Aiseedo artificial intelligence creates smart autonomous IoT and robotic systems.

Introducing Aiseedo

Aiseedo provides artificial intelligence (AI) software that makes IoT and robotic systems smarter, by giving them the skills to autonomously predict, adapt and react to changing situations.

Aiseedo software is currently offered as an on-demand SAAS / Cloud service for maximum flexibility. Its integration is facilitated by Aiseedo’s innovative framework, capable of understanding and automatically integrating multiple complex data streams, such as user input and sensors used in IoT systems or robots.

At its core, the Aiseedo AI technology is based on several years of research. It integrates state-of-the-art deep learning, reinforcement learning and convolutional network technologies.

A great application example is the ability of an assisted living system to leverage multiple sensors and human input to understand and adapt to an elderly person’s living patterns. This will ensure not only their safety but also their health and mental wellbeing.


Businesses leveraging Aiseedo’s software benefit from fast-tracked, flexible access to cutting edge artificial intelligence to enable smarter, reactive, autonomous IoT systems and robots.

Five years from now...

We envision Aiseedo to provide real-time artificial intelligence for automated systems, namely in the fields of IoT, robotics and transportation.

A little more info

Aiseedo’s showcase displays a cookie monster game where the Aiseedo AI (artificial intelligence) software learns for itself both the context and rules of the game, as well as how to best pilot the cookie monster to obtain a killer score.

Imagine that the cookie monster is an IoT system (vacuum cleaner, lawnmower, or an HVAC system): it learns by itself about its surroundings and control options to succeed in the goals given (optimal cleaning /mowing or optimal temperature to match environmental and financial targets).

Such intelligence is necessary for IoT systems to intelligently and autonomously reach their goals, in environments, which involve multiple complex inputs.