See AI usage. Manage what it costs.
Inspect duration, token usage and estimated cost for each run, alongside its activity and outputs. Use that evidence with quality review and a clear baseline to judge value.
See what each run used.
Each run shows its duration, token usage and estimated cost next to the workflow’s activity and outputs.
Judge the quality of the result.
Review quality, human review effort and rework with the people who own the work. Usage alone does not show whether an output was useful.
Compare against a baseline.
Compare the current process with the AI-assisted workflow, including implementation, platform, infrastructure and human effort alongside model costs.
To report cost per accepted output, first define what counts as accepted and the period you measure.
See the controls behind the work.
Walk through the product with your workload. Review the controls available for your deployment and agree how to evaluate quality, time, and cost.