Know where your AI budget goes, and what it buys.

Where the numbers come from

Alesia's on-device agent already sees each AI interaction in order to protect it. For analytics it keeps only the facts about it: the platform, the surface, the team, token counts, and the outcome of any policy check. In the console those records add up to usage, cost, and adoption by team and tool, and to risk trends over time. No prompt or response is stored or analyzed, so the data that answers the budget question never turns into a monitoring problem.

The quarterly AI budget review

Finance asks a simple question: the company pays for three AI tools, are people using them? The console has the answer. One tool is used daily across most of engineering. One is used heavily by two teams and barely touched anywhere else. The third has a handful of active users, while an unapproved tool doing the same job shows up on dozens of devices. The decisions follow from the numbers: expand the first, limit the second to the teams that use it, and either replace the third or approve what people already chose.

What changes for your team

AI budget decisions stop relying on vendor dashboards and anecdotes. Every tool's usage is measured the same way, including tools nobody bought, and paid seats nobody uses show up as idle spend.

• One view across every AI tool, approved or not
• Usage and spend broken down by team
• Idle seats and idle spend surfaced
• Built entirely on metadata, never content