Rising AI-agent fleet costs — detect, predict, and optimize spend

Rising AI-agent fleet costs — detect, predict, and optimize spend targets a $18.0B = 180k mid+large enterprises x $100k ACV (annual spend on AI ops, cost management and optimization tools) total addressable market with medium saturation and a year-over-year growth rate of 30%+ (AI infrastructure & MLOps market growth; LLM adoption accelerating agent deployments).

Key trends driving demand: Autonomous agents -- Teams are running many persistent agents that compose LLM calls, increasing aggregate spend exponentially as usage scales.; Usage-based pricing -- Token/compute billing from major LLM providers shifts risk to customers and elevates need for spend management.; Model proliferation -- Multiple model endpoints and hybrids (local+cloud) force per-request model selection decisions that materially change cost/perf tradeoffs.; Richer telemetry APIs -- Cloud and LLM vendors now surface more detailed request/billing logs enabling real-time cost observability and automated remediation..