Culpa traces every AI dollar

Culpa targets a painful gap in the AI stack: provider invoices show what was spent, but rarely explain why.

• –Conversation-level attribution can expose expensive workflows that aggregate dashboards hide
• –Retry-loop visibility turns silent margin leakage into an actionable engineering problem
• –Customer and feature cost breakdowns can inform usage limits, packaging, and pricing decisions
• –Forecasting planned features before deployment connects product planning directly to infrastructure economics
• –Local-first deployment is a strong differentiator for teams that cannot send prompts or traces to a third-party SaaS