Daytona Raises $60M Funding at $1B Valuation to Build the Cloud Where AI Agents Actually Work

Daytona, the San Francisco-based startup building cloud infrastructure purpose-built for AI agents, has raised $60 million in Series B funding at a $1 billion valuation, officially joining the unicorn club. The round was led by FirstMark Growth, with participation from an A-list roster of tech founders investing as angels: Patrick Collison (Stripe), Tobi Lütke (Shopify), Aravind Srinivas (Perplexity), Eric Yuan (Zoom), Olivier Pomel (Datadog), Adam D’Angelo (Quora), and Brendan Foody (Mercor). Strategic investors included Qualcomm Ventures, Samsung Next, and Okta Ventures .

The round brings Daytona’s total funding to approximately $91 million, following a $24 million Series A in February 2026 led by FirstMark, a $5 million seed in 2024, and a $2 million pre-seed in 2023. About $50 million of the new round came from existing investors, with E2VC participating for the fourth time, Upfront Ventures for the third, and Pace Capital and FirstMark for the second .

Daytona Funding Overview By CREDX Media

Startup Name	Daytona
Founders	Ivan Burazin (CEO), Vedran Jukić(CTO), Goran Draganić (Chief Architect)
Founded	2023
HQ	San Francisco, USA (offices in Split and Zagreb, Croatia)
Round	Series B Funding
Amount Raised	$60M
Valuation	$1B
Category	AI Infrastructure, Agent Cloud, Developer Tools
Lead Investor	FirstMark Growth
Key Angel Investors	Patrick Collison (Stripe), Tobi Lütke (Shopify), Aravind Srinivas (Perplexity), Eric Yuan (Zoom), Olivier Pomel (Datadog), Adam D’Angelo (Quora), Brendan Foody (Mercor)
Strategic Investors	Qualcomm Ventures, Samsung Next, Okta Ventures
Total Funding Raised	~$91M
Employees	~35 (plans to reach 50-60 by year-end)
Key Customers	Anthropic, OpenAI, NVIDIA, Meta, Cursor, Cognition, Cohere, Snorkel, Handshake, Postman, n8n, Clay
Revenue Growth	~25x since January 2026

💡 Use of Funds

• Infrastructure Expansion: Leasing or purchasing servers and deploying them in data centers to meet growing demand for agent sandboxes .
• Team Growth: Expanding from ~35 employees to 50-60 by year-end across San Francisco, Split, and Zagreb .
• Platform Development: Continuing to build out the Agent Cloud with new capabilities for agent-native workloads.

Startup Overview: Daytona

What Daytona Is Building in Simple Words

Daytona has built an Agent Execution Cloud—infrastructure purpose-built for AI agents to run code, browse the web, and operate software inside isolated virtual computers called sandboxes. While traditional cloud infrastructure was designed for long-running human services, AI agents spin up thousands of short, stateful jobs that nobody planned in advance. Daytona’s platform is built for exactly that pattern .

• Instant Sandboxes: Daytona can provision a sandbox in 60 milliseconds—roughly half the time it takes to blink. Traditional cloud providers like AWS, Azure, or Google Cloud take 30 seconds to several minutes to spin up a virtual machine .
• Multi-OS Support: Daytona is the only provider offering Linux, Windows, macOS, and GPU sandboxes on a single platform. Agents can optimize CUDA kernels, test native Mac apps, drive Windows desktops, or work in 3D CAD software without leaving Daytona .
• Fork and Snapshot: Agents can pause a sandbox, resume it, or fork it into parallel copies to try multiple approaches simultaneously. State persists across failures, and execution paths can be cloned, resumed, or merged .
• Built for Scale: Customers like Snorkel have provisioned over one million sandboxes on Daytona’s platform. Writer, which ran its own sandbox infrastructure until it passed 20,000 sandboxes per day, provisioned 300,000 sandboxes in a single month on Daytona .

Why Daytona Matters

1. The Cloud Wasn’t Built for Agents CEO Ivan Burazin’s core thesis is that agents are “digital humans” who need computers just like people do. But an agent’s computer has little in common with a traditional cloud instance: it must start in milliseconds, pause with state intact, fork into parallel copies, and disappear when the job is done. Existing clouds were optimized for maximum utilization of long-lived services, not the bursty, stateful, short-lived workloads of AI agents .
2. Agent Security Demands Isolation As autonomous agents gain access to enterprise credentials and the ability to execute code, the risk of one agent’s actions spilling into company-wide chaos grows. Burazin frames it directly: “Recent agent security incidents are not edge cases. They are previews. The agents aren’t going rogue; they are doing their job without any morals or fear of consequences. Companies are going to manage thousands of digital employees, and each one needs a safe place to fail” . Daytona’s sandboxes provide that isolation.
3. Revenue Growth Validates the Urgency Daytona’s revenue run rate has grown approximately 25-fold since January 2026, with average month-over-month growth of 50.9%. Net revenue retention is averaging around 135% per month—customers who were spending with Daytona six months ago are now spending nearly three times as much . For context, Snowflake’s famous NRR at IPO was around 160% per year. Daytona is averaging close to that every month .
4. A Pivot That Nearly Killed the Company Daytona didn’t start as an agent cloud. The founders originally built a tool to automate software development environments for large enterprises. When they saw that AI agents would need computers too, they gave their existing customers to competitors, rebuilt the product from scratch, and relaunched with roughly three months of revenue left in the bank . That gamble paid off.

