Typical use cases are:

* fraud and anomaly detection

* recommender systems

* predictive analytics (churn, forecasting)

* image recognition

With image recognition, we hit 98% accuracy on a recent project. Until a few years ago, that was unheard of, and it's simply not possible with other algorithms, so for many companies, deep neural nets can make a significant difference.

Here are two news stories about work we've done for clients:

Making deep learning accessible on Openstack https://insights.ubuntu.com/2016/04/25/making-deep-learning-...

For Canonical, we built a solution that predicts server breakdowns.

For France Telecom's mobile unit, Orange, we built a fraud detection solution using anomaly detection:

http://www.orangesv.com/blog/orange-deep-learning-work-featu...