Aito, a Helsinki-based machine learning startup that is developing “predictive database” technology, has raised €1 million in pre-seed funding, including from Nokia Chairman Risto Siilasmaa (via his investment company First Fellow Partners).
Others backing the round are Hermitage and UMO Capital, with funding from Business Finland. Previous Aito investors include Futurice and the company’s own founders Vesa-Pekka Grönfors, Antti Rauhala, Kai Inkinen.
Aiming to replace current machine learning tools that have a steep learning curve and generate only single-purpose models, Aito has built a predictive database for developers. Specifically, it lets users search existing information, make predictions and find hidden correlations.
Crucially, the results are said to be fully explainable and the tech can be integrated into existing software as easily as integrating a SQL query.
“The idea of an unconventional approach to AI and machine learning dates back for more than 10 years,” Grönfors tells me. “Antti, co-founder and chief scientist of Aito, started working with the concept already at the end of his studies and continued through the following years as a lead data scientist at Futurice [the European consultancy company].”
More broadly, Aito is founded on the premise that software developers are the new AI developers. There are some 23 million software developers in the world, and they increasingly work with machine learning or AI-related features, meaning it’s no longer only the domain of data scientists only.
“They require tools that are quick to adopt, support agile workflows and are familiar without specific knowledge of data science,” adds Grönfors.
“Aito.ai is a predictive database for developers who value quick time to market. It’s familiar as a database, yet provides the intelligence of machine learning… Predictions, recommendations, and explanations are provided in milliseconds over a beautiful API, using the entire Aito database as training data. Where traditional database gives the user, for example, five past purchases of an e-commerce customer, Aito can automatically predict the next likely purchases and explain what lead to such prediction.”
As an example, a subscription business could feed their product, financial, user and event data into Aito, and get out various business-critical predictions and insights, such as: predict demand, explain conversion, predict churn, optimise pricing, personalize content, recommend products, maximize lifetime value and more.
Already being tested in the wild, Aito is currently being used to automatically suggest categories for documents uploaded to contract management system; to find relevant movies based on similarity; and to automate conversational UI workflows and provide predictions on which customer complaints will escalate.
“Futurice, where Aito was spun off from, uses Aito to find who knows about a certain topic within an organization. Simply by typing a term, Aito uncovers the people with such knowledge based on several internal data sources, with no taxonomy or tagging needed,” says Grönfors.
Meanwhile, the Aito business model is a classic enterprise SaaS developer play: the pricing model is based on the size of a user’s data set and volume of queries. Pricing starts from €6 per day and there is a free trial period.