Today, Artificial Intelligence (AI) startup Aito announced it’s latest funding round in which it raised €1.6M from B2B software investor henQ.

Slush lightened Helsinki up once again during the November darkness. For those who have not visited Finland during this time of the year: don’t. Unless you’re coming to Slush.

Matching is one of the most common, yet worst recognized, problems in both software engineering and data science fields.

There needs to be a tool that allows testing with datasets from various sources without a massive effort of normalisation and feature engineering. A tool that allows iterating the use case with real predictions, with real users.

In the following post, I will share my top learnings from leading the development of a SaaS platform called Aito.ai

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.

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.