AI, Data & SaaS Spend

AI Cost Management

Governing the total cost of AI workloads: inference APIs, GPU training capacity, vector stores and data pipelines.

AI cost spans more than model API calls: GPU clusters for training and fine-tuning, vector databases, embedding generation, data labelling, evaluation runs, and the storage and transfer that feed them.

AI spend also behaves differently from classic cloud — it is spiky, experiment-driven, and frequently grows faster than any other line item. Budget guardrails, per-team quotas and anomaly alerts matter more here than almost anywhere else in the bill.