support for MCP through stdio, SSE, and streamable HTTP amalgamates external tools within a single registry, while Markdown skills and independent subagents enhance the agent's capabilities without necessitating a fork. Reasonix maintains a map of the codebase established at the outset, preserving that map for the entirety of the session, which allows users to organize tasks, examine differences, and continue their work seamlessly without sacrificing context. This design fosters an efficient workflow that minimizes the risk of losing track of ongoing projects.

Constellation Gate AI serves as an auxiliary defense mechanism for AI agents, positioned strategically between the agent and the model to filter all requests for potential threats and data leaks. This solution functions as an inline gateway for coding agents and model APIs, ensuring protection of workflows while eliminating the need for significant code modifications. Users can direct existing tools such as Claude Code, Cursor, OpenClaw, Codex, or OpenCode to utilize Gate, thereby gaining access to defenses against prompt injection, secret detection, PII redaction, token optimization, and a reliable audit trail. The platform specifically addresses three critical vulnerabilities: prompt injection attacks, leakage of credentials and PII, and unauthorized tool calls. Rather than depending on the model's self-defense mechanisms, Gate preemptively intercepts attacks before they penetrate the model, removes sensitive information prior to the return of responses, and prevents outputs from compromised tools before an agent can act on them. Gate is compatible with the existing calls made by agents, relaying them to the model while meticulously scanning each request and response in both directions, ensuring comprehensive protection against emerging threats. This proactive approach not only enhances security but also instills confidence in users about the integrity and safety of their AI workflows.

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.

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.

Confidential AI offers a secure platform for private AI inference, agent environments, and confidential computing solutions tailored for AI laboratories, inference service providers, routers, and organizations that manage sensitive data. Its hosted inference service operates open-weight models within hardware-backed trusted execution environments (TEEs), utilizing technologies such as Intel TDX and AMD SEV-SNP confidential virtual machines, paired with NVIDIA GPUs in a confidential computing configuration. The system ensures that prompts, responses, and workload information remain safeguarded from infrastructure operators, allowing clients to authenticate attestation prior to submitting sensitive information. Users have the flexibility to implement an OpenAI-compatible API to establish inference endpoints and agent workloads, or alternatively, they can acquire the confidential-computing stack for deployment on their own premises, bare metal servers, or across major cloud platforms. This service is particularly beneficial for scenarios that involve serving models while restricting operator access to prompts and model assets, as well as executing sensitive AI workloads in a dedicated confidential computing environment. Additionally, the emphasis on robust security measures fosters trust in the processing of sensitive data, enabling clients to focus on innovation without compromising privacy.

Sapiom serves as a financial and access infrastructure platform that allows AI agents and API-driven applications to securely access, provision, and pay for various third-party services, APIs, tools, and compute resources in real-time, eliminating the need for manual onboarding, individual management of API keys, and the necessity of pre-purchased credits. It features a centralized dashboard that enables organizations to keep track of overall spending, agent activities, service utilization, and real-time analytics, while also allowing the establishment of rule-based spending and usage limits, alongside the enforcement of governance policies to ensure that autonomous agents operate securely within set financial boundaries. Additionally, Sapiom offers SDKs and APIs that empower developers to link agents to a selective network of services, including verification processes, web searching, AI models through OpenRouter, and automation of image/audio generation and browser tasks, facilitating automated authentication and micro-payments for each use. This system meticulously tracks every API invocation, associated costs, and execution traces, ensuring comprehensive visibility and control over operations, which ultimately enhances the operational efficiency of organizations leveraging its capabilities.

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.