Prove what your AI workforce is producing.
Watch this on-demand webinar where Revenium's Jason Cumberland and Bailey Caldwell put a real number on what your AI produces alongside what it costs.
Your AI workforce is already running, making thousands of economic decisions a day, and it's the only team in your company measured by nothing but its token bill. Sales gets credit for the closed deal and engineering gets credit for the shipped feature, while AI gets a line item on an invoice.
That's why 78% of finance leaders can't tie AI spend to an outcome, only 7% can show a measurable return, and nearly half have already paused or pulled back a rollout. This session covers the fix. Treat AI like a workforce, measure the fully loaded cost and real outcome of every job, and catch the waste before the bill lands.
In this on-demand session, Bailey Caldwell and Jason Cumberland show how to measure your AI workforce the way you measure every other team, then prove it live in the product.
The Autonomous Job. The fully loaded cost of AI work, model plus tools plus human time, tied to an outcome and an owner instead of a raw token count.
Cost meets productivity. Coding-assistant spend mapped to pull requests, tickets, and individual engineers, where your least efficient developer can cost 20x what your most efficient one does.
Waste hiding inside success. The top 1% most expensive jobs surfaced automatically, the retries buried inside a result that reads as successful, and model choices scored on real failure rates.
Control before the invoice. Real-time alerts and circuit breakers, plus a flagship-model budget that caps your priciest model while developers keep working.
