“We learn behaviors of what it looks like to leave,” said Michael Suswal, Standard Cognition’s co-founder and chief operating officer. Trajectory, gaze and speed are especially useful for detecting theft, he said, adding, “If they’re going to steal, their gait is larger, and they’re looking at the door.”

Once the system decides it has detected potential theft behavior, a store attendant will get a text and walk over for “a polite conversation,” Mr. Suswal said.

Predicting theft requires a lot of data about shoppers, much of which does not exist yet — “or at least no one is willing to give it to us,” he said.

So a few days before Standard Market opened, Standard Cognition hired 100 actors to shop there for four hours. In Japan, the team has worked with a convenience store chain, whose name it has not disclosed, in a very useful data collection effort.

Standard Cognition said that unlike facial recognition, it did not collect biometric information, a possibility that has troubled privacy experts watching the technology evolve.

The growth of cashierless technology could hurt the American labor force; there are nearly five million retail sales workers in America. But as Mr. Suswal has pitched Standard Cognition’s technology, he said, he has found that most shop owners are not looking to replace workers. Instead, they want their workers wandering the stores more, in hopes of luring shoppers back into brick-and-mortar retail.

“They all talk about new services, making shopping more fun, making it worthwhile to shop offline,” Mr. Suswal said.