Agents spend money on every run, and most teams find out how much when the bill arrives.

Tying that spend back to a step, a tool call, or a retry loop is manual work: pull traces, export token counts, guess which change made things worse.

In this demo webinar, we'll go inside the Monte Carlo platform and show how teams spend less per run without losing reliability:

• Where the money goes: cost attributed across the dimensions your team cares about, so an expensive run tells you why it was expensive.

• Performance you can act on: latency, failures, and output quality on the same view, so you can tell a slow agent from a wrong one.
  

• Waste you didn't know to look for: Reinforcement Loop reads every production run and flags the silent inefficiencies no dashboard catches, like retry loops and duplicate queries, so you fix spend on runs that technically succeeded.

Can't wait? Schedule a personal demo in one click.