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Case study

Automotive: A Partner in Expansion

8 Nov 2023
Close up to hands on the wheel. Concept of machine learning applied to automotive industry.Download Case Study

Going beyond initial project scope to add increasing value as a true ally

In this world of ever-growing technology, many businesses are turning to niche specialists to help them
achieve their goals. While this can give them access to the best-of-the-best, it can also lead to
integration challenges and scope creep. For startups with limited resources, it is essential to find a true
partner who can meet their multiple needs and help them scale and expand.

One such startup partnered with a top German carmaker to develop a machine-learning model
for driver safety using sensor data. Unlike many solutions that relay detected events like sudden
acceleration and lane shifts to a backend platform, this startup processed data directly on
mobile devices to avoid delays and provide real-time insights.


About the Startup


The solution was originally created for fleet applications within the transportation and logistics
industry. However, because of a leadership change, it shifted its value proposition to address
the broader need for vehicle safety solutions. Instead of being part of a specific car, this solution
would be connected to the individual through a mobile device, offering a sphere of protection
anytime that person was in a moving vehicle. Not only would the solution report problematic
driving behavior, but it could also automatically notify the nearest first responders during
accidents.


Challenge


Employing mainly machine learning and data analyst experts, the management team didn’t
know how to bring its solution to the enterprise level. Outside the individual machine learning
modules, the application and architecture were very unreliable, and critical features such as first
responder communication were not available. The organization needed to ramp up its solution
to be more robust in order to execute a pilot program for a major car manufacturer successfully.
In addition, the start-up didn’t know the best way to monetize its application, which could work
on iPhone and Android devices. The team needed to move from an OEM licensing agreement
to a more modern cloud subscription pricing model.


Solution


The CEO and the co-founder of this start-up contacted IO Connect Services to help address
their challenges. The IO Connect team built a satellite application, including working with
outdated legacy code, providing feedback, and fixing bugs and errors.
After a successful pilot program, the major German car manufacturer extended its contract with
the startup, asking it to help the enterprise bring this solution to different countries. This
introduced a new set of challenges as each country often had different data regulations and
requirements. However, it would be important to deploy the solution locally to reduce latency of
data transfer, especially to solicit first-responder assistance and local authorities.
Since the solution traveled with the individual and not the vehicle, IO Connect helped create a
pricing structure that matched travel personas. For example, a sales executive might do a great
deal of traveling, utilizing a personal car, rented vehicles, taxi or ride-sharing services, and
public transportation. That persona would be much different than a parent simply driving a child
to school and running local errands within a hometown.


Results


Most importantly, the start-up successfully completed the pilot project with the major car
manufacturer and opened doors to continue that relationship. It also found an effective, modern
way to price its solution as it looked toward the future.


However, the IO Connect team saw further opportunities for this start-up to expand its solution.
After designing and implementing a data lake solution, the IO Connect team suggested new
ways to monetize this valuable asset. One instance was instead of solely focusing on major
accidents, the team suggested adding new events, such as minor accidents that may occur at
slow speeds in a parking lot. The team created such a model, alerting the car manufacturer to
the event in real time. As a result, the manufacturer could immediately send promotional
marketing materials, offering repairs to scratch-and-dent incidents at competitive prices to
recapture revenue that often went to third-party, less expensive repair shops.


Moving forward, IO Connect is partnering with this start-up to explore other new lines of
revenue. For instance, the technology and data may be useful to insurance companies in
collecting driver behavior and assigning coverage or in forecasting when routine maintenance
will be required on a vehicle depending on driver habits.


As a true partner, IO Connect not only helped achieve this start-up’s original goals but has
remained an ally and valuable resource to help this organization refine its future vision for
growth and success.

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