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

E2B, an emerging company that provides cloud infrastructure designed specifically for artificial intelligence agents, has closed a funding round of the AER 21 million chain led by Insight Partners, and benefited from the high demand for institutions for artificial intelligence automation tools.

Funding comes as 88 % of the Fortune 100 companies that have already participated to use the E2B platform, according to the company, with highlighting the AI Agen rapid adoption. The tour included the participation of current investors Despell, Rabver Capital, and Kaya, along with prominent angels including Scott Johnston, former CEO of Docker.

E2B technology deals with a critical infrastructure gap as companies grow in an artificial intelligence agents-independent programs programs that can carry out complex multi-step tasks including generating code, data analysis and web browsing. Unlike the traditional cloud computing designed for human users, E2B provides secluded and isolated computing environments where artificial intelligence factors can operate a possible dangerous symbol safely without prejudice to the institution’s systems.

“Institutions have huge expectations for artificial intelligence agents, however, we ask them to expand and perform on ancient infrastructure that were not designed for independent factors,” said Vasik Minsky, co -founder and CEO of E2B. “This E2B replaces this by preparing artificial intelligence agents with safe, developed and highly -designated cloud infrastructure designed to spread the agent on the production scale.”

The height of the monthly revenue from seven monthly numbers for betting projects appears to automate artificial intelligence

Funding reflects the growth of explosive revenue, as E2B adds “seven numbers” in new business last month, according to MLJNSKY. The company has dealt with hundreds of millions of Sandbox sessions since October, indicating the scale in which institutions have published artificial intelligence agents.

You read the E2B Customer menu such as the WHO WHO from AI Innovation: The Perplexity E2B search engine is used to operate the advantages of advanced data analysis for professional users, and implement the ability in only one week. AI Chip Groq depends on E2B to implement a safe code in the vehicle AI systems. Lindy Integrated E2B platform to enable Python and JavaScript to be intended within the user’s workflow.

The startup technology has also become a critical infrastructure for artificial intelligence research. Huging Face, a pioneering AI model, is used to implement software instructions safely during reinforcement learning experiments to repeat advanced models such as Deepseek-R1. Meanwhile, the LMARNA platform from the University of California at Berkeley launched more than 230,000 E2B sand boxes to assess the possibilities of developing web models.

Microvms Microvms solve the serious code problem that suffers from artificial intelligence development

The basic innovation of E2B is to use it for MicroVMs for firearms-light-weight virtual devices originally developed by Amazon Web Services-to create completely isolated environments to implement code created from artificial intelligence. This addresses a basic challenge of safety: Artificial intelligence agents often need to run an unreliable code that can destroy sensitive systems or data.

“When speaking to customers and private institutions, their greatest decision is always based on purchase,” MLJNSKY explained in an interview. “By solving Build against Buy Buy, everything is due to whether you want to spend the six to 12 months in building this employment from five to 10 people in the infrastructure that will cost you at least half a million dollars … or you can use our components and operation solution.”

The platform supports multiple programming languages including Python, JavaScript and C ++, and new computing environments can rotate at about 150 milliliters-enough speed to keep users ’response in the actual time of artificial intelligence applications.

The Corporation’s customers in particular estimate the open source E2B approach and the elasticity of publishing. Companies can host the entire basic system for free or publish it within their virtual private clouds (VPCS) to maintain data-a decisive requirement for Fortune 100 companies that deal with sensitive information.

Ideal timing with Microsoft’s transformation for the signal to replace the artificial intelligence factor

Funding comes in a pivotal moment of artificial intelligence agent technology. Modern developments in large language models have made artificial intelligence agents increasingly able to deal with complex tasks in the real world. MLJNSKY indicated in our interview.

However, infrastructure restrictions may restrict the adoption of artificial intelligence agent. Industry data indicates that less than 30 % of artificial intelligence agents succeed in publishing publishing, often due to safety, expansion and reliability that the E2B platform aims to solve.

“We build the next cloud,” said MLJNSKY, which defines the ambitious vision of the company. “The current world is working on Cloud 2.0, which has been made for humans. We are building an open source cloud for artificial intelligence agents as it can be independent and operate safely.”

