Tracks spend across
OpenAI
Anthropic
Amazon Bedrock
Azure
Your own models
The problem
Token bills arrive later, split across vendors, licenses, and teams. Nobody can say which team, agent, or task spent what, or whether a cheaper model would have done the job.
What changes when every model call goes through xpander
Bills arrive later, split across vendors, licenses, and teams
Every model call tracked by team, model, agent, and end user
Limits only at the vendor account, if anywhere
Budgets per group, member, key, and agent, and per task
Found when the invoice lands
Owners warned as budgets approach their limits
Routine work runs on the same expensive model
Routine work moves to cheaper or self-hosted models, without changing apps or agents
Usage on your own licenses stays out of view
Usage on licenses you bring yourself is tracked too
A separate AI seat for every employee
Non-technical employees use the AI Workspace instead
How xpander helps
Every model call goes through the AI Gateway.
01
One view of spend
Every model call goes through the AI Gateway, so cost is tracked by team, model, agent, and end user, including licenses you bring yourself.
02
Budgets at every level
Per group, member, key, and agent, and per task, so one large job can never run away. Owners are warned as budgets approach their limits.
03
The right model for the job
Route routine work to cheaper models, models in your cloud account, or open-weight models on your own GPUs, without changing apps or agents.
04
Fewer AI seat licenses
Give non-technical employees the AI Workspace instead of a separate AI seat each.
Spending limits for every group, key, and agent
