E2B Raises $21M to Build Cloud Infrastructure for AI Agents, Attracting 88% of Fortune 100 Companies

How E2B became essential to 88% of Fortune 100 companies and raised $21 million

Want smarter insights in your inbox? Sign up for our weekly newsletters to get only what matters to enterprise AI, data, and security leaders. Subscribe Now E2B, a startup providing cloud infrastructure specifically designed for artificial intelligence agents, has closed a $21 million Series A funding round led by Insight Partners, capitalizing on surging enterprise demand for AI automation tools. The funding comes as an remarkable 88% of Fortune 100 companies have already signed up to use E2B's platform, according to the company, highlighting the rapid enterprise adoption of AI agent technology. The round included participation from existing investors Decibel, Sunflower Capital, and Kaya, along with notable angels including Scott Johnston, former CEO of Docker. E2B's technology addresses a critical infrastructure gap as companies increasingly deploy AI agents -- autonomous software programs that can execute complex, multi-step tasks including code generation, data analysis, and web browsing. Unlike traditional cloud computing designed for human users, E2B provides secure, isolated computing environments where AI agents can safely run potentially dangerous code without compromising enterprise systems. "Enterprises have enormous expectations for AI agents. However, we're asking them to scale and perform on legacy infrastructure that wasn't designed for autonomous agents," said Vasek Mlejnsky, co-founder and CEO of E2B, in an exclusive interview with VentureBeat. "E2B solves this by equipping AI agents with safe, scalable, high-performance cloud infrastructure designed specifically for production-scale agent deployments." Seven-figure monthly revenue spike shows enterprises betting big on AI automation The funding reflects explosive revenue growth, with E2B adding "seven figures" in new business just in the past month, according to Mlejnsky. The company has processed hundreds of millions of sandbox sessions since October, demonstrating the scale at which enterprises are deploying AI agents. E2B's customer roster reads like a who's who of AI innovation: search engine Perplexity uses E2B to power advanced data analysis features for Pro users, implementing the capability in just one week. AI chip company Groq relies on E2B for secure code execution in its Compound AI systems. Workflow automation platform Lindy integrated E2B to enable custom Python and JavaScript execution within user workflows. The startup's technology has also become critical infrastructure for AI research. Hugging Face, the leading AI model repository, uses E2B to safely execute code during reinforcement learning experiments for replicating advanced models like DeepSeek-R1. Meanwhile, UC Berkeley's LMArena platform has launched over 230,000 E2B sandboxes to evaluate large language models' web development capabilities. Firecracker microVMs solve the dangerous code problem plaguing AI development E2B's core innovation lies in its use of Firecracker microVMs -- lightweight virtual machines originally developed by Amazon Web Services -- to create completely isolated environments for AI-generated code execution. This addresses a fundamental security challenge: AI agents often need to run untrusted code that could potentially damage systems or access sensitive data. "When talking to customers and special enterprises, their biggest decision is almost always build versus buy," Mlejnsky explained in an interview. "With the build versus buy solution, it all really comes down to whether you want to spend next six to 12 months building this hiring five to 10 person infrastructure team that will cost you at least half a million dollars...or you can use our plug and play solution." The platform supports multiple programming languages including Python, JavaScript, and C++, and can spin up new computing environments in approximately 150 milliseconds -- fast enough to maintain the real-time responsiveness users expect from AI applications. Enterprise customers particularly value E2B's open-source approach and deployment flexibility. Companies can self-host the entire platform for free or deploy it within their own virtual private clouds (VPCs) to maintain data sovereignty -- a critical requirement for Fortune 100 firms handling sensitive information. Perfect timing as Microsoft layoffs signal shift toward AI worker replacement The funding comes at a pivotal moment for AI agent technology. Recent advances in large language models have made AI agents increasingly capable of handling complex, real-world tasks. Microsoft recently laid off thousands of employees while expecting AI agents to perform previously human-only work, Mlejnsky pointed out in our interview. However, infrastructure limitations have constrained AI agent adoption. Industry data suggests fewer than 30% of AI agents successfully make it to production deployment, often due to security, scalability, and reliability challenges that E2B's platform aims to solve. "We're building the next cloud," Mlejnsky said, outlining the company's ambitious vision. "The current world runs on Cloud 2.0, which was made