Mollom is one of those cool SaaS companies every developer dreams of creating when they wrack their brains looking for a viable software-as-a-service startup. Mollom profitably runs a useful service—spam filtering—with a small group of geographically distributed developers. Mollom helps protect nearly 40,000 websites from spam, including one of mine, which is where I first learned about Mollom. In a desperate attempt to stop spam on a Drupal site, where every other form of CAPTCHA had failed miserably, I installed Mollom in about 10 minutes and it immediately started working. That's the out of the box experience I was looking for.

From the time Mollom opened its digital inspection system they've rejected over 373 million spams and in the process they've learned that a stunning 90% of all messages are spam. This spam torrent is handled by only two geographically distributed machines that handle 100 requests/ second, each running a Java application server and Cassandra. So few resources are necessary because they've created a very efficient machine learning system. Isn't that cool? So, how do they do it?