AI cost management is moving fast. This two-page datasheet is built for FinOps practitioners, platform engineers, and finance stakeholders who need a concise, shareable summary of what it takes to bring financial discipline to AI workloads. From token cost attribution to financial guardrails and GPU capacity management, we got you covered. 

This datasheet covers:

• How to achieve unified visibility into AI token costs across cloud-hosted and direct AI providers
• Structuring cost attribution by team, project, and model using Scopes
• Setting preventative financial guardrails before spend exceeds thresholds
• Enforcing AI compliance policies to restrict access to disallowed models
• Analyzing input, output, cached, and uncached token costs to find optimization opportunities
• Managing GPU capacity commitments with the same rigor as reserved cloud infrastructure

Want to learn more? Explore the FinOps for AI platform page to get a deeper dive on how Kion brings financial governance to AI spend end-to-end.