Synapse Partners

Even before the pandemic arrived, urban mobility was changing quite dramatically. The change was initially driven by the need for convenience and was enabled by the risking disposable income of urban dwellers, because of booming economies globally. Ride hailing, car sharing and micromobility entered the fabric of our urban multimodal transportation. On-demand delivery of restaurant food, groceries, and other items became a reality around the world. Pilots of autonomous passenger vehicles and trucks were growing. New mobility became a reality. The pandemic changed the urban movement patterns. It decreased the movement of people but increased the movement of goods. New mobility was morphing in real time and becoming an even more integral part of urban landscapes across the globe.

New mobility is the ability to move people and goods using a coordinated combination of vehicles producing zero emissions, are automated or autonomous, and connected and transport services that are offered on a scheduled or as-needed/ondemand basis. New mobility is first adopted by cities because:

1. It is most urgently needed there due to the mobility-related problems cities face.

2. It is where fixed-scheduled and on-demand transportation providers and goods delivery companies converge.

3. Cities are environments of the right complexity level where the success of new mobility can be attempted and measured.

 New mobility utilizes four main ingredients:

 1. Digital platforms that enable accessing a wide range of applications and are used by a variety of fixed-schedule and on-demand services that move people or goods using privatelyowned and shared advanced technology vehicles.

 2. Vehicles producing zero emissions, mostly be being battery electric, are automated or autonomous, and connected. we call these ACE vehicles, standing for Autonomous/ Automated, Connected and Electrified.

 3. Intelligent and highly instrumented physical and digital transportation infrastructures that incorporate a city’s rules and policies and make possible for these services to be offered through these vehicles.

 4. Innovative business models through which new mobility is monetized providing a return on the massive investment that is necessary to make it a reality.

As the world is starting to emerge following the restrictions that were necessitated by the pandemic, now is the right time for planning, and implementing new urban mobility. The covid-19 pandemic has led most of us to change our norms. It has changed the way we work, shop, and entertain. Many of these changes have resulted in people a) moving less because items or services are delivered to them, b) moving shorter distances that can be covered either by walking or using micromobility, and c) adopting zero-emission vehicles faster. During this period, together with our efforts to develop autonomous vehicles that can operate reliably in larger and more complex urban environments, more than ever we are becoming aware of the pivotal role AI can play in new mobility. This is because vehicles, platforms, and infrastructures are big data generators, and their complexity almost dictates the incorporation of machine intelligence

“As it is introduced into increasingly more complex environments and its adoption accelerates, the need for AI - based solutions will become even more urgent than it is today providing continued opportunities to entrepreneurial team and their investors”

AI will provide the key differentiator of the in-cabin experience the new vehicles will offer to consumers and businesses, the systems that operate and manage vehicle fleets, the infrastructures cities use to manage and monetize their transportation systems, and the multitude of intelligent applications that will be developed around new mobility. While developing autonomous vehicles and scaling mobility services have required large capital investments on an ongoing basis, which has proven problematic for many startups, investments in AI software startups developing intelligent applications for new mobility presents entrepreneurs and investors with opportunities for outsize returns. Most frequently such a statement was justified by acknowledging the abundance of data, combined with open-source software, cheap computing, massive storage, and broadband networking.

Since founding our firm in 2016 we have been investing exclusively in early-stage startups developing enterprise software AI applications. At least half of our active portfolio has always comprised of startups working on new mobility applications. The experiences working with the entrepreneurial teams of these companies have led us to the following conclusions which we continue to apply in every potential investment we evaluate and every portfolio company we support:

 1. Data is important but it is more important to own large sets of proprietary data that can be properly, easily, and inexpensively be labeled. The proprietary data creates important barriers to entry. Being able to properly, easily, and inexpensively be labeled, preferably without human intervention provides an important barrier to entry. We invested in Safegraph and Miles for this reason.

 2. AI is more than machine learning. There is no question that through data-driven learning using a variety of neural network methods and architectures we have been able to automate tasks that just a few years ago seemed impossible for a machine to accomplish. However, we have found that entrepreneurs who are able to consider the entire set of knowledge-based and datadriven learning and reasoning approaches, most frequently combining the two in their effort to solve a hard industry problem, typically come out with the solutions that enable to erect the highest barriers to entry. Humanising Autonomy, Stipple, and Connected Travel are mobilityrelated portfolio companies that have demonstrated this power.

 3. Open-source software helps expedite a solution’s development but creating proprietary scalable algorithms that can be incorporated into larger solutions of new mobility problems using “systems thinking” provides important advantages in the long run. In these days when every single market, no matter how small, has multiple competitors because we have cracked the code on how to stand-up startups, we always look for the differentiated, algorithmic IP a team brings to the solution that defines their company. Awake Mobility, Stipple, and Divergent are prime examples demonstrating this importance.

New mobility will continue to evolve over the next 30- 40 years. As it is introduced into increasingly more complex environments and its adoption accelerates, the need for AIbased solutions will become even more urgent than it is today providing continued opportunities to entrepreneurial team and their investors. The conclusions reached from our efforts with such solutions to date will continue to serve as important aids to both entrepreneurs and investors.