A demo shows that something works once, in a setting the team chose. A technical diligence asks whether it keeps working, and at what cost. In the AI startups I look at, the gap opens in three places.
1. The cost of a completed task. A product can look healthy while every task it completes costs more than the customer pays. It stays hidden while usage is small, then surfaces as the company grows.
2. Results on unprepared data. Demos run on data the team has seen. Customers bring data nobody has seen. The difference between the two is where most disappointment starts.
3. Dependence on one outside vendor. Many AI products rest on a single model provider. That’s a reasonable start, but it ties margin, performance and roadmap to decisions the company doesn’t control.
None of this appears in a demo. All of it appears within a month of real use. Investors often meet it after the cheque is written. Founders who find it first have a better conversation.
A technical diligence sprint takes one to three weeks and ends in a report you can decide from. If you’re assessing an AI company, or preparing yours for a raise, book a conversation.