Backing partners Microsoft, Siemens, Deutsche Telekom (parent of T-Mobile), BMW, Village Global VC
Stellar Team: Honored Stanford PhD, UIUC Professor, IEEE Award "Top 10 to watch in AI"
Patented AI technology, Proprietary data, Gartner Cool Vendor 2020 ...
Funnel increased 50x since previous WeFunder raise
Mobility and Smart City markets seeing exponential growth potential, inflection point
Why investors us
$792,200 since our founding
Despite all the location data made available from cell phones and other smart devices, no one has been able to figure out how to use that data to better understand how humans move through space. Parknav has assembled an award winning team of data scientists to turn location information into actionable data. They’ve started with parking. Using machine learning algorithms they are able to detect up to 95% accuracy if parking is available on any street in over 70 cities in the US and Germany. That’s incredible.
To solve a technical challenge like this you need an exceptional team, and Parknav has it. Dr. Eyal Amir has a PhD from Stanford, is a CAREER award recipient from the National Science Foundation and has been named one of the “Top Ten to Watch” in artificial intelligence. His partner Sergei has won numerous hackathons, built security systems for UBS and the Chicago Mercantile Exchange and has over 10 years in development experience.
Instead of taking the riskier path of focusing on a consumer app that won’t be able to monetize for years, Parknav is already making money. Their consumer app is just a prototype, they are already selling the parking data itself to several auto manufacturers across the US and Europe (at $9 per car per year) for use with their in-car GPS navigation. One of the largest real estate listing sites is also buying Parknav data to show potential home buyers how much on street parking is available in the neighborhoods they are considering.
They’ve demonstrated an ability to solve 3 challenging problems. Getting access to extremely sensitive cell phone data from Telecom companies, assembling a team that can make that data actionable, and figuring out how to sell it to enterprise companies.
There is so much more they can do with this data beyond parking. In addition to real estate, Parknav will have the best data set available for retailers to decide where to site their next location, for cities to better plan the built environment, and numerous other applications they are keeping warm on the back burner. Big data will be the source of how everything we do in life is made more efficient, and Parknav has the right start to be at the center of that revolution.
Back in 2015, it was everyone's idea that sensors alone would bring information about parking and living. We felt that sensors would take ages to cover our world and lots of money before that is reality. We knew that AI technology was ready to deliver this at 1000x lower cost. We already proved that we could do it at small scale with our FasPark (later Parknav) app in 2012. Then we won BMW and Inrix as customers in 2016 and launched this to large scale in BMW cars in 2017.
Wow! It works!
Hundred of thousands of drivers could use the tech. Also, we realized that the same tech can be used to create realtime information about anything in the street: lamps, trash bins, benches, seats in restaurants, cleanliness, disrepair, safety, and inventory.
With the help of new partners, especially Deutsche Telekom (T-Mobile), Siemens, and others, we were able to start reaching the potential of our company. While our technology was already running for 100+ cities such as NYC, Boston, San Francisco, LA, Berlin, Munich, Paris, and others, and data was available for more than 1000+, our potential customers were all large and slow. How do we scale faster so we are not left behind?
Then We Proved our ROI
Drivers want to find parking and wish to pay for information, but how could we prove it? With our customers, we were able to test and show that drivers used mobility apps more (50% increase in retention; 30% increase in usage, more) with Parknav data. Cities, insurers, and marketers are able to save millions by using our data.
The market potential is opening up:
Now the RFPs are pouring in
In March 2020 CoVid-19 started changing our lives. In the US people started moving out of big cities into small ones. In the EU people got locked down. Cities everywhere started taking the opportunity to upgrade, and companies started investing in city information. We receive the demand from all those.
In total, we see inbound substantially increase from companies investing in post-CoVid mobility and cities investing in smart-city planning and operations information.
We are a US-based company called Ai Incube, with our leading product Parknav creating an entry for us into large-revenue opportunities. Our German subsidiary Ai Incube GmbH enables us to leverage strengths from both US and EU and deliver value to both and beyond.
We are a team of founder-types. Hello! Thanks for choosing us!
The team of Parknav
What does your company do?
We use artificial intelligence to help drivers find available on-street parking in real-time.
Where will your company be in 5 years?
We want to serve 10MM+ people in 10,000+ cities and surpass revenue of $100MM in 5 years.
Why did you choose this idea?
Parking is the most painful part of every driving experience. By providing real-time information about parking availability, we will improve the lives of millions around the world.
Who is on your team?
Our team is led by award winning data scientist Professor Eyal Amir. Eyal received his tenured Professorship at the University of Illinois at Urbana-Champaign in 2009 and is the recipient of a number of awards for his research including being chosen by the IEEE as one of the "10 to watch in AI", receiving the CAREER Award from the National Science Foundation, and being awarded the Arthur L. Samuel award for best Computer Science Ph.D. thesis (2001-2002) at Stanford University. Our team also consists of many of his Ph.D students.
Who are your current customers and partners?
Parknav's technology launched in 2017 BMW vehicles in EU and US (via partnership with INRIX), and our customers now include Deutsche Telekom (parent of T-Mobile), Siemens, Q8 Petroleum and others along with partners including Microsoft, O2/Telefonica and others.
How are you different from other parking solutions?
Instead of requiring dedicated parking sensors, we only use data to determine real-time on-street parking availability.
Where does the data come from that "powers" your solution?
We use artificial intelligence to analyze data generated by cars manufacturers, telecommunication companies, insurance companies, car-sharing companies, mapping companies and many other sources.
How do you acquire this data?
We are provided real-time data by our customers/partners, we license real-time data from providers and we curate our own proprietary data.
What is the exact product you provide to customers?
We provide real-time parking availability data to our business enterprise and government customers. This data is then integrated into a a car's navigation system, mobile