When using AI Agents like Manus, Genspark, ChatGPT Agent, and GitHub Spark, I often wonder how these agents create and manage their runtime environments—do they use container technology, or is there specialized infrastructure? With this question in mind, I researched the current mainstream cloud agent runtime solutions and found E2B and Browserbase to be prominent representatives. Each offers innovative agent infrastructure in the fields of “code sandboxing” and “browser automation.” This article analyzes their technical architectures and application patterns to understand the latest trends in AI Agent runtime environments.
Click to toggle the mind map - E2B and Browserbase Mind Map
Company Background and History
E2B (Enterprise to Bot) was founded in 2023 by Václav Mlejnský (aka Vasek) and Tomáš Valenta, close friends who graduated from the Czech Academy of Mathematics and Physics. After collaborating in computer vision, they were inspired by GPT-3.5 to build AI Agent infrastructure. E2B was established as an open-source cloud platform for AI Agent runtime, giving each agent its own cloud “mini computer.” Early on, E2B secured $3 million in pre-seed funding led by Kaya VC and Sunflower Capital, with notable entrepreneurs like Vercel CEO Guillermo Rauch participating. In less than a year, E2B announced a $11.5 million seed round in 2024 (led by Decibel Partners’ Alessio Fanelli), and the latest $21 million Series A was completed in July 2025, led by Insight Partners, bringing total funding to about $32 million. Headquartered in San Francisco, E2B is rapidly expanding to meet global demand.
Browserbase is a San Francisco-based startup founded by Paul Klein IV in early 2024. Klein, a former Twilio engineer and successful entrepreneur in live streaming software, has deep experience in large-scale browser automation. Browserbase focuses on providing cloud-based headless browser infrastructure, enabling developers and AI Agents to automate complex web tasks. In June 2024, Browserbase launched its open registration platform and announced $6.5 million seed funding led by Kleiner Perkins. Just nine months later, Browserbase completed a $21 million Series A in November 2024 (led by CRV and Kleiner Perkins, with Okta participating). In June 2025, the company raised another $40 million Series B led by Notable Capital, reaching a $300 million valuation—nearly quadruple its Series A. By mid-2025, Browserbase had grown to 30 employees and over 1,000 paying customers in just 16 months. The following chart shows key milestones for both companies:

Core Product Overview
E2B’s core product is a platform providing cloud sandbox environments for AI Agents. Built on an open architecture, it allows each agent to instantly obtain an isolated, secure virtual computer with real-world development tools and OS environments. Agents can safely execute code, access the file system, run terminal commands, and even connect to the internet, enabling complex multi-step tasks. E2B emphasizes high security and scalability: sandboxes use hardened isolation technology and support elastic scaling of thousands of instances on public or private clouds. Developers can use E2B’s JavaScript/TypeScript or Python SDK to launch and control sandboxes via API. Typical features and scenarios include:
- Code execution and analysis: Agents get a code interpreter environment to run Python, JS, etc., for data analysis and reporting (e.g., Perplexity launched code analysis in one week using E2B).
- Automation tasks: Agents execute scripts to automate internal enterprise tasks (JP Morgan saves 360,000 man-hours annually with similar agents).
- Research and reinforcement learning: Researchers launch thousands of sandboxes in parallel for AI strategy evaluation and RL simulation.
- Virtual interaction environments: The E2B Desktop module provides cloud desktops with GUIs, allowing LLMs to operate graphical applications (“Computer Use” scenarios).
E2B sandboxes support any programming language and framework, plug-and-play. Developers can execute agent code snippets and return results in a few lines. Sandboxes have ultra-low startup latency (near-instant), can run for extended periods, and offer monitoring/logging tools for agent behavior tracking. E2B aims to become the open standard and interface for agent infrastructure, planning to support Linux containers, Windows VMs, headless browsers, and multi-cloud deployments (Kubernetes, AWS, Azure). Its complete, open-source platform has become a de facto standard for enterprise agent workflows.
