Shipped: Catch the runaway agent while it’s still running.

AI spend has no ceiling. An engineer can burn $5,000 in an hour, and a team that spins up an agent on Friday can loop it on a bad prompt all weekend. You find out when the bill lands: the money is already gone, the damage pieced back together from logs. Cloud spend had a natural limit. Tokens don’t.

Now you see it as it happens. Connect a source and the calls stream in within seconds. Within minutes they’re broken out by model, provider, agent, and user. Within hours they’re fully allocated across every dimension you track (team, product, feature, customer) to finance-grade accuracy. The urgent answer arrives immediately; the deep one follows shortly after.

Billing-anchored tools show you yesterday. Observability tools show you traces, not dollars. Neither one shows you spend the moment it happens.

Why this matters

AI spend moves faster than any billing cycle. Without real-time visibility, the only lever you have is a blunt cap. The project worth funding is often the one burning the most tokens, so a cap set without context cuts the wrong thing. Seeing spend as it lands lets you decide instead of guess. The data arrives in tiers: monitor in seconds, allocate in minutes, full allocation in hours. You don’t trade speed for accuracy.

What we built

AI Signals: a live stream of inference events feeding straight into the allocation engine that’s run CloudZero in production for ten years. It’s the same engine and same dimensions you already use for cloud spend, now running on real-time AI data, so the live feed and the finance-grade allocation are the same system at different stages, not two tools stitched together.

How design partners use it

It’s available to design partners now, and the livestream is the first proof: connect a gateway, and events scroll past within seconds. From there it’s the Explorer they already know, with AI spend broken out by team and repo — and mapped to the customer and feature it served, as you connect those dimensions. Seeing cost per customer sit next to cost per model is usually the part that lands in the first session.

Talk to us about the design partner program.

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