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MarginDash – See which AI customers are profitable

MarginDash – See which AI customers are profitable

by gdhaliwal23·Feb 13, 2026·1 point·1 comment

AI Analysis

●●SolidSolve My ProblemEye Candy

Real per-customer margin tracking when every founder has this exact blind spot.

Strengths
  • Stripe sync + token-count logging gives genuine margin visibility founders lack today
  • Cost simulator ranked by MMLU-Pro benchmarks beats manual model shopping
  • Clean dashboard design makes painful data (negative margins) immediately actionable
Weaknesses
  • Solves a real but narrow pain (AI SaaS margin math) vs. broader audience
  • Cost tracking already exists in Lithic, OpenRouter; this adds Stripe linkage but isn't revolutionary
Category
Target Audience

SaaS founders using AI APIs

Similar To

Lithic · OpenRouter · Anthropic billing dashboard

Post Description

I built MarginDash because I couldn't answer a basic question: which of my customers actually make me money after AI costs? My Stripe dashboard showed revenue going up. My OpenAI bills showed costs going up faster. I had no way to connect the two at the customer level.

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.

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