Daytona reached $1M forward revenue run rate in under three months. Six weeks later, it doubled.

The speed reflects enterprise urgency around a fundamental infrastructure gap: current cloud platforms were built for production workloads—stateless, immutable systems optimized to run the same code the same way every time. AI agents need the opposite: persistent, stateful environments where they can experiment, branch execution paths, and recover from failures at massive scale.

The Infrastructure Mismatch

Enterprise adoption of AI agents is hitting a hard infrastructure bottleneck. While agents can reason through complex workflows and make decisions, they break when deployment infrastructure treats every workload like a web server.

EnFi raised $15 million in Series A funding to deploy AI agents that function as virtual credit professionals, addressing a fundamental scaling crisis where commercial lending demand is growing faster than the human talent pool can accommodate.

The Boston-based startup represents a shift from AI-assisted tools to autonomous agent workforces, with customers deploying targeted agents across deal screening, documentation, and portfolio monitoring within 60 to 90 days. This timeline reflects a new deployment velocity for financial services AI, where traditional implementations often require 12-18 months.

79% of enterprises now deploy AI agents, but 97% lack proper security controls—a gap that’s created a new category of infrastructure risk as organizations race to automate everything from database queries to payment processing.

Virtue AI just launched AgentSuite, the industry’s first multi-layer security and compliance platform purpose-built for enterprise AI agents. While traditional security tools were designed for predictable application workflows, AgentSuite addresses the dynamic, multi-tool nature of autonomous agents that can trigger complex actions across enterprise systems in real time.