Meet Cohort 08: Adiona

Q: Tell us a little bit about your company and how it is using innovative methods to solve urban challenges? 

A: Adiona is an AI-powered SaaS API that allows logistics, supply chain, and mobile workforce organizations to reduce costs, time, and environmental impacts while simplifying operations.  Our deep learning models ingest data from sources like ERPs, transport management systems, IoT feeds, and more to create digital twins of logistics operations. Once twinned, the model can be used to diagnose efficiency problems, simulate changes, and deliver optimization solutions. Adiona is being used by major multinational organizations to automate workforce and delivery scheduling, optimize last mile fleets, and more.

Q: What inspired you to start your company? 

A: The name Adiona is the Roman Goddess of the Return Journey. We are passionate about improving city life by reducing the burdens of transportation on them and can do so by commercializing unique academic research into large enterprises and logistics software platforms.

Q: Tell us why you decided to apply to the URBAN-X Program? What were the key takeaways for your company during the program?

A: The URBAN-X team shares the vision and courage of startup founders. They know that real disruption through innovation requires risk and are willing to help founders who are bold and action oriented.  They helped us mature our product direction, implement a real growth framework for scale, and prepare for the next phase of our journey.

Q: What advice to you have for other startups and/ or inspiring entrepreneurs looking to reimagine urban life?

A: Don’t wait! Contrary to what some might say, the future is NOT here today. Many of the most inspiring new innovations are very difficult to implement in traditional companies and government organizations that truly run cities. It’s crucial to iterate rapidly, continuously update and improve your vision, and prove your value proposition quickly if you are going to survive long enough to thrive.


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