November 24, 2020 • 1 min read
I had the honor to visit the Formulated Automation podcast a few weeks ago. I had gotten the invitation from Marc Percival in October. I had engaged with Reddit’s RPA subforum, and Marc had started to believe that Aito - our predictive database - could be interesting for his audience.
I believe that the reason why Aito was seen as interesting is the same reason why Robot Framework has seen exponential growth, and why Robocorp’s Antti Karjalainen has been quite successful in making a splash in the various Podcasts and in the social media.
The reason for the interest are the megatrends of both RPA and AI/ML democratizations, that are addressed by Robot Framework and by Aito-like solutions. Especially the midsized companies are looking for easier and more affordable ways to do RPA and AI/ML to make their economics to work, and to serve this need Robocorp and Aito have also joined their forces:
In the Formulated Automatics podcast I go through explaining Aito’s inspiration, the reasons why RPA+machine learning is rewarding, why Aito fits well the RPA space and also some practical use cases.
As a spoiler, Aito was inspired by the obvious need in the market to make AI / machine learning easier and more affordable, and by the observation that the merging of database and machine learning could make this possible. With Aito’s predictive database any (RPA) developer can do machine learning with predictive queries.
As another spoiler: RPA+ML is rewarding, because business processes tend to be very regular and easy to imitate with machine learning. It’s not unforeseen, that you could automate two thirds of work simply by imitating the way the expert does the process.
On the other hand Aito fits very well with the RPA space, because RPA has a need for such an easy-to-use AI tool that any RPA developer can use and that is affordable enough to not compromise the delicate business cases of this cost-sensitive industry.
But now: what about the use cases? Perhaps you want to listen to the podcast and hear about them yourself. Also please forgive me, if I rambled a bit or went too much into details. I'm pretty technical and it was my first podcast. ;-)Back to blog list
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