PromptAudit: AI Cost Attribution Engine
Tracks which features, user segments, and workflows consume the most API spend across Claude, GPT, and Gemini, automatically flagging cost anomalies and suggesting optimization routes.
The Problem
Teams building with multiple AI APIs have no visibility into which parts of their app are expensive—a single poorly-tuned prompt or runaway feature can silently drain thousands monthly. Existing billing dashboards show total spend, not causation. Engineers waste weeks debugging cost spikes because they can't correlate spend to actual user behavior or feature usage.
Target Audience
Solo founders and small teams (5-50 people) building AI-native applications on Cursor/Bolt/Lovable who are already in production but surprised by their monthly bills.
Why Now?
AI app costs are exploding and unpredictable; founders are actively hunting for spend control tools as Claude and GPT-4 usage outpaces their budgets. Langsmith/Helicone are enterprise-focused, leaving a gap for indie builders.
What's Missing
Existing tools treat AI as a black box cost center rather than attributing spend to specific features, prompts, or user cohorts. No product yet lets a founder see 'our image generation feature costs 3x more than expected' at a glance.
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