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e2bA launch of cloud infrastructure, especially for artificial intelligence agents, has closed the $ 21 million series A funding round, headed by Visual PartnersTaking advantage of promoting the demand for enterprise for AI automation tools.
According to the company, the E2B has already signed up to use the platform, with a significant 88 % of the company’s 100 companies already signed up. The round was involved in the participation of current investors DecebalFor, for, for,. The capital of the sunflowerAnd KayaWith notable angels, including Scott Johnston, former CEO Doctor.
E2B’s technology relieves an important infrastructure difference because companies rapidly deploy AI agents-the Sacred Software Program that can perform complex, multi-faceted tasks, including code generation, data analysis, and web browsing. Unlike traditional cloud computing for human users, the E2B provides safe, isolated computing environment where AI agent can safely run a potentially dangerous code without compromising with the enterprise system.
In an exclusive interview with Venture Bat, E -2B co -founder and CEO Vesic Melgeninsky said, “Businesses have high expectations from AI agents.” E2B AI agents are specifically designed for production by equipped with safe, expanding, high -performance cloud infrastructure. “
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Seven figures have shown a major bet on AI automation by increasing monthly revenue of seven figures
According to Melganski, financing reflects the increase in explosives, in which E2B added “seven personalities” to the new business last month. The company has taken action on millions of sandbox sessions since October, which shows that businesses have deployed AI agents.
E2B customer roster alike AI Innovation: Reads Like Search Engine Disturbance Pro uses E2B for advanced data analysis features for users, which implement the capacity in just a week. AI chip company Groq Its compound relies on E2B for implementation of a secure code in the AI system. Workflow automation platform Poppy Integrated E2B to enable the Customs and Javascript to enable the Customs and JavaScript to enable the user’s workflose.
Startup technology has also become an important infrastructure for AI research. The hugs faceThe leading AI model uses E2B to safely perform the code during learning experiments to create a copy of modern models like EPSEEK-R1. Meanwhile, UC Berkeley’s lmarena The platform has launched more than 230,000 E2B sandboxes to evaluate the web development capabilities of large language models.
Fire cracker microVMS solves a hazardous code problem that causes AI’s growth
E2B’s basic innovation is in its use Fire cracker microVM -Hill weight virtual machines were actually manufactured by Amazon Web Services-to create a completely isolated environment for AI-Infield Code implementation. This indicates a basic safety challenge: AI agents often need to run a non -confident code that can potentially damage the system or access sensitive data.
“When talking to consumers and special businesses, his biggest decision is almost always compared to buying,” Melganski explained in an interview. “With the Blood vs. Purchase Solution, it all really comes about whether you want to hire five to 10 personal infrastructure team for the next six to 12 months, which will cost you at least half a million dollars … or you can use our plug and game solution.”
The platform supports multiple programming languages that include DearFor, for, for,. JavaScriptAnd C ++And can rotate a new computing environment in about 150 millions of seconds-which Enough to maintain real-time reaction expects users with AI applications quite quickly.
Enterprise users specially value E2B’s open source view And deployment flexibility. Companies can host or deploy the entire platform for free in their virtual private clouds (VPCS) to maintain data sovereignty.
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Funding AI agent comes at an important moment for technology. Recent development in large language models has enabled AI agents to handle complicated, real -world tasks. Microsoft recently Left thousands of employees When AI agents only expect humanitarian work before the agents, Melganski indicated in our interview.
However, infrastructure boundaries have forced the AI agent to adopt. Industry data suggests less 30 % of AI agents successfully placed in production deploymentOften due to security, scales, and reliability challenges, the purpose of the E2B platform is to solve.
“We are building the next cloud,” Melgansky said, presenting a outline of the company’s vision. “The present world operates on Cloud 2.0, which was made for humans. We’re making open source clouds for AI agents where they can be independent and run safely.”
The opportunity for the market appears quite. Code generation assistants already produce at least 25 % of the world’s software code, while JP Morgan Chase saved 360,000 hours annually by document processing agents. Enterprise leaders expect a huge demand to automatically support infrastructure in manual tasks using AI agents.
Open source strategy creates defensive ditch against tech giants like Amazon and Google
E2B faces potential competition from cloud giants such as Amazon, Google, and Microsoft, which canore theoretically transmit similar functionality. However, the company has developed competitive benefits through this Open source view And focus on issues of AI’s specific use.
Malajinski explained that E2B focuses on making an open standard for how E2B has interacted with computing resources. “We are even in partnership with many of these cloud providers, as many enterprise users actually want to deploy E2B to their AWS account.”
Of the company Open Source Sandbox Protocol With hundreds of millions of computers, showing its real -world effectiveness, has become a standard of reality. The impact of this network makes it difficult for rivals to displace E2B when once the business is standardized on the platform.
Such as alternate solutions Doctor Containers, though technically possible, lack the security isolation and performance properties required for the deployment of production AI agent. According to Melganski, construction of similar capabilities at home usually requires 5-10 infrastructure engineers and at least 500,000 annual expenditures.
Enterprise features such as 24 -hour session and 20,000 compatible compatible sandboxes in adoption of Fortune 100
E2B’s Enterprise Success is specially developed for large -scale AI deployments. This platform can scale from 100 synchronous synchronization environment for free levels for enterprise users, in which each sandbox is able to run for 24 hours.
Advanced enterprise features include comprehensive logging and monitoring, network security controls, and secrets management – the necessary capabilities for Fortune 100 compliance requirements. The platform is connected with the current enterprise infrastructure, while providing security teams to granular controls.
“We have a very strong bound,” Melgansky described the sales process. “Once we deal with 87 %, we will return for 13 %.” Consumer objections are generally focused on security and privacy control rather than basic technology concerns, which indicate a wide range of market acceptance to the basic price proposal.
Visual Partners $ 21m Bet AI infrastructure verifies the next major software category
Visual Partners‘Investment AI reflects the growing investors’ confidence in infrastructure companies. The global software investor, which manages more than 90 billion in regulatory assets, has invested in more than 800 companies worldwide and has earned 55 portfolio companies in preliminary public offers.
“The visionary partners are excited to back the vision team of the E -2B,” said Parveen Akiraju, Managing Director of the Partners, said that they offer the need for infrastructure for AI agents. ” “It can be difficult to get such a fast growth and enterprise, and we understand that the quality of the E2B’s open source sandbox will be the foundation stone of the Fortune 100 and beyond.”
This investment will support the expansion of E2B engineering and outgoing market teams in San Francisco, development of additional platform features, and growing customer base. The company plans to strengthen its open source sandbox protocol as a global standard, while manufactures secrets and surveillance tools of secrets such as enterprise grade modules.
Infrastructure drama that can explain the next chapter of the Enterprise AI
A fundamental change at the speed of E2B shows how businesses turn to the AI deployment. Although a lot of focus is on large language models and AI applications, the faster adoption of the company among 100 firms shows that special infrastructure has become an important obstacle.
Startup success also highlights a broad trend: AI agents are more closely similar to traditional enterprise software than users’ AI applications, as a transfer from experimental tools to experimental tools. Security, compliance, and scalebuability – not just the model’s performance – now determine which AI measures are successful on a scale.
For enterprise technology leaders, the emergence of E2B as the essential infrastructure shows that the AI change strategy must be much more than the choice of the model and the development of application. Companies that successfully invest in AI agents on a scale infrastructure layer that make autonomous AI operation possible.
In this period where AI agents are designed to handle the growing part of knowledge work, the platforms that keep these agents safely can be more valuable than agents themselves.