for humans. We're building the open-source cloud for AI agents where they can be autonomous and run securely." The market opportunity appears substantial. Code generation assistants already produce at least 25% of the world's software code, while JPMorgan Chase saved 360,000 hours annually through document processing agents. Enterprise leaders expect to automate 15% to 50% of manual tasks using AI agents, creating massive demand for supporting infrastructure. Open-source strategy creates defensive moat against tech giants like Amazon and Google E2B faces potential competition from cloud giants like Amazon, Google, and Microsoft, which could theoretically replicate similar functionality. However, the company has built competitive advantages through its open-source approach and focus on AI-specific use cases. "We don't really care" about the underlying virtualization technology, Mlejnsky explained, noting that E2B focuses on creating an open standard for how AI agents interact with computing resources. "We are even like actually partnering with a lot of these cloud providers too, because a lot of enterprise customers actually want to deploy E2B inside their AWS account." The company's open-source sandbox protocol has become a de facto standard, with hundreds of millions of compute instances demonstrating its real-world effectiveness. This network effect makes it difficult for competitors to displace E2B once enterprises have standardized on its platform. Alternative solutions like Docker containers, while technically possible, lack the security isolation and performance characteristics required for production AI agent deployments. Building similar capabilities in-house typically requires 5-10 infrastructure engineers and at least $500,000 in annual costs, according to Mlejnsky. Enterprise features like 24-hour sessions and 20,000 concurrent sandboxes drive Fortune 100 adoption E2B's enterprise success stems from features specifically designed for large-scale AI deployments. The platform can scale from 100 concurrent sandboxes on the free tier to 20,000 concurrent environments for enterprise customers, with each sandbox capable of running for up to 24 hours. Advanced enterprise features include comprehensive logging and monitoring, network security controls, and secrets management -- capabilities essential for Fortune 100 compliance requirements. The platform integrates with existing enterprise infrastructure while providing the granular controls security teams demand. "We have very strong inbound," Mlejnsky noted, describing the sales process. "Once we tackle the 87% we will come back for those 13%." Customer objections typically focus on security and privacy controls rather than fundamental technology concerns, indicating broad market acceptance of the core value proposition. Insight Partners' $21M bet validates AI infrastructure as next major software category Insight Partners' investment reflects growing investor confidence in AI infrastructure companies. The global software investor, which manages over $90 billion in regulatory assets, has invested in more than 800 companies worldwide and seen 55 portfolio companies achieve initial public offerings. "Insight Partners is excited to back E2B's visionary team as they pioneer essential infrastructure for AI agents," said Praveen Akkiraju, Managing Director at Insight Partners. "Such rapid growth and enterprise adoption can be difficult to achieve, and we believe that E2B's open-source sandbox standard will become a cornerstone of secure and scalable AI adoption across the Fortune 100 and beyond." The investment will fund expansion of E2B's engineering and go-to-market teams in San Francisco, development of additional platform features, and support for the growing customer base. The company plans to strengthen its open-source sandbox protocol as a universal standard while developing enterprise-grade modules like secrets vault and monitoring tools. The infrastructure play that could define enterprise AI's next chapter E2B's trajectory reveals a fundamental shift in how enterprises approach AI deployment. While much attention has focused on large language models and AI applications, the company's rapid adoption among Fortune 100 firms demonstrates that specialized infrastructure has become the critical bottleneck. The startup's success also highlights a broader trend: as AI agents transition from experimental tools to mission-critical systems, the underlying infrastructure requirements more closely resemble those of traditional enterprise software than consumer AI applications. Security, compliance, and scalability -- not just model performance -- now determine which AI initiatives succeed at scale. For enterprise technology leaders, E2B's emergence as essential infrastructure suggests that AI transformation strategies must account for more than just model selection and application development. The companies that successfully scale AI agents will be those that invest early in the specialized infrastructure layer that makes autonomous AI operation possible. In an era where AI agents are poised to handle an ever-growing share of knowledge work, the platforms that keep those agents running safely may prove more valuable than the agents themselves.

