AI pilots feel affordable until real users, real workflows, and real context hit production. That’s when costs “sneak up,” driven by the invisible meter behind every interaction: tokens. Prompt design, conversation history, retries, and verbose responses can turn small decisions into recurring spend at scale, especially in agentic workflows.
This whitepaper breaks down token economics in business terms, introduces a simple cost model leaders can forecast with, and shows proven engineering levers to cut spending without sacrificing quality or velocity.

Why tokens per outcome is the KPI that actually predicts AI ROI.
Where tokens hide in production: agents, long context, tool chains, retries, and verbosity.
The highest-ROI levers: model routing, caching, batch processing, retrieval & summarization, structured outputs.
When to use TOON/CSV vs JSON to reduce token bloat.

We’re a certified Google Cloud Partner specializing in secure, scalable AI built to perform in production.
We help companies like yours:

Baseline and reduce tokens per outcome across real workflows

Implement routing, caching, guardrails, and FinOps dashboards for predictable spending

Scale GenAI responsibly & without surprise invoices
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