As government agencies adopt advanced and autonomous AI systems, token consumption is becoming a critical factor in managing costs, even as model pricing declines. Scaling AI across government operations requires agencies to consider how they design, deploy, and govern AI workloads to balance performance, cost, and security.

This solution brief examines how architectural decisions, including workload placement and local-first execution, can improve token efficiency, strengthen data governance, and support AI deployment across edge, data center, and cloud environments. Learn how agencies can scale AI capabilities while maintaining control over costs, security, compliance, and public trust.

Download the brief to learn more.