EDI is an incubation programme run by 20 partners across Europe.
It gives the most innovative “Big Data” startups the opportunity to tackle real world challenges set by corporates across Europe, such as improving road safety in Barcelona or predicting fraudulent transactions in supermarkets.
ZYLK Industry is taking part in EDI to solve the challenge set by Volkswagen Navarra: Predictive maintenance models for industrial robots in body shop. Our approach is to develop Industrial Robots Insights (IRI), a product capable of reading, processing and visualizing data from any Siemens PLC connected to either KUKA robots and FANUC devices. The first step is to format the datasets and map the variable values to obtain the correct working model for each robot axis. The next step is the mining and analysis of the formatted datasets. Zylk Industry will train a deep learning algorithm after several robot behaviour cycles in order to predict to predict problems or failures in the robots. The last step is the visualization and alarm detection.
Benefits include up to €100k in equity-free funding, mentoring, workshops, access to a free cloud environment, and the chance to connect with and be recognised by major European organizations.
Each year of EDI incubation process is divided into three progressive phases, in which only the best startups pass to the next level: ‘Explore’, ‘Experiment’, ‘Evolve’.
On 17 and 18 October, ZYLK Industry will travel to Berlin with 30 other startups for the first ‘Explore’ phase. Here we will take part in a datathon, practice our pitches, receive €5k (equity-free) and meet face to face with the corporates. Finally, a jury will decide which 16 startups will pass to the next ‘Experiment’ level.
Take a look at the EDI startup portfolio to see our team photo, description and a 30 second video.
To read more about EDI, please visit the website: www.edincubator.eu
Follow our journey through EDI:
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 779790.