A machine learning model you haven’t deployed is worth the same as one you haven’t built... nothing.

The fact is, most models built by data scientists never get deployed in production.

That’s wasted time and wasted money. And there’s a simple reason for all of it:

Whenever a new model is developed, tested and proven out, it still has to be rebuilt in a production language, usually by an engineer.

Coding for production takes time.

And time isn’t something software engineers usually have a lot of.

So the models sit and wait for deployment, pushed aside again and again for higher priorities.

Meanwhile, they’re nothing but investment without return, dragging down your bottom line.