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See what changed and know why, with an answer you can trust
Cost Anomaly Detection breaks spend down by agent, user, and workspace instead of just a total. Every anomaly links straight to the conversations that explain it, and it runs on the same permissions and Agent Trust Registry as the rest of Bigeye.
Cost figures shown are estimates for trend detection and won't reconcile exactly to your provider invoice. Available in USD only at launch.
Use Cases
Catch it before the auditor does
A production agent's cost quietly drops to zero because a credential expired or an integration silently failed. For a week, it looks like a cost win. Then someone notices the report it was supposed to generate never ran. Cost Anomaly Detection flags the drop as an anomaly using daily automated detection, so the team catches the outage before the auditor does.
Stop a spike before next month's bill
An agent slips into a retry loop or an unexpectedly chatty conversation pattern, and its daily cost climbs well outside its normal range. Cost Anomaly Detection surfaces the spike as soon as it clears the range derived from that agent's own history, and links straight to the conversations driving it, so the fix starts in minutes, well before the invoice lands.
Turn a shrug into an answer
Every month, Finance asks the same question: why did AI spend move? Historically the honest answer was “agents, probably.” Now the governance lead can open Bigeye and point to the specific agent, user, and dataset behind the change. That turns a shrug into a two-minute explanation.
Ask instead of digging
An engineer investigating something unrelated has a passing cost question: which agent is the most expensive this week, what did we spend querying the Orders table. Instead of pulling logs or filing a ticket, they ask bigAI directly and get a ranked answer immediately, right where they're already working.
Part of the Platform
Part of the Agent Trust HubCost Anomaly Detection is a capability inside the Agent Trust Hub, built on the same AI stack you already use. Anomalies inherit the same workspace and agent-level permissions already configured in Bigeye, and they live alongside the Agent Trust Registry. Drill into any anomaly and you're looking at the same agent view Bigeye already gives you: the data it accessed, and the quality and freshness signals already tracked on those tables. And because bigAI already understands agent activity, you can ask plain-language questions, like “which agent cost the most this week?,” right from the same chat you already use.
