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E2B, a startup offering cloud infrastructure particularly designed for synthetic intelligence brokers, has closed a $21 million Sequence A funding spherical led by Perception Companions, capitalizing on surging enterprise demand for AI automation instruments.
The funding comes as an outstanding 88% of Fortune 100 corporations have already signed up to make use of E2B’s platform, in line with the corporate, highlighting the fast enterprise adoption of AI agent expertise. The spherical included participation from current traders Decibel, Sunflower Capital, and Kaya, together with notable angels together with Scott Johnston, former CEO of Docker.
E2B’s expertise addresses a crucial infrastructure hole as corporations more and more deploy AI brokers — autonomous software program applications that may execute advanced, multi-step duties together with code era, knowledge evaluation, and net shopping. In contrast to conventional cloud computing designed for human customers, E2B offers safe, remoted computing environments the place AI brokers can safely run doubtlessly harmful code with out compromising enterprise techniques.
“Enterprises have monumental expectations for AI brokers. Nonetheless, we’re asking them to scale and carry out on legacy infrastructure that wasn’t designed for autonomous brokers,” stated Vasek Mlejnsky, co-founder and CEO of E2B, in an unique interview with VentureBeat. “E2B solves this by equipping AI brokers with secure, scalable, high-performance cloud infrastructure designed particularly for production-scale agent deployments.”
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Seven-figure month-to-month income spike reveals enterprises betting huge on AI automation
The funding displays explosive income progress, with E2B including “seven figures” in new enterprise simply previously month, in line with Mlejnsky. The corporate has processed tons of of thousands and thousands of sandbox periods since October, demonstrating the size at which enterprises are deploying AI brokers.
E2B’s buyer roster reads like a who’s who of AI innovation: search engine Perplexity makes use of E2B to energy superior knowledge evaluation options for Professional customers, implementing the potential in only one week. AI chip firm Groq depends on E2B for safe code execution in its Compound AI techniques. Workflow automation platform Lindy built-in E2B to allow customized Python and JavaScript execution inside consumer workflows.
The startup’s expertise has additionally change into crucial infrastructure for AI analysis. Hugging Face, the main AI mannequin repository, makes use of E2B to soundly execute code throughout reinforcement studying experiments for replicating superior fashions like DeepSeek-R1. In the meantime, UC Berkeley’s LMArena platform has launched over 230,000 E2B sandboxes to guage massive language fashions’ net growth capabilities.
Firecracker microVMs clear up the damaging code drawback plaguing AI growth
E2B’s core innovation lies in its use of Firecracker microVMs — light-weight digital machines initially developed by Amazon Internet Companies — to create fully remoted environments for AI-generated code execution. This addresses a basic safety problem: AI brokers typically must run untrusted code that might doubtlessly harm techniques or entry delicate knowledge.
“When speaking to clients and particular enterprises, their greatest choice is nearly at all times construct versus purchase,” Mlejnsky defined in an interview. “With the construct versus purchase resolution, all of it actually comes down as to if you need to spend subsequent six to 12 months constructing this hiring 5 to 10 individual infrastructure workforce that may value you a minimum of half 1,000,000 {dollars}…or you need to use our plug and play resolution.”
The platform helps a number of programming languages together with Python, JavaScript, and C++, and might spin up new computing environments in roughly 150 milliseconds — quick sufficient to take care of the real-time responsiveness customers count on from AI functions.
Enterprise clients significantly worth E2B’s open-source method and deployment flexibility. Corporations can self-host the complete platform without cost or deploy it inside their very own digital personal clouds (VPCs) to take care of knowledge sovereignty — a crucial requirement for Fortune 100 corporations dealing with delicate data.
Good timing as Microsoft layoffs sign shift towards AI employee alternative
The funding comes at a pivotal second for AI agent expertise. Latest advances in massive language fashions have made AI brokers more and more able to dealing with advanced, real-world duties. Microsoft just lately laid off hundreds of staff whereas anticipating AI brokers to carry out beforehand human-only work, Mlejnsky identified in our interview.
Nonetheless, infrastructure limitations have constrained AI agent adoption. Business knowledge suggests fewer than 30% of AI brokers efficiently make it to manufacturing deployment, typically on account of safety, scalability, and reliability challenges that E2B’s platform goals to unravel.
“We’re constructing the following cloud,” Mlejnsky stated, outlining the corporate’s bold imaginative and prescient. “The present world runs on Cloud 2.0, which was made for people. We’re constructing the open-source cloud for AI brokers the place they are often autonomous and run securely.”
