Inference Cost

The computing cost of running an AI model to respond to user requests.

Example

An AI product spending 4,000,000 on model usage to deliver 10,000,000 of revenue.

It can make AI products' gross margins much lower than traditional software.

Gross margin — Gross profit - revenue less the cost of goods sold - expressed as a percentage of revenue. It asks whether the thing being sold makes money.
Capital Intensity — The amount of capital a business needs to invest, in equipment, inventory or projects, to generate revenue and grow.

AI companies can have software growth with hardware-like costs; deep tech trades time for defensibility — AI businesses must be judged on the cost of running models and on what protects them from competitors using the same models. Deep tech companies face technical risk and long timelines before revenue, in exchange for harder-to-copy advantages. (12 min)
An AI product's margin and moat depend on what it does not own — Companies built on AI models carry specific risks: dependence on model providers, inference costs that grow with usage, rights to training data and outputs that are hard to evaluate. Diligence tests each. (11 min)