Decagon tripled its valuation to $4.5 billion in six months, raising $250 million in Series D funding led by Index Ventures and Coatue Management. The customer service AI agent platform now processes over 80 million conversations across 100+ enterprise customers including Duolingo, Hertz, Deutsche Telekom, and ClassPass.

The funding milestone signals enterprise confidence in autonomous customer service infrastructure over traditional human-centric support models. While legacy platforms like Salesforce, Intercom, and Zendesk retrofit AI capabilities onto existing architectures, agent-native companies are capturing market share by rebuilding customer operations from the ground up.

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.