Every AI dollar, attributed and defensible.
Your OpenAI invoice is one number. Your AI estate is a hundred workflows. Cost Intelligence splits every dollar of model spend across workflows, nodes, and prompts — then hunts the estate for waste: retry storms, oversized models, bloated prompts, and zombie workflows still burning tokens.
The problems that pile up quietly.
The monthly AI bill doubles and nobody can say which workflow did it.
A retry loop burns $900 over a weekend because token spend has no alarms.
Budget conversations are guesswork because cost has no attribution.
What changes for your team.
A price tag on every workflow
Each workflow shows its daily and monthly cost, broken down by node and model call — so "what does this automation cost us?" takes one click.
Spend anomalies caught in hours
Sudden cost spikes trigger alerts with the responsible workflow and the execution pattern behind them — retry storms die young.
Savings surfaced automatically
Obsivara flags where a cheaper model, a trimmed prompt, or a batching change would cut spend without hurting quality. Teams commonly find 30%+.
Live in minutes, not sprints.
Meter every call
Token counts and model rates are captured per execution and rolled up to nodes, workflows, and teams.
Baseline and watch
Spend patterns are baselined per workflow; deviations beyond the norm alert immediately, not at invoice time.
Recommend the cut
The savings engine continuously compares your traffic against alternative models and prompt sizes, and quantifies each opportunity in dollars.
See it on your own AI stack.
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