On October 22, 2026 Kochava announced cost-control upgrades to the Enterprise tier of its StationOne desktop hub. The update adds an automatic router that sends simple AI requests to cheaper models and lets admins set token or dollar budgets. Marketers gain finer visibility into AI spend as they scale automation.
What happened
Kochava rolled out a suite of Enterprise-level tools for StationOne, its desktop platform that lets marketers run multiple AI chatbots and agents in one place. The highlight is an Auto Router that evaluates each AI request and directs it to the most cost-appropriate model based on task complexity. Administrators can set per-user or per-team budgets measured in tokens or dollars, receive alerts when thresholds are approached, and view personal analytics that show current and projected spend. Two plugins move routine work away from large language models entirely, and users may run compatible models on their own hardware.
Why it matters
Large language models charge per token, and the per-token rate for premium models is typically many times higher than for smaller ones. As marketing teams lean on AI to automate campaign workflows, audience management and reporting, "the cost of running those models at scale has become a growing concern for enterprise budget owners," the release states. By routing mechanical, code-driven tasks to cheaper or on-device execution, StationOne aims to stop teams "paying premium model pricing for simple tasks." The new features promise finer-grained visibility into AI spend, turning opaque token usage into task-level cost data.
What this means for marketers
Marketers can now deploy agentic AI across large organizations without the fear of hidden token bills. The routing and budgeting controls give finance and operations teams the data they need to justify AI investments. For performance-driven teams, the ability to run simple reformatting or data-pull jobs on low-cost models or local hardware frees up budget for high-impact, reasoning-heavy tasks. This aligns with ADFLU’s autonomous SEO and GEO service, which also relies on precise AI cost management to keep search-driven campaigns efficient.
"We built StationOne so marketers could put agentic AI to work on real campaigns, not just experiment with it." Charles Manning, founder and chief executive of Kochava
The bottom line
Kochava’s StationOne update tackles one of the biggest barriers to scaling agentic AI: unpredictable token spend. By automatically matching task complexity to the cheapest suitable model and providing budget alerts, the platform gives marketers confidence to expand AI automation while keeping compute costs in check. The real test will be the actual savings teams see, but the new controls mark a significant step toward transparent, scalable AI use in enterprise marketing.
Sources
- 1.ppc.land