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Meet Orbem, a startup with 7 team members from 6 different nationalities! Orbem is working hard during the EXPERIMENT phase of EDI incubation programme, growing their solution to transform the poultry industry towards a sustainable and animal friendly future.

Can you tell us how you came to your Startup idea? We would also love to know more about your team, what makes your dynamic so promising and impactful?

Orbem was created as a spin-off of the Technical University of Munich, where we were doing research at the intersection of Artificial Intelligence (AI) and Magnetic Resonance Imaging (MRI). We decided to put our technological expertise into practice when we heard about the challenges the poultry industry is currently facing: the wasting of over 9 billion perfectly edible infertile eggs and the killing of over 7 billion 1-day-old-males.

Our international and interdisciplinary team makes Orbem a very unique Startup. With 6 different nationalities from 7 team members, we cover all of the required domain expertise – ranging from reproductive biotechnology and avian embryology to MR imaging and advanced AI – and bring forth years of industry and entrepreneurship experience. We are excited about combining our strengths to transform poultry towards a sustainable and animal friendly future. By doing so, we can create positive ripple effects across our society, our environment, and our economy.

What makes your solution unique? What is the impact you are trying to achieve?

Our AI-powered imaging solution is unique in three aspects: flexibility, speed, and safety. Our technology is flexible enough so we can rely on the same machine to tackle different classification tasks, such as day 0 predictive analytics for fertility detection and early-stage sexing. This classification happens at high-speeds and thus can be used within high-volume industrial settings. Finally, our technology is completely contactless, providing tremendous advantages in food safety and biosecurity.

By classifying eggs in a contactless and automated procedure, we hope to achieve impact to the triple-bottom-line:

  1. People: we’re feeding the world by introducing billions of eggs into the global food market.
  2. Planet: We’re preventing the unnecessary killing of billions of 1-day-old male chicks, reducing food waste and energy consumption along the way.
  3. Profit: We’re creating new revenue streams, increasing hatchery productivity and efficiency, and dramatically reducing incubation costs.

 

 

What challenge have you selected for the EDI incubation programme and why did you choose it? 

We chose a track 3 challenge – bring your own data provider – because MRI datasets of chicken eggs are very hard to come by! Our data provider supplied a dataset of hundreds of MRI volumes together with the corresponding ground truth label. We then used the data to develop our own AI models to classify each individual egg.

 

For a few months now, you have been working hard in the EDI Experiment stage, developing your Big Data solution even further. Can you please elaborate on your progress and how have you evolved during the acceleration process? How was your experience working with your Data Provider?  

Participating in the EDI Experiment stage has helped us grow significantly. Most importantly, we evolved from lab-based results to an actual computational MVP that can handle the large data streams required by our customer. We also expanded on our classification capabilities by including important features for the poultry industry, such as the measurement of the egg position, quality, and volume before it is incubated. In collaboration with our data provider and potential customers, we refined the economic value of providing these data to the hatchery before they incubate the eggs, empowering them to efficiently manage the incubation process.

 

 

Participating in the EDI Experiment stage has helped us grow significantly. Most importantly, we evolved from lab-based results to an actual computational MVP that can handle the large data streams required by our customer.

After joining and benefiting from the tools EDI provided you, what is your next step? 

Our next step is to install our first MVP inside a hatchery and demonstrate how our solution works under real hatchery conditions. This installation will allow us to collect large amounts of data to further refine our models and improve the performance of our systems. Thereafter, will continue growing our team and scaling our technology to completely transform the way we produce food to satisfy the needs of a rising population.

Finally, what would you say to a startup considering applying to EDI?

It is definitely worth applying! Besides funding, the support network that EDI supplies is very valuable. The EDI personnel are genuinely supportive and helpful and a great variety of trainings are provided. While some trainings are closer to our current needs than others, every training provided valuable insights into building and creating a big data startup. Also, hard deadlines are always an extra motivator to keep the project moving forward.

Liked what you read?

EDI 3rd Open Call is coming on the 17th of March! Learn more about the programme and see if you have what it takes to apply!

 

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