Founder Background: The Croatian Team That Bet on Agents Before It Was Obvious

Ivan Burazin (CEO) co-founded the cloud coding tool Codeanywhere in 2009 and later served as Chief Developer Experience Officer at Infobip, a Croatian unicorn. He also founded the Shift developer conference, which Infobip acquired in 2021 .

Vedran Jukić(CTO) and Goran Draganić (Chief Architect) co-founded Daytona with Burazin in 2023. Their collaboration dates back to Codeanywhere, giving the founding team nearly two decades of shared experience building developer tools and cloud infrastructure .

The founding insight came from watching AI agents evolve from chatbots into autonomous workers. Burazin and his co-founders recognized that agents would need their own computers—not just API calls to existing services—and that the existing cloud was fundamentally ill-suited for how agents actually operate. That contrarian view, initially met with skepticism (“why can’t agents just run on existing infrastructure?”), became consensus as long-running agents went mainstream in 2026 .

The Agent Cloud Race Nobody Expected

Daytona operates in a market where traditional cloud providers and AI-native infrastructure startups are converging.

Hyperscalers including AWS, Microsoft Azure, and Google Cloud offer virtual machines but require 30 seconds to minutes to provision. Burazin argues that to match Daytona’s performance, hyperscalers would need to “create a whole new company inside their existing cloud services” .

AI-native competitors including Modal (valued at $15.75B) and E2B focus on serverless GPU access and agent sandboxes respectively. Daytona’s differentiation is its multi-OS support (Windows, macOS, GPU sandboxes alongside Linux) and its 60-millisecond provisioning speed .

The competitive moat, if it materializes, is workflow depth and customer entrenchment. Once an AI lab or enterprise builds its agent training or production pipeline on Daytona’s sandboxes, switching costs become high—especially as usage scales and net revenue retention exceeds 135% monthly .

Founder Intelligence: What Founders Can Learn from Daytona

• Kill your product when the market shifts: Daytona had paying customers and revenue. The founders gave them up to competitors and rebuilt from scratch because they believed the real opportunity was elsewhere. That kind of conviction is rare—and necessary when the market is moving faster than your current product .
• Contrarian views become consensus faster than you think: Burazin was told agents could run on existing infrastructure. Within a year, agent-specific infrastructure was consensus. The window to build the definitive solution in a new category is shorter than most founders realize .
• Grow bottoms-up, not with salespeople: Daytona grew ~51% month-over-month for 18 months with no sales team. The company is self-serve, priced on consumption, and runs about 1,100 Slack channels with customers. It had just agreed to hire its first head of sales when Burazin spoke to TNW .
• Go where the ecosystem is: Daytona is headquartered in San Francisco but maintains a significant team in Croatia. Burazin flies between the two twice a month. The company has US and European entities, and while two-thirds of the team is currently in Europe, Burazin expects most to be in the US next year .

Investor Intelligence: Why This Round Gets Premium Capital

FirstMark Growth led the round, deepening its conviction after leading Daytona’s Series A in February 2026. Partner Matt Turck, who joined the board with the Series A, framed the thesis: “We believe the next infrastructure shift is from human-centric cloud primitives to agent-native ones. Daytona’s breakthrough is making ‘a computer for every agent’ practical: instant startup, persistent state, and the tooling agents need to write code, use Git, and execute safely at scale. That’s a foundational building block for the agentic economy” .

The angel roster is extraordinary: seven founders of companies collectively worth trillions of dollars—Patrick Collison (Stripe), Tobi Lütke (Shopify), Aravind Srinivas (Perplexity), Eric Yuan (Zoom), Olivier Pomel (Datadog), Adam D’Angelo (Quora), and Brendan Foody (Mercor). Their participation signals that operators who have built category-defining companies see Daytona as infrastructure for the next wave of software .

Qualcomm Ventures participated as a strategic investor. Quinn Li, SVP at Qualcomm Technologies, framed the investment around agent security and scale: “AI agents need secure environments to run code, call tools, browse the web and learn through reinforcement learning. We believe Daytona’s platform gives each agent its own environment to do all of it at scale” .

