How do I track AI API costs without a spreadsheet?

MarginDash replaces spreadsheet-based AI cost tracking with an SDK that auto-tracks usage, daily-updated pricing across 100+ models, and automatic Stripe revenue reconciliation — no manual entry or stale formulas.

How often do AI model prices change?

AI model prices change frequently — OpenAI, Anthropic, and Google all adjust pricing regularly and launch new models monthly. MarginDash syncs pricing daily across 100+ models so you never calculate costs with outdated data.

When should I stop tracking AI costs in a spreadsheet?

Switch when you add a second AI model, lose track of a customer's profitability, or realize your pricing data is out of date. If you have fewer than 5 customers and use a single model, a spreadsheet still works.

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Stop Tracking AI Costs in Spreadsheets

Every time a model price changes, your spreadsheet breaks. MarginDash is the spreadsheet that updates itself.

If you're tracking AI costs in Google Sheets or Excel — pulling token counts from logs, looking up model pricing, and manually calculating margins — you know it doesn't scale. MarginDash replaces that workflow with an SDK that auto-tracks usage, daily-updated pricing for 100+ models, and automatic Stripe revenue reconciliation.

Feature	Spreadsheets	MarginDash
Automatic cost tracking	Manual entry	SDK auto-tracks
Real-time data	Always stale	Real-time
Revenue/margin per customer	Manual formulas	Automatic
Budget alerts	Not available	Email alerts
Cost simulator	Manual math	Built-in
Daily pricing updates	Manual	Automatic (100+ models)
Multi-provider normalization	Custom formulas	Built-in
Scales past 50 customers	Painfully

The spreadsheet worked — until it didn't

Every AI-powered SaaS starts with a spreadsheet. You pull token counts from logs, look up pricing on vendor websites, and manually calculate cost per customer. It works for 5 customers. At 50, it's a part-time job — and by then you're spending more time in VLOOKUP hell than building product. MarginDash automates the entire pipeline: SDK tracks usage, pricing updates daily, Stripe syncs revenue, and margins calculate in real time.

Prices change weekly. Your spreadsheet doesn't know.

OpenAI drops prices, Anthropic launches a new model, Google adjusts Gemini rates — it's happening constantly. Every change means manually hunting down the new pricing, updating your formulas, and hoping you didn't miss one. MarginDash syncs pricing daily across 100+ models from every major vendor. Every time you add a new model via Groq or Bedrock, it just works — no 4 hours in VLOOKUP hell.

From manual entry to automated margin tracking

Instead of exporting logs, parsing token counts, and pasting into cells, you call addUsage() with the model and token count, then track() with the customer ID and revenueAmountInCents. The cost is calculated server-side using daily-updated pricing. Revenue reconciles against actual Stripe data. No manual work, no stale data, no broken formulas.

When to keep the spreadsheet

If you have fewer than 5 customers, use a single AI model, and don't mind updating costs manually each week, a spreadsheet works. Switch to MarginDash the first time you add a second model, lose track of a customer's profitability, or realize your pricing data is two weeks out of date.

The metric that matters

Realized margin, not estimated cost

Other tools estimate cost from tokens. MarginDash reconciles actual Stripe revenue against AI costs — accounting for coupons, tiered pricing, and annual credits. You see who's profitable and who's underwater.

Customer	Revenue	Cost	Margin	Margin %
Plexo Health	$233.25	$277.20	-$43.95	-18.8%
Vantage Ops	$358.86	$421.66	-$62.80	-17.5%
Stratos Cloud	$417.32	$357.64	$59.68	14.3%
Canopy Labs	$350.89	$316.85	$34.04	9.7%
Prism Data	$105.80	$87.23	$18.57	17.6%

Connect AI costs to revenue in a few lines

Other tools estimate cost from tokens. MarginDash reconciles cost against actual revenue. Pass revenueAmountInCents and see realized margin — not guesswork.

// After your existing AI call
md.addUsage({ vendor: "openai", model: response.model,
  inputTokens: response.usage.prompt_tokens,
  outputTokens: response.usage.completion_tokens });

md.track({
  customerId: user.id,
  eventType: "summarize",
  revenueAmountInCents: subscription.amount
});