Stacklet has launched Token Custodian, a new control plane designed to help enterprises attribute, govern and optimize artificial intelligence token usage across teams, agents, applications and projects.
The platform is built for enterprise FinOps and policy-driven workflows, giving organizations visibility into where AI tokens are being consumed while also allowing them to take automated actions based on budgets, usage policies and business priorities.
Rather than simply reporting AI spending, Token Custodian is designed to govern that spending in real time within the workflows organizations already use.
Stacklet developed the platform as enterprises rapidly increase their use of generative and agentic AI but struggle to determine whether that spending is generating sufficient business value.
According to the Tokenomics Foundation’s 2026 State of Tokenomics survey cited by Stacklet, 43% of respondents identified proving value as their biggest challenge with AI spending, five times the number that identified price as the primary concern.
Stacklet believes enterprises need more than dashboards showing where money is being spent. The company is positioning Token Custodian as an operational layer that can connect token consumption with individual teams, projects, applications and cost centers and then enforce policies based on that information.
The platform can trace individual token usage and agent runs back to the organizational resources responsible for them.
It provides a unified view across multiple AI providers, allowing FinOps and platform teams to evaluate AI usage across their environments rather than managing individual platforms separately.
Organizations can establish budgets and usage policies by team, project or environment.
When usage approaches a predefined limit, Token Custodian can take automated action rather than simply blocking employees or applications.
For example, the system can automatically move a workload to a lower-cost AI model or trigger an approval workflow before authorizing additional spending.
Stacklet said this approach is intended to help enterprises control costs without unnecessarily slowing developers, employees or AI agents that are producing meaningful business value.
The platform is based on the policy-driven automation experience of the team behind Cloud Custodian, an open-source cloud governance policy engine hosted by the Cloud Native Computing Foundation.
Stacklet is extending that model from traditional cloud infrastructure into AI economics, where usage can vary significantly depending on models, agents and workloads.
The company argues that applying identical spending caps to every AI workload could prevent enterprises from maximizing the value of agentic AI.
Instead, Token Custodian is designed to allow organizations to differentiate between high-value agents or workloads that justify greater token usage and lower-value workloads where costs should be reduced.
That capability could become increasingly important as organizations deploy larger numbers of autonomous agents capable of independently consuming AI resources.
Stacklet is also integrating Token Custodian into tools already used by enterprise teams, including Claude Code and Slack.
The company said this allows governance policies and approvals to operate within existing workflows rather than forcing users to move to a separate cost-management system.
Token Custodian is currently available in early preview, with general availability planned for the fourth quarter of 2026.
Stacklet plans to demonstrate the technology during its Token Governance Summit on October 27, which will focus on approaches to managing enterprise AI token consumption.
The launch expands Stacklet’s broader platform for autonomous cloud and AI infrastructure.
Stacklet said its technology is currently used by enterprises managing more than $10 billion in cloud and AI spending.
The company says its platform can autonomously discover, remediate and prevent operational, cost and security issues, with customers achieving up to 50% cost reductions and spending as much as 80% less time on governance.
KEY QUOTES:
“Organizations are moving quickly to scale AI, but the ability to govern that investment and connect it to business value is still catching up. As a Tokenomics Foundation member, Stacklet brings expertise in cloud governance to this broader effort to help enterprises manage AI economics and turn AI investment into measurable business outcomes.”
Kevin Emamy, VP of Development for the Tokenomics Foundation
“Applying the same cost limit to AI agents that deliver significant business value and those that consume tokens without comparable returns can prevent organizations from realizing the full potential of agentic AI. Token Custodian enables FinOps teams to define and enforce more granular controls for token usage, helping enterprises direct spend toward workloads where it makes business sense and manage costs where it doesn’t. This closes the critical gap between simply reporting on AI spend and managing it based on business impact and priorities.”
Torsten Volk, Principal Analyst, Application Modernization at Omdia
“Governing our AI spend so it drives value, not waste, is exactly what we’re after, and most tools either stop at reporting or weren’t built for FinOps and governance workflows. Token Custodian does both, and it fits right into the tools our teams already use, like Claude Code and Slack. We’re excited to try it.”
Lindbergh Matillano, Director of Cloud & AI Optimization at Avalara
“The instinct with AI spend is to cut or cap it, but that just slows your teams down. The real win is governing it so spend flows to the work that pays off, and that’s what we built Token Custodian to do, on the same engine enterprises have trusted to govern their cloud for years.”
Travis Stanfield, CEO of Stacklet
