PromptAudit: LLM Cost Per Feature
Tracks which features in your app consume the most LLM tokens and costs, helping AI app builders identify wasteful prompts and optimize spend before it scales.
The Problem
AI app builders using Claude, GPT, or other APIs have no visibility into which specific features or user flows are burning tokens and money. They ship features, users love them, then the bill surprises them. By then, architectural changes are expensive. Most devs only notice overspend after it's too late.
Target Audience
Solo and small-team founders building with Cursor/Lovable/Bolt who use LLM APIs; particularly those with chat, generation, or analysis features that call APIs per-user action.
Why Now?
AI app development is accelerating faster than cost awareness; devs are shipping production apps without cost observability. LLM pricing is opaque and can double overnight if one feature goes viral.
What's Missing
Existing observability tools are enterprise-focused and require instrumentation. There's no lightweight, feature-level cost dashboard for indie builders who just want to know: 'Is my chat feature or my image gen feature bleeding tokens?'
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