The market opportunity looks great. The code generation aides already produce at least 25 % of the world software code, while JPMorgan Chase 360,000 hours annually through document processing agents. Institutional leaders expect 15 % automation to 50 % of manual tasks using artificial intelligence agents, creating a huge demand to support infrastructure.

An open source strategy creates a defensive trench against technology giants such as Amazon and Google

E2B faces a possible competition from cloud giants like Amazon, Google and Microsoft, which can theoretically repeat similar functions. However, the company built competitive advantages through its open source approach and focus on the prosecution’s use cases.

“We are not really interested” in the basic virtual simulation technology, noting that the E2B focuses on creating an open standard for how artificial intelligence agents interact with computerized resources. “We are actually like partnership with many cloud service providers as well, because many institutions agents really want to publish E2B within their AWS account.”

The company’s open sand fund protocol has become a actual standard, as hundreds of millions of mathematical cases show their effectiveness in the real world. This network effect makes it difficult for competitors to displace E2B once institutions are unified on their basic system.

Alternative solutions such as Docker containers, although technically possible, lacks security isolation and performance characteristics required to publish AI production agent. Building similar capabilities at home usually requires 5-10 infrastructure engineers and at least $ 500,000 at annual costs, according to MLJNSKY.

Foundation’s features such as 24 -hour sessions and 20,000 synchronized sand boxes lead Fortune 100

The E2B success of the institution stems from the features specially designed to spread artificial intelligence on a large scale. The platform can expand a range of 100 simultaneous sandy boxes at a free level to 20,000 simultaneous environments for institutions customers, with each sand box capable of up to 24 hours.

The advanced institution features include comprehensive registration and monitoring, network safety controls, secret management – the basic capabilities of Fortune 100 compliance requirements. The statute is integrated with the infrastructure of current institutions while providing demand for security control teams.

“Our very strong”, MLJNSKY indicated, describing the sales process. “Once we deal with 87 %, we will return to these 13 %.” Customer objections usually focus on security and privacy controls instead of basic technology concerns, indicating the acceptance of the wide market for the basic proposal of value.

Bet Insight Partners’ $ 2 million, verifying the health of the infossible infrastructure

Insight Partners Investment reflects the increasing investor confidence in Amnesty International’s infrastructure companies. The global software investor, which runs more than 90 billion dollars in organizational assets, has invested in more than 800 companies worldwide and has seen 55 portfolio companies achieving primary public offers.

“Insight Partners is enthusiastic to support the E2B insight team because it is a leader in the basic infrastructure of artificial intelligence agents,” said Bravin Akirajo, Managing Director of Insight Partners. “It may be difficult to achieve such a rapid growth and the adoption of institutions, and we believe that the standard of the open sand fund for sources in E2B will become the cornerstone of the adoption of safe and developmental artificial intelligence via Fortune 100 and beyond.”

This investment will finance expansion in E2B engineering and engineering teams in San Francisco, develop additional platform features, and support the growing customer base. The company plans to enhance the open source sand fund protocol as a global standard with the development of units of the Foundation category such as secrets in the cellar and monitoring tools.

The infrastructure play that can determine the next chapter of the Foundation AI

E2B path reveals a basic shift in how institutions deal with spreading artificial intelligence. Although a lot of attention has focused on large language models and artificial intelligence applications, the company’s rapid dependence between the Fortune 100 companies shows that the specialized infrastructure has become a critical bottleneck.

The start of the startup also highlights a wider direction: with artificial intelligence agents moving from experimental tools to important systems, basic infrastructure requirements are very similar to the dates of traditional institutions programs from consumer AI applications. Security, compliance and expansion – not only the performance of the model – now define artificial intelligence initiatives that are widely succeeded.

For institutions technology leaders, the appearance of E2B as an essential infrastructure indicates that artificial intelligence transforming strategies should explain more than just choosing the model and developing applications. The companies that have succeeded in expanding the scope of artificial intelligence customers will be the ones that invest early in the specialized infrastructure layer that makes the independent artificial intelligence possible possible.

In an era in which artificial intelligence agents are preparing to deal with an increasing share of knowledge work, the platforms that keep these agents who work safely have proven value more than the agents themselves.