MarginDash – See which AI customers are profitable
Plugs the gap between Stripe and OpenAI bills—finally see which customers are actually profitable.

Real per-customer margin tracking when every founder has this exact blind spot.
SaaS founders using AI APIs
Lithic · OpenRouter · Anthropic billing dashboard
MarginDash is a few line SDK integration (TypeScript, Python, or REST) that tracks model usage per customer and connects it to revenue — either through Stripe sync or by passing revenue directly in the API call. You get a per-customer P&L showing revenue, cost, and margin.
A cost simulator lets you pick any feature, swap the underlying model, and see projected savings. Models are ranked by intelligence-per-dollar using public benchmarks (MMLU-Pro, GPQA, AIME) so you can find cheaper options that aren't actually worse. Budget alerts email you before a customer or feature blows past a threshold.
The pricing database covers 100+ models across OpenAI, Anthropic, Google, AWS Bedrock, Azure, and Groq with daily updates — so cost calculations stay accurate without you maintaining a spreadsheet. The SDK only sends model name, token counts, and customer ID. No prompts, no responses.
Solo founder, built the whole thing for $239.72 in AI costs (wrote about that too). Currently free while I get feedback — would love to hear what you think, especially about the cost simulator.
Plugs the gap between Stripe and OpenAI bills—finally see which customers are actually profitable.
Pulls data straight from ~/.claude/projects and only uploads aggregated metrics (tokens, cost, calls) via a 6-letter invite code flow — nice and surgical. The one-command npx init + join UX and a show-data privacy audit button make adoption trivial, but it’s strictly useful only to groups already using Claude Code and requires trust that aggregated uploads are enough for your threat model.
Another embedded AI builder competing with Retool, Bubble, and internal tooling platforms.
AI observability dashboard when LangSmith and Arize already dominate this space.
Claude Code usage dashboard reading local files—fills exact gap Anthropic didn't address.
Finally tracks silent AI struggle per account, solving the blind spot in Amplitude and Datadog.