PromptAudit: LLM Cost Per Feature
Tracks which AI features in your app consume the most tokens and cost, helping developers optimize prompt efficiency before bills spiral.
The Problem
AI app builders have no visibility into which prompts, features, or user actions drive LLM costs. A poorly engineered prompt can 10x token usage, but developers only discover this when the AWS bill arrives. They can't A/B test prompt efficiency or identify wasteful features without manual logging.
Target Audience
Solo and small-team founders building with Claude/GPT APIs, early-stage AI SaaS startups with <$50k/month spend, indie developers using Cursor/Bolt to ship AI features quickly.
Why Now?
LLM API costs are now a primary concern for bootstrapped founders; rising token prices (Claude 3.5 flux pricing) make optimization urgent. Vibe coding tools now handle dashboard/analytics easily.
What's Missing
Existing monitoring tools (Langsmith, OpenAI dashboard) show aggregate usage but don't connect token spend to specific product features or user behaviors. Developers manually log prompts or guess which features are expensive.
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