The market alternative seems substantial. Code era assistants already produce a minimum of 25% of the world’s software program code, whereas JPMorgan Chase saved 360,000 hours yearly by doc processing brokers. Enterprise leaders count on to automate 15% to 50% of guide duties utilizing AI brokers, creating large demand for supporting infrastructure.
Open-source technique creates defensive moat towards tech giants like Amazon and Google
E2B faces potential competitors from cloud giants like Amazon, Google, and Microsoft, which may theoretically replicate comparable performance. Nonetheless, the corporate has constructed aggressive benefits by its open-source method and give attention to AI-specific use circumstances.
“We don’t actually care” concerning the underlying virtualization expertise, Mlejnsky defined, noting that E2B focuses on creating an open normal for the way AI brokers work together with computing assets. “We’re even like really partnering with quite a lot of these cloud suppliers too, as a result of quite a lot of enterprise clients really need to deploy E2B inside their AWS account.”
The corporate’s open-source sandbox protocol has change into a de facto normal, with tons of of thousands and thousands of compute cases demonstrating its real-world effectiveness. This community impact makes it troublesome for opponents to displace E2B as soon as enterprises have standardized on its platform.
Different options like Docker containers, whereas technically doable, lack the safety isolation and efficiency traits required for manufacturing AI agent deployments. Constructing comparable capabilities in-house sometimes requires 5-10 infrastructure engineers and a minimum of $500,000 in annual prices, in line with Mlejnsky.
Enterprise options like 24-hour periods and 20,000 concurrent sandboxes drive Fortune 100 adoption
E2B’s enterprise success stems from options particularly designed for large-scale AI deployments. The platform can scale from 100 concurrent sandboxes on the free tier to twenty,000 concurrent environments for enterprise clients, with every sandbox able to working for as much as 24 hours.
Superior enterprise options embody complete logging and monitoring, community safety controls, and secrets and techniques administration — capabilities important for Fortune 100 compliance necessities. The platform integrates with current enterprise infrastructure whereas offering the granular controls safety groups demand.
“We’ve got very robust inbound,” Mlejnsky famous, describing the gross sales course of. “As soon as we sort out the 87% we’ll come again for these 13%.” Buyer objections sometimes give attention to safety and privateness controls quite than basic expertise considerations, indicating broad market acceptance of the core worth proposition.
Perception Companions’ $21M guess validates AI infrastructure as subsequent main software program class
Perception Companions‘ funding displays rising investor confidence in AI infrastructure corporations. The worldwide software program investor, which manages over $90 billion in regulatory belongings, has invested in additional than 800 corporations worldwide and seen 55 portfolio corporations obtain preliminary public choices.
“Perception Companions is happy to again E2B’s visionary workforce as they pioneer important infrastructure for AI brokers,” stated Praveen Akkiraju, Managing Director at Perception Companions. “Such fast progress and enterprise adoption may be troublesome to attain, and we imagine that E2B’s open-source sandbox normal will change into a cornerstone of safe and scalable AI adoption throughout the Fortune 100 and past.”
The funding will fund growth of E2B’s engineering and go-to-market groups in San Francisco, growth of extra platform options, and help for the rising buyer base. The corporate plans to strengthen its open-source sandbox protocol as a common normal whereas creating enterprise-grade modules like secrets and techniques vault and monitoring instruments.
The infrastructure play that might outline enterprise AI’s subsequent chapter
E2B’s trajectory reveals a basic shift in how enterprises method AI deployment. Whereas a lot consideration has targeted on massive language fashions and AI functions, the corporate’s fast adoption amongst Fortune 100 corporations demonstrates that specialised infrastructure has change into the crucial bottleneck.
The startup’s success additionally highlights a broader development: as AI brokers transition from experimental instruments to mission-critical techniques, the underlying infrastructure necessities extra intently resemble these of conventional enterprise software program than client AI functions. Safety, compliance, and scalability — not simply mannequin efficiency — now decide which AI initiatives succeed at scale.
For enterprise expertise leaders, E2B’s emergence as important infrastructure means that AI transformation methods should account for extra than simply mannequin choice and utility growth. The businesses that efficiently scale AI brokers might be those who make investments early within the specialised infrastructure layer that makes autonomous AI operation doable.
In an period the place AI brokers are poised to deal with an ever-growing share of information work, the platforms that preserve these brokers working safely might show extra beneficial than the brokers themselves.
