Know your AI cost. Defend your margin. Price with proof.

The AI Margin Ledger captures every LLM, image, and embedding call as a cost-stamped event in your own storage — then turns it into cost reports, model what-if simulations, pricing-tier design, and margin alerts.

See how the ledger works

The real risk

The real risk isn't your AI bill. It's not know hwo to iterpret.

You're charging a flat price for a cost that swings 100× per call. Without per-call economics, every pricing and model decision is a guess.

Tier that loses money

A mismatched total, missing party, or invalid container value stalls the shipment.

Power user eating the margin

Wrong quantities, prices, totals, or currencies become downstream exceptions.

Model swap you can't justify

A smudged member ID or missing intake field can quietly break the workflow.

Board asks "what's your gross margin?"

Ops teams find the error later, then restart the same document loop.

Provider price hike, invisible until the invoice

The document did not add up, but the system accepted the value anyway.

Pricing set by gut, not data

The customer sees the exception before your team catches the bad field.

How it works

From a single line of code to a board-ready margin report

From a single line of code to a board-ready margin report — without a database, a dashboard server, or a vendor holding your data.

Record

Add ledger.record({…}) after each AI call. Fire-and-forget, buffered, never blocks your user.

Stamp

Each event is cost-stamped (multi-modal: tokens, images, characters) and provenance-tagged, then written to your object storage.

Query

DuckDB reads your Parquet on demand — no server, no database to run. Cost reports, simulations, forecasts.

Simulate

You change pricing or models in your own product. The ledger informs every call; it never makes one for you.

Send one painful document workflow.

We’ll run the full end-to-end process on your real documents and show what can safely auto-pass, what needs review, and what clean output would look like.

Start a pilot

Beyond AI observability

AI observability tools tell you a call happened. They were never built to tell you if you made money on it.

OCR asks: "Show me the trace."

"Show me what a model swap saves before I make it."

Our System: Is this safe to use?

"What margin did we make, by tier and user?"