Can you go into more detail on the image recognition? Do you mean AR-style image recognition ("find exactly this image"), or more image /classification/ (here's what's in this image)?
Both. Given an example: Sentiment analysis on a car show floor detecting sentiment of buyers. It can also just be binary: "Is this object present or not?"
Run that by me again.. So you have an algorithm that attaches to a camera in a car shop and can determine the likelihood that a buyer is interested in the car?
That's pretty awesome and scary in equal measure..