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AI Cost Governance

Turn an Unallocatable AI Invoice Into a Chargeback Model

Per-turn token counts priced by model, rolled up per developer, per team, and per repository, with budget thresholds that fire before the invoice does.

The Situation

AI Became a Line Item Before It Had an Owner

AI spend grew from an experiment to a recurring cost without ever acquiring the structure that other infrastructure has: no tags, no cost centers, no per-team allocation.

Finance asks a reasonable question - what are we paying for AI, and who is spending it - and engineering has to answer from provider dashboards that know nothing about teams.

What Goes Wrong Today

Provider Dashboards Are Not Cost Management

  • Org-level totals. Provider invoices do not break down by team, repository, or developer.
  • Multiple providers. Spend is split across several vendors with incompatible reporting.
  • No leading indicator. The first signal that spend doubled is the invoice, 30 days late.
  • No model attribution. Nobody can tell an expensive workflow from an unnecessarily expensive model choice.
What Kraitos AIDR Does

Cost From the Same Telemetry as Everything Else

  • Per-turn input, output, cache read, and cache write token counts captured at the endpoint
  • Model-aware pricing across model families - Opus, Sonnet, Haiku, GPT-4 class, and others
  • Rollups per developer, per team, per model, and per repository with 30-day trends
  • Budget and usage threshold policies that alert while spend is still accruing
  • Chargeback-ready CSV exports for finance
  • Adoption metrics alongside cost, so a spend increase can be read against usage
What You End Up With

A Defensible AI Budget

  • What did each team spend on AI last month, and on which models?
  • Which developers are near their token threshold this week?
  • Did the increase come from more usage, or from a more expensive model?
  • Can finance allocate AI cost the same way it allocates cloud cost?
Cost and usage analytics with total cost, cache hit ratio, cost over time chart, and per-developer breakdown
Cost and usage - spend attribution by developer, repo, model, and team, with cache hit ratio and a 30-day trend.

See Kraitos AIDR in Action

Deploy in 60 seconds. Get answers in 24 hours. Stop guessing what your AI-augmented organization is doing.

[email protected]kraitos.io