Finance
Full visibility into AI spend weeks before getting the invoices
Attribute every AI dollar to a team, key, model, and provider, and catch spikes before the bill arrives.
Spend by project, current month totals, savings, and budget status in one view.
Attribution
Team + key
Pricing
Volume-based
Alerts
Spend spikes
Support
$18.4k
Largest driver this month.
Engineering
$8.1k
Coding assistant spend stayed flat.
Research
$3.2k
Candidate for cheaper route.
New capabilities
What your team gains with Concentrate
Explain the bill
Break token spend down by team, project, feature, key, model, and provider.
Set limits early
Use limits and alerts before usage turns into invoice surprise.
Use volume terms
When spend gets serious, move toward usage-volume pricing and better provider rates.
Where it fits
For finance teams watching AI costs become a real line item
Once AI spend moves from experiments to material usage, finance needs attribution, limits, and a shared language with engineering.
Cost center attribution
Assign usage to teams, projects, features, customers, and keys so finance can explain the bill.
Budget and performance metrics
Review spend limits, latency spikes, unusual usage patterns, and model choices before the month closes.
Savings analysis
Track savings from routing, caching, and token credits instead of only seeing gross provider invoices.
Engineering context
Tie numbers back to models, providers, requests, and owner keys so cost conversations are specific.
Finance basics