Agent loops multiply token usage
Autonomous workflows can call models many times for one business task, making API bills hard to anticipate.
Token burning cost control
Stop token burning before it becomes an uncontrolled AI cost.
Token burning happens when repeated prompts, long contexts, vector search, tool calls and autonomous agents consume large volumes of paid tokens. It is especially risky when teams scale AI usage without a predictable infrastructure strategy.
RAG and embeddings add hidden volume
Document ingestion, retrieval and summarization often generate token usage beyond the visible chat prompt.
Local clusters absorb repeated workloads
High-volume private workloads can run on owned GPU capacity while cloud APIs remain optional for selected cases.
These trade-offs determine which workloads should stay local and where cloud services can remain useful.
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