Browserbase’s core product is a cloud platform for large-scale headless browser operation. It provides “Web Browser as a Service” for AI applications and automation scripts, enabling agents to interact with web pages like humans—without a real GUI. Key features include:
- Large-scale browser clusters: Developers can launch tens, hundreds, or thousands of cloud browser instances via API for parallel tasks. By 2025, the platform had run over 50 million browser sessions, with 25 million in the first half of 2025 alone.
- Headless browser automation: Supports major frameworks like Puppeteer, Playwright, and Selenium. Developers write scripts as usual, and Browserbase hosts and executes them in the cloud.
- Advanced web interaction: Provides robust browser environments with advanced debugging, session recording/playback, global proxy networks, and anti-bot detection to ensure reliable automation.
- Complex operations and data extraction: Supports not just scraping, but full user workflows—auto-login, form filling, cart operations, etc.—plus APIs for structured data extraction and screenshots.
Browserbase is positioned as a key component in the AI software stack, described as the “eyes and ears” for AI applications, enabling LLMs (“brains”) to interact with the internet. For example, an agent can use Browserbase to search and book flights or fill out enterprise web reports. As automation needs grow, Browserbase launched “Director,” a no-code web automation tool for non-developers. Director uses AI to generate browser scripts from prompts, expanding Browserbase’s reach to broader enterprise users.
In summary, E2B focuses on general code execution sandboxes for agent computation/programming, while Browserbase specializes in web interaction, giving agents “frontend” capabilities. Both are vital parts of Agent Infra, supporting next-gen intelligent agent applications.
Business Models and Customer Base
E2B’s business model is “open-source core + cloud service upsell.” The core tech is open-source and free for developers, but E2B offers hosted sandbox cloud services. The official cloud uses SaaS subscription + usage-based billing: the “Hobby” plan is free (with $100 compute credits, no credit card required); the “Pro” plan is $150/month for higher concurrency and longer sessions, plus usage-based fees. Usage is measured by CPU seconds and memory (e.g., 2-core sandbox costs $0.000028/s, memory $0.0000045/GiB/s). Enterprises can choose the “Ultimate” plan for custom deployment/support. E2B also provides self-hosting options via open-source Terraform scripts for AWS, GCP, Azure, etc. This open + commercial model attracts developer communities and monetizes enterprise services. Major customers include tech companies and large enterprises needing AI Agents: Hugging Face and LMArena use E2B for safe AI scaling; Perplexity launched code analysis for paid users in one week; Groq uses E2B for secure code execution. E2B claims 88% of Fortune 100 companies have registered for trials, showing traditional enterprises are exploring agent adoption. E2B helps lower development costs for AI automation while ensuring security/compliance, earning high recognition.
Browserbase’s business model is a classic cloud API service. Developers pay for API access based on browser instance count and duration. This usage-based model allows small-scale initial use, with spending growing as applications scale. By 2025, Browserbase had $3 million+ annual recurring revenue, mainly from expanding usage by existing customers. Free credits/trials and open registration attract developers. Browserbase also focuses on enterprise needs, especially security/compliance: after Series A, it began SOC2 Type1 and HIPAA audits for healthcare/finance clients. The new Director no-code tool may expand to premium subscriptions or seat-based licensing for non-technical users, targeting SMBs with automation needs. Current customers include tech companies of all sizes: AI Agent startups, B2B SaaS, professional services, risk/marketing teams, and web UI test developers. Known users include Commure (health data), Perplexity (search), Vercel (frontend cloud), and over 1,000 companies. As Director lowers the barrier, Browserbase may penetrate non-internet industries, offering AI-driven browser automation for broader business scenarios.
In summary, both E2B and Browserbase use a developer-centric growth strategy: free/open-source tools build momentum, then enterprise features/services drive monetization. Each solves clear pain points—code sandboxing and browser automation—with proven demand. As AI transforms traditional industries, their business models are highly scalable and sustainable.
Open Source Ecosystem
Both companies prioritize open source, actively releasing projects to expand developer influence and improve products via community feedback.