The composition signals conviction across multiple dimensions: FirstMark’s enterprise infrastructure expertise, operator angels who understand what it takes to scale, and strategic investors from mobile, semiconductor, and identity sectors—all of whom see agent infrastructure as a critical layer in their own ecosystems.

The Road Ahead for Daytona

Expansion Targets

With $60 million in capital, Daytona will:

• Scale infrastructure by leasing or purchasing servers for data center deployment .
• Grow the team from ~35 to 50-60 employees by year-end .
• Continue product iteration, with Burazin noting the company “slightly repositions the product every three months, on both the business and technical side” to match market needs .

Product Roadmap (Expected)

• New sandbox capabilities for agent-native workflows.
• Deeper integrations with AI training and production pipelines.
• Expansion of GPU and Windows sandbox offerings as customer demand grows.

Competitive Response

Expect:

• Hyperscalers to invest in agent-specific infrastructure, though Burazin argues it would require rebuilding their core architecture .
• Modal and E2B to deepen their offerings in adjacent agent infrastructure categories.
• New startups to emerge targeting specific agent execution niches.
• Daytona’s moat: 60ms provisioning + multi-OS support + proven scale + high net revenue retention.

Conclusion

Daytona’s $60 million Series B at a $1 billion valuation validates the thesis that AI agents need their own computers—and the existing cloud isn’t built for them. The company’s 25-fold revenue growth since January, 135% monthly net revenue retention, and customers including Anthropic, OpenAI, and Meta demonstrate that the demand is real and urgent.

Market tailwinds favor Daytona: the shift from human-centric to agent-native infrastructure, the security imperative of isolating autonomous agents, and the sheer scale of agent deployments that will require millions of sandboxes. The company’s Croatian founding team, Silicon Valley backing, and proven execution position it to become the execution layer for the agentic economy.

For deep analysis of AI infrastructure funding, agent cloud innovation, and companies reshaping how AI runs in production, explore CREDX Media for comprehensive coverage of startup funding trends, valuation intelligence, and founder playbooks.

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Frequently Asked Questions

1. What is Daytona’s total funding and latest round size?
Daytona has raised approximately $91 million total. Its $60 million Series B was led by FirstMark Growth in October 2026 .

2. How much did Daytona raise in its Series B round and who led the investment?
Daytona raised $60 million led by FirstMark Growth, with angel participation from Patrick Collison, Tobi Lütke, Aravind Srinivas, Eric Yuan, Olivier Pomel, Adam D’Angelo, and Brendan Foody, plus Qualcomm Ventures, Samsung Next, and Okta Ventures .

3. What is the valuation of Daytona?
Daytona is valued at $1 billion following its Series B round, making it a unicorn .

4. Who are the major investors in Daytona?
Major investors include FirstMark Growth (lead), Qualcomm Ventures, Samsung Next, Okta Ventures, E2VC, Upfront Ventures, and Pace Capital, along with seven tech founder angels .

5. Who are Daytona’s founders?
Daytona was founded in 2023 by Ivan Burazin (CEO), Vedran Jukić (CTO), and Goran Draganić (Chief Architect). The team previously built Codeanywhere together .

6. What is Daytona’s business model?
Daytona operates a consumption-based self-serve model, charging customers for sandbox usage. The company grew ~51% month-over-month for 18 months with no sales team .

7. How does Daytona’s technology work?
Daytona provisions isolated virtual computers (sandboxes) for AI agents in 60 milliseconds by pre-distributing snapshots of configured machines onto server drives. Agents can pause, resume, fork, and clone sandboxes to run code, browse the web, and operate software safely .

8. What traction justifies Daytona’s $1 billion valuation?
Daytona’s revenue run rate grew ~25x since January 2026, with average month-over-month growth of 50.9% and net revenue retention around 135% monthly. Customers include Anthropic, OpenAI, NVIDIA, Meta, Cursor, and Cognition .

9. What are Daytona’s plans for the $60 million Series B capital?
Daytona will lease or purchase servers for data center deployment, grow its team from ~35 to 50-60 employees, and continue developing the Agent Cloud platform .

10. What is the “agent cloud” and why does it matter?
The agent cloud is infrastructure purpose-built for AI agents—short-lived, stateful workloads that need instant provisioning, multi-OS support, and secure isolation. Existing clouds were designed for long-running human services and take 30 seconds to minutes to provision, which is too slow for agent workloads at scale .

11. Who is the CEO of Daytona?
Ivan Burazin serves as CEO and co-founder. He previously co-founded Codeanywhere and served as Chief Developer Experience Officer at Infobip .