E2B shares its vision of sandboxed, cloud environments for every AI agent after raising $21M in funding - SiliconANGLE

E2B shares its vision of sandboxed, cloud environments for every AI agent after raising $21M in funding Agentic cloud infrastructure startup E2B said today it has raised $21 million in early-stage funding to build out an entirely new, open-source infrastructure for running artificial intelligence agents securely in the cloud. The startup, officially known as FoundryLabs Inc., said today's Series A round was led by Insight Partners and saw participation from Decibel, Sunflower Capital, Kaya and well-known angel investors such as former Docker Inc. Chief Executive Scott Johnston. E2B's vision is to provide businesses with a dedicated, open-source cloud infrastructure stack for AI agents. It believes that the best place for AI agents to be hosted is in secure sandboxed environments in the cloud, where it will provide them with safe computer and browser-use features to automate various complex business tasks. Co-founder and Chief Executive Vasek Mlejnsky (pictured, right, alongside co-founder and Chief Technology Officer Tomas Valenta) said he hit upon the idea for a dedicated, sandboxed cloud environment for AI agents after building his own agentic system. While doing that, he came to realize that existing cloud infrastructure has been designed specifically for humans rather than AI agents, and that it's not possible for them to use it efficiently. "How can we expect AI agents to do the same work as humans if we can't give them the same environment to use the tools we use?" he asked. Mlejnsky explained that enterprises have massive expectations for AI agents due to all the hype around them, but he believes that they won't easily scale if they're built on legacy infrastructure that's not designed to be used by them. "E2B solves this by equipping AI agents with safe, scalable and highly-performant cloud infrastructure, as well as tools that help agents to scale in production," he added. With E2B's sandboxed cloud environments, AI agents get access to the same computational capabilities as human workers do, meaning their own computer plus a browser and other tools that enable them to retrieve information, as well as a file system to store that data, and compute platforms for executing AI-generated code. Companies can quickly spin up and shut down these sandboxed cloud environments as needed, and they can scale rapidly to millions of virtual personal computers, allowing enterprises to unleash armies of agents that can work even more efficiently than humans do. It's all hosted in a simple and secure runtime that enables reinforcement loops for AI training and agentic workflows to run rapidly. "All of the main use cases we see for AI agents need not only high scale but also extremely high speed," Mlejnsky said. "Agents building a full website and making research reports need to give you an answer in a lower seconds. There's no other way to do this today, especially securely and no open-source alternative than us that customers can deploy inside their clouds." Holger Mueller of Constellation Research Inc. said E2B is making a good case, from both an architectural and a usability perspective, that agentic AI systems need their very own, specialized infrastructures. "The key will be how well E2B is able to use the funding to materialize this new architecture it's promising," the analyst added. "Enterprises will be watching, because we are moving toward an agentic future that's likely to come much sooner than later." E2B says its vision has been embraced by dozens of Fortune 500 companies, as well as AI industry leaders such as Hugging Face Inc., Perplexity AI Inc. and Manus. With the money from today's round, E2B aims to position its open-source sandbox protocol as the universal standard for AI agents, and has plans to add additional functionality such as "secrets vaults" and orchestration tools for managing fleets of AI agents from a single console. Praveen Akkiraju of Insight Partners said he believes E2B is pioneering "essential infrastructure" for AI agents and predicts its sandboxed cloud environments will become widely used in the near future: "We believe that E2B's open-source sandbox standard will become a cornerstone of secure and scalable AI adoption across the Fortune 100 and beyond."