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E2B Secures $21 Million in Series A Funding
E2B, a startup focused on cloud infrastructure specifically designed for artificial intelligence agents, has successfully completed a $21 million Series A funding round led by Insight Partners. This investment capitalizes on the increasing demand for AI automation tools within enterprises. Notably, 88% of Fortune 100 companies have already adopted E2B’s platform, underscoring the swift integration of AI agent technology in the corporate world.
Notable Investors and Participation
The funding round saw participation from existing investors such as Decibel, Sunflower Capital, and Kaya, along with prominent angel investors, including Scott Johnston, the former CEO of Docker. E2B’s technology addresses a significant infrastructure gap as organizations deploy AI agents—autonomous software programs capable of executing complex, multi-step tasks like code generation, data analysis, and web browsing.
Innovative Infrastructure for AI Agents
Unlike traditional cloud computing systems designed for human users, E2B offers secure and isolated computing environments where AI agents can run potentially hazardous code without jeopardizing 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,” stated Vasek Mlejnsky, co-founder and CEO of E2B, in an exclusive interview with VentureBeat. “E2B addresses this by providing AI agents with safe, scalable, high-performance cloud infrastructure specifically designed for production-scale agent deployments.”
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Explosive Growth and Client Success
The funding reflects impressive revenue growth, with E2B generating “seven figures” in new business within just the past month, according to Mlejnsky. The company has facilitated hundreds of millions of sandbox sessions since October, demonstrating the scale at which enterprises are deploying AI agents. E2B’s clientele includes notable names in AI innovation: the search engine Perplexity uses E2B to enhance advanced data analysis features for Pro users, implementing this capability in just one week. AI chip manufacturer Groq depends on E2B for secure code execution in its Compound AI systems, while workflow automation platform Lindy has integrated E2B to enable custom Python and JavaScript execution within user workflows.
Critical Infrastructure for AI Research
E2B’s technology has also become essential for AI research. Hugging Face, the leading AI model repository, employs E2B to safely execute code during reinforcement learning experiments aimed at replicating advanced models like DeepSeek-R1. Additionally, UC Berkeley’s LMArena platform has launched over 230,000 E2B sandboxes to assess large language models’ web development capabilities.
Addressing Security Challenges with MicroVMs
E2B’s core innovation lies in its use of Firecracker microVMs—lightweight virtual machines originally developed by Amazon Web Services—to create entirely isolated environments for AI-generated code execution. This innovation tackles a crucial security challenge: AI agents often need to execute untrusted code that could potentially harm systems or access sensitive data. “When discussing with customers and enterprises, the key decision is often build versus buy,” Mlejnsky elaborated. “With the build versus buy solution, it ultimately comes down to whether you want to invest the next six to twelve months building this with a team of five to ten people, costing at least half a million dollars, or utilize our plug-and-play solution.”
Versatile and Flexible Platform
The platform supports multiple programming languages, including Python, JavaScript, and C++, and can create new computing environments in approximately 150 milliseconds—quick enough to ensure real-time responsiveness that users expect from AI applications. Enterprise customers particularly appreciate 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 vital requirement for Fortune 100 firms managing sensitive information.
A Pivotal Moment for AI Agent Technology
This funding arrives at a crucial time for AI agent technology. Recent advancements in large language models have empowered AI agents to tackle increasingly complex, real-world tasks. Mlejnsky noted in our interview that Microsoft recently laid off thousands of employees, anticipating that AI agents will take over tasks previously performed solely by humans. However, infrastructure limitations have hindered the broader adoption of AI agents.