Artificial intelligence is moving beyond conversations and into execution, with digital agents increasingly expected to write code, operate software, analyse information and complete complex tasks independently. But as businesses deploy more of these autonomous systems, they need secure computing environments that can run thousands of agents simultaneously. Daytona is targeting this emerging infrastructure market, having raised $60 million in a Series B funding round at a $1 billion valuation.
$60 Million Funding Round
The funding round was led by FirstMark, with participation from prominent technology entrepreneurs and executives, including Stripe co founder Patrick Collison, Quora founder Adam D’Angelo, Mercor co founder Brendan Foody, Shopify CEO Tobi Lütke, Datadog CEO Olivier Pomel, Perplexity CEO Aravind Srinivas and Zoom founder Eric Yuan.
Other investors included Alumni Ventures, Evergreen Fund, Okta Ventures, Qualcomm Ventures, Samsung Next and Torch Capital. Existing backers also increased their investments, with Pace Capital doubling its commitment, Upfront Ventures tripling its investment and E2VC quadrupling theirs.
The latest round brings Daytona’s total funding to $91 million, giving the company additional capital to expand its infrastructure and strengthen its position in the growing AI agent ecosystem.
Building Infrastructure for AI Agents
Daytona develops cloud infrastructure that provides secure, isolated computing environments for artificial intelligence agents. These environments allow agents to execute code, interact with software tools and perform tasks without exposing the wider system to unnecessary risks.
As AI systems become capable of taking actions rather than simply generating responses, developers need infrastructure that can support their work throughout the execution process. Agents may need to test code, access files, run applications and experiment with different solutions before completing a task.
Daytona provides these capabilities through an API that enables developers and businesses to create computing environments on demand. Its platform supports Linux, Windows and macOS, allowing teams to select environments suited to their workloads.
Security Meets Scalability
Running autonomous agents introduces new infrastructure challenges. An agent may execute incorrect code, access untrusted inputs or behave in unexpected ways. When many agents operate simultaneously, businesses must ensure that an individual failure does not affect other workloads or sensitive systems.
Daytona addresses this issue by isolating computing environments so that agents can perform tasks within defined boundaries. The platform also allows computing resources to scale according to workload requirements, helping developers manage fluctuating demand.
Environments can be paused and resumed, enabling agents to continue work without restarting every process from the beginning. This flexibility is particularly useful for long running tasks, model evaluation and development workflows that require repeated experimentation.
Co founder and CEO Ivan Burazin has described the company’s vision around enabling organisations to manage thousands of digital workers while giving each one a safe environment in which to operate.
Adoption Across the AI Industry
Daytona says its infrastructure is used by organisations including Anthropic, OpenAI, NVIDIA, Cursor and Cognition. Its wider customer base also includes Meta, Cohere, Mercor, Handshake, Surge AI, SambaNova, Postman, Bolt.new, n8n and Clay.
The company is also seeing adoption in AI training and evaluation. Customers such as Snorkel and Trajectory use its infrastructure for workloads that involve processing and assessing AI systems.
Daytona has reported a 25 fold increase in its revenue run rate between January and September, indicating rapid commercial growth, although the company has not disclosed the underlying revenue figures in the announcement.
What Comes Next?
The new funding will support Daytona’s expansion beyond its original sandbox product towards a broader agent cloud platform. The company plans to scale its computing infrastructure, develop additional capabilities and grow its international workforce, with recruitment planned across San Francisco, Croatia and Singapore.
As AI agents become more integrated into business operations, the infrastructure supporting them could become an increasingly important part of the technology stack. Daytona is betting that secure, flexible and scalable computing environments will be essential for organisations moving from AI experimentation to large scale autonomous execution.