E2B’s core code is open-source under Apache 2.0, with the GitHub repo E2B (e2b-dev/E2B). It provides SDKs for launching/controlling cloud sandboxes and self-hosting guides. The repo has ~9.4k stars, 650+ forks, and a vibrant community. Developers can freely view/modify code and contribute via PRs. Beyond the core SDK, E2B also open-sourced E2B Desktop, a sandbox solution for LLMs to connect to graphical desktops, supporting screen streaming and remote control. This repo has ~1.1k stars. E2B’s stack is mainly TypeScript/Node.js (backend/SDK) and Python (bindings), with Terraform for cloud-agnostic deployment. The community maintains a Cookbook knowledge base with code samples for various LLM/framework integrations. E2B’s open source builds technical transparency and reliability, with millions of monthly SDK downloads from npm/PyPI. The Discord channel (thousands of members) enables rapid feedback and iteration.
Browserbase open-sources key tools to embrace the developer ecosystem. The flagship project is Stagehand—an AI-driven browser automation framework. Released in late 2024, Stagehand translates natural language instructions into browser automation code. Developers can mix code and AI for web operations: use Playwright for known flows, let AI generate steps for uncertain parts. Stagehand offers preview/caching and integrates OpenAI/Anthropic’s “Computer Use” models, greatly simplifying browser agent development. Licensed under MIT, Stagehand has ~16.6k stars and 1k+ forks, showing explosive popularity. There’s also a Python version for broader language support. Another key open-source module is Browserbase MCP Server, implementing the “Model Context Protocol” for standardizing LLM integration with external tools/data. MCP Server lets LLMs call Browserbase cloud browser features (screenshots, form filling, data extraction). This repo has 2.5k+ stars and is widely used by agent developers. Browserbase also publishes sample projects like Open Operator, showing how to build web agent apps with Next.js, React, Browserbase, and Stagehand. The SDK clients (Node.js/Python) are open-source for easy review/customization. Most Browserbase projects use TypeScript/JavaScript, leveraging modern frontend/cloud-native stacks, with Slack as the main community hub. Founders like Paul Klein are active in open source, answering questions and seeking feedback. Stagehand is now a de facto standard for browser automation, with developers calling it the “natural choice.” This thriving open-source ecosystem feeds back into Browserbase’s commercial products, integrating community innovations and enhancing competitiveness.
Note: All data as of September 2025.
E2B vs. Browserbase Comparison
After exploring the technical architectures and ecosystems of E2B and Browserbase, here’s a systematic comparison across core positioning, main features, target users, business models, and open-source ecosystems. The table below helps readers quickly grasp the similarities, differences, and advantages of these cloud agent infrastructure platforms.
Comparison Dimension | E2B (AI Sandbox Cloud) | Browserbase (Cloud Browser Platform) |
---|---|---|
Core Positioning | Open-source cloud sandbox, giving AI Agents code execution and compute environments; called “the cloud computer for AI agents” | Hosted browser infrastructure, providing high-performance headless browser clusters for AI; seen as “the internet interface for AI” |
Main Features | ⚡Instant sandbox: Launch isolated Linux VMs/containers in seconds, with sudo and dev tools; ⚡ Secure execution: Agents safely run any code/scripts, support file I/O, networking; ⚡ Persistent sessions: Long-running sandboxes, stateful tasks; ⚡ Multi-cloud: Deploy on public/local clouds | ⚡Browser automation: Run Chrome/Firefox headless browsers in the cloud, compatible with Puppeteer/Playwright; ⚡ Web interaction: Agents simulate user actions—click, fill forms, screenshot, scrape; ⚡ Anti-interference: Detection resistance, global proxies; ⚡ Visual orchestration: Director tool generates automation scripts from natural language |
Target Users | AI app developers, data scientists, innovation teams; tech companies/researchers needing LLM code execution/automation; now adopted by some Fortune 100 enterprises | Initially AI Agent startups, web automation developers; expanding to non-coders (operations, marketing) using AI for business automation; covers global SMBs |
