Need smarter insights in your inbox? Join our weekly newsletters to get solely what issues to enterprise AI, information, and safety leaders. Subscribe Now
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 exceptional 88% of Fortune 100 firms have already signed up to make use of E2B’s platform, in response to the corporate, highlighting the speedy enterprise adoption of AI agent expertise. The spherical included participation from present buyers Decibel, Sunflower Capital, and Kaya, together with notable angels together with Scott Johnston, former CEO of Docker.
E2B’s expertise addresses a vital infrastructure hole as firms more and more deploy AI brokers — autonomous software program packages that may execute complicated, multi-step duties together with code era, information evaluation, and net looking. In contrast to conventional cloud computing designed for human customers, E2B gives safe, remoted computing environments the place AI brokers can safely run doubtlessly harmful code with out compromising enterprise techniques.
“Enterprises have huge expectations for AI brokers. Nevertheless, 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.”
The AI Influence Sequence Returns to San Francisco – August 5
The following part of AI is right here – are you prepared? Be a part of leaders from Block, GSK, and SAP for an unique have a look at how autonomous brokers are reshaping enterprise workflows – from real-time decision-making to end-to-end automation.
Safe your spot now – area is restricted: https://bit.ly/3GuuPLF
Seven-figure month-to-month income spike exhibits enterprises betting large on AI automation
The funding displays explosive income progress, with E2B including “seven figures” in new enterprise simply prior to now month, in response to Mlejnsky. The corporate has processed a whole bunch of tens of millions of sandbox classes 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 information 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 person workflows.
The startup’s expertise has additionally turn out to be vital infrastructure for AI analysis. Hugging Face, the main AI mannequin repository, makes use of E2B to securely 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 judge giant language fashions’ net growth capabilities.
Firecracker microVMs remedy the damaging code downside plaguing AI growth
E2B’s core innovation lies in its use of Firecracker microVMs — light-weight digital machines initially developed by Amazon Internet Providers — to create fully remoted environments for AI-generated code execution. This addresses a basic safety problem: AI brokers usually have to run untrusted code that might doubtlessly injury techniques or entry delicate information.
“When speaking to prospects and particular enterprises, their largest choice is nearly all the time construct versus purchase,” Mlejnsky defined in an interview. “With the construct versus purchase answer, all of it actually comes down as to if you need to spend subsequent six to 12 months constructing this hiring 5 to 10 particular person infrastructure workforce that can price you no less than half one million {dollars}…or you need to use our plug and play answer.”
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 anticipate from AI purposes.
Enterprise prospects significantly worth E2B’s open-source method and deployment flexibility. Firms can self-host the complete platform without cost or deploy it inside their very own digital personal clouds (VPCs) to take care of information sovereignty — a vital requirement for Fortune 100 companies dealing with delicate info.
Good timing as Microsoft layoffs sign shift towards AI employee substitute
The funding comes at a pivotal second for AI agent expertise. Current advances in giant language fashions have made AI brokers more and more able to dealing with complicated, real-world duties. Microsoft not too long ago laid off hundreds of staff whereas anticipating AI brokers to carry out beforehand human-only work, Mlejnsky identified in our interview.
Nevertheless, infrastructure limitations have constrained AI agent adoption. Business information suggests fewer than 30% of AI brokers efficiently make it to manufacturing deployment, usually as a result of safety, scalability, and reliability challenges that E2B’s platform goals to resolve.
“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 no less than 25% of the world’s software program code, whereas JPMorgan Chase saved 360,000 hours yearly by doc processing brokers. Enterprise leaders anticipate to automate 15% to 50% of handbook duties utilizing AI brokers, creating huge 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. Nevertheless, the corporate has constructed aggressive benefits by its open-source method and concentrate on 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 a way AI brokers work together with computing sources. “We’re even like really partnering with numerous these cloud suppliers too, as a result of numerous enterprise prospects really need to deploy E2B inside their AWS account.”
The corporate’s open-source sandbox protocol has turn out to be a de facto normal, with a whole bunch of tens of millions of compute cases demonstrating its real-world effectiveness. This community impact makes it tough for rivals to displace E2B as soon as enterprises have standardized on its platform.
Different options like Docker containers, whereas technically potential, lack the safety isolation and efficiency traits required for manufacturing AI agent deployments. Constructing comparable capabilities in-house usually requires 5-10 infrastructure engineers and no less than $500,000 in annual prices, in response to Mlejnsky.
Enterprise options like 24-hour classes 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 prospects, with every sandbox able to working for as much as 24 hours.
Superior enterprise options embrace complete logging and monitoring, community safety controls, and secrets and techniques administration — capabilities important for Fortune 100 compliance necessities. The platform integrates with present enterprise infrastructure whereas offering the granular controls safety groups demand.
“We now have very sturdy inbound,” Mlejnsky famous, describing the gross sales course of. “As soon as we deal with the 87% we’ll come again for these 13%.” Buyer objections usually concentrate on safety and privateness controls fairly 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 firms. The worldwide software program investor, which manages over $90 billion in regulatory property, has invested in additional than 800 firms worldwide and seen 55 portfolio firms obtain preliminary public choices.
“Perception Companions is worked up to again E2B’s visionary workforce as they pioneer important infrastructure for AI brokers,” stated Praveen Akkiraju, Managing Director at Perception Companions. “Such speedy progress and enterprise adoption might be tough to attain, and we imagine that E2B’s open-source sandbox normal will turn out to be 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 further platform options, and assist 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 centered on giant language fashions and AI purposes, the corporate’s speedy adoption amongst Fortune 100 companies demonstrates that specialised infrastructure has turn out to be the vital 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 carefully resemble these of conventional enterprise software program than shopper AI purposes. 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 potential.
In an period the place AI brokers are poised to deal with an ever-growing share of information work, the platforms that maintain these brokers working safely could show extra worthwhile than the brokers themselves.
