We kept hitting the same problem while building AI features: token spikes, unpredictable costs, and customers asking for budget controls we couldn’t easily give them.
So we built AI Usage Management at Stigg: a real time usage governance layer you embed directly in your product. It lets you meter AI usage, define limits, set alerts, allocate budgets to users or teams, and enforce policies at the moment of consumption instead of discovering it on the bill later.
Think:
- low latency metering
- allocation per user, team or feature
- alerts and enforcement
- credit or outcome based models
- drop in admin UI or use your own
If you’re shipping AI features and need to keep spend predictable or meet enterprise governance requirements, early access is open.
So we built AI Usage Management at Stigg: a real time usage governance layer you embed directly in your product. It lets you meter AI usage, define limits, set alerts, allocate budgets to users or teams, and enforce policies at the moment of consumption instead of discovering it on the bill later.
Think: - low latency metering - allocation per user, team or feature - alerts and enforcement - credit or outcome based models - drop in admin UI or use your own
If you’re shipping AI features and need to keep spend predictable or meet enterprise governance requirements, early access is open.