In our previous blog post, we introduced the new database category: predictive database. Now we’ll go deeper into how to use this predictive database.

Machine learning powered features, like recommendations and personalization, have become commonplace and as such the new normal. Customers have started to expect these smart features and the internal stakeholders and POs have started to demand them.

How can Aito’s predictive database be used to forecast Freska's customer churn?

A lot has been written about the importance of Robotic Process Automation (RPA) and why it is necessary. And even more, how combining both AI and RPA is combining the best of two worlds.

Machine Learning changes the design of intelligent conversational bots. In order to provide the same capabilities without using ML, an application would have to ask the user to answer a long set of questions, which would negatively impact the user experience.

Aito, a Helsinki-based startup that has built a predictive database for developers, has raised $1.1 million in pre-seed funding.

Startup life. The lure of setting your own schedules and priorities. Being your own boss. Being able to focus, if not on one thing, then at least on one dimension of things.

Every developer knows that one key to high productivity is making the feedback cycles as short as possible. The usual AI-workflow is not really tuned for this, since the training phase can take ages.

I’ve set out to change the world, and there are two lines to the story.