At Google Cloud’s latest startup showcase, the shift toward agentic AI is clear: startups are building systems that don’t just generate outputs, but take action across workflows. These applications rely on complex stacks of models, GPUs, APIs, and orchestration layers, making AI infrastructure more powerful, but also far harder to track and manage.
As AI moves into production, the challenge is no longer just building agents. It’s understanding what they cost to run, how resources are consumed, and whether they deliver real ROI. This growing complexity highlights the need for full-stack visibility, granular cost attribution, and financial controls across the entire AI ecosystem.
