Know what AI is costing you
Because every call flows through the gateway, Gatelyr shows exactly where AI token usage and spend is going — by user, department, location, product, or model — and lets you set limits so a runaway bill is never a surprise at the end of the month, no matter how many teams are calling how many models.
The problem
AI spend often has no clear owner — nobody can say which team, product, or feature is driving the bill until finance flags a number that's already too large to explain.
How it helps
What this means day to day
See spend by user, department, or location
Answer "who is spending what, from where" without pulling together spreadsheets.
Set budgets by team and cost center
Set spending limits at the team or department level, get warned as one approaches, and cut off spend before a budget is blown.
Compare the cost of different models
Understand what the same workload would cost on a different model before you switch.
Keep model pricing current
Maintain up-to-date pricing across every provider and model, globally or per organization, so every cost figure reflects reality.
Build the report each stakeholder asks for
Assemble and save usage and cost reports tailored to any question — per team, per model, per period — instead of rebuilding a spreadsheet each time.
Catch a runaway workload early
Notice a spend spike from a specific team or feature the day it happens, not the month it shows up on an invoice.
Plan next quarter's AI budget with real data
Base next quarter's number on actual usage patterns instead of a guess.
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