Business Model | Open-source + cloud service: Core code is free; official SaaS charges by subscription/usage; custom deployment/support for large enterprises | Online API service: Free trials for developers, usage-based billing; premium features (global regions, enterprise auth), no-code tools expand paid options; investors/cloud vendors as ecosystem partners |
Open Source | Core Sandbox SDK open (9k+⭐); desktop GUI sandbox open (1k+⭐); active Discord community, plugins/tutorials | Open-source AI browser framework Stagehand (16k+⭐); MCP integration module (2.5k⭐); official Node/Python SDKs; active Slack community, frequent joint innovation |
Both E2B and Browserbase focus on vertical domains and actively embrace open source. E2B specializes in “runtime/sandbox,” providing secure, isolated code execution for AI Agents, integrating with memory/planning modules. Browserbase leads in browser interaction, optimizing cloud browser automation and open-source frameworks. Technically, E2B supports AWS, Azure, and major clouds, compatible with various LLMs; Browserbase supports OpenAI, Anthropic, and offers rich open-source tools/SDKs. Both use developer-centric SaaS models, targeting innovative companies and enterprise clients in Western markets. Through ongoing tech iteration and community co-creation, they’ve secured leadership in AI Agent infrastructure.
Global Market Impact and Trends
Worldwide, AI Agent infrastructure is a new hot track in AI. In Western markets, E2B and Browserbase are leading players:
- Industry adoption: E2B’s sandbox is a de facto standard for agent code execution, used by hundreds of enterprises from Fortune 100 to cloud startups. Browserbase has made “AI controlling browsers” a reality, with Stagehand’s 16k+ GitHub stars showing global developer adoption. Many third-party projects now integrate Browserbase/Stagehand for AI web automation, strengthening their market position.
- Capital and valuation: Both companies have raised large rounds and high valuations, showing investor confidence. Browserbase reached a $300M valuation in under two years, backed by top Silicon Valley funds. E2B, though European, attracted global investors like Insight Partners. Ample funding accelerates R&D and global expansion.
- Product evolution: E2B and Browserbase are rapidly upgrading, expanding features. E2B plans more environment types (Windows, browser) and modular extensions (secret management, sandbox monitoring), aiming for a universal, open standard. Browserbase is moving from dev tools to no-code platforms, democratizing browser automation. Expect convergence/competition with traditional RPA in the future.
Open source plays a key role in this field. It’s the core strategy for AI infrastructure. E2B and Browserbase have built strong developer ecosystems, signaling a future of open collaboration and interoperability via standards/protocols.
Summary
AI Agent infrastructure is experiencing rapid growth and evolution globally. As E2B’s co-founder said: “Just as iPhone apps need iOS, every intelligent agent will rely on its own secure compute environment.” In the next 5–10 years, infrastructure giving AI Agents “bodies and tools” will be as ubiquitous as cloud computing, forming a new digital economy foundation. Western innovation and Asian scale will drive maturity. E2B and Browserbase have established early leadership in tech and community. As the “Agent Era” begins, the global tech ecosystem is racing to make AI work better for humanity. Driven by multiple forces, AI Agent infrastructure will see rapid iteration and standardization, becoming a key accelerator for next-gen AI adoption.
References
- E2B Co-founder Interview - therecursive.com
- E2B Funding Report (The Recursive) - therecursive.com
- E2B Official Funding Announcement (July 2025) - e2b.dev
- E2B Funding Press Release (PR Newswire) - prnewswire.com
- E2B Official Docs - docs.e2b.dev
- Browserbase Funding Report (VentureBeat) - venturebeat.com
- Browserbase Series A (Pulse 2.0) - pulse2.com
- Browserbase Series B Report (Upstarts Media) - upstarts.media
- E2B GitHub Repo - github.com
- Browserbase Stagehand GitHub - github.com
- Browserbase MCP Server GitHub - github.com