Geordie Launches Cost Intelligence to Connect AI Spend to the Agent Work Driving It

New capability gives AI Ops teams a clearer picture of the financial risk behind agent activity

Geordie, the leading platform trusted by enterprises to understand and control agentic risk, today announced Cost Intelligence, which connects agent usage and activity directly to the costs they generate. The new capability expands Geordie’s approach to agent risk management beyond security, giving enterprises the financial context needed to govern AI agents holistically.

AI spend is typically measured by consumption: which models ran, how many tokens they used, and what they cost. But as usage spreads across tools and token consumption varies from one agent run to the next, those numbers alone cannot explain what is actually driving spend. Cost Intelligence adds the missing context by connecting costs back to the agents, activities, and workflows that generate them. The stakes are already significant: one retailer saw $1 million a month in model-routing waste from tasks being routed to models more expensive than the job required, while a bank had 50% of its monthly AI budget consumed in a single day by an agent stuck in an endless tool loop.

“One of our biggest challenges with AI spend has been visibility,” said Jacob Sweat, VP of Technology at Wood Partners. “Once Geordie gave us a clear view of what agents are costing us and whether that spend is doing something useful, the conversation shifted from ‘how much are we spending?’ to ‘is this spend worth it?’”

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Geordie’s architecture is designed to sit close to the agent and understand its behavior for security and governance. That same proximity gives Geordie a granular view of the agent’s economics, including its activity, token consumption, and model usage. When an AI Ops team sees a change in spend, they can connect the dollar figure back to which agent acted, what it did, and who was responsible, giving teams the financial context needed for comprehensive agent risk management.

“Tokens and invoices tell you what you consumed; they do not tell you what work drove that consumption,” said Henry Comfort, co-founder and CEO of Geordie. “Cost Intelligence connects spend back to individual agents and their activity. When you can see what an agent costs alongside the work it performed, you have the foundation for understanding agentic ROI, and that is exactly what Cost Intelligence delivers.”

Cost visibility is only as complete as the instrumentation behind it. Geordie measures spend at the individual-agent level across cloud, code, and endpoint, giving teams visibility across the AI estate rather than only on activity that happens to route through a single gateway or model router.

“As agents take on more autonomous work across the enterprise, the risk they create isn’t limited to security alone; it’s operational, financial, and accountability risk,” said Hanah-Marie Darley, co-founder and chief AI officer of Geordie. “Organizations need a shared view of how agents are operating and the full range of risk their behavior creates, not just the security dimension.”

Key capabilities of Cost Intelligence include:
– Cross-platform spend aggregation: AI spend combined into one view across every connected platform, attributed to the agents and work that generated it.
– Multi-dimensional breakdown: Drill from an organization-wide total to platform, team, user, model, individual agent, or workflow to understand where spend goes and what work it supports.
– Cache-utilization insight: Per-agent caching efficiency tracked as its own metric, flagging which agents are under-caching and what it costs.
– Token-efficiency mapping: Spend and volume mapped per agent, so a busy, high-value agent performing critical work is never mistaken for a wasteful one.
– Cost anomaly detection: Identifies agents stuck in infinite loops, tasks routed to oversized models, and sessions burning tokens with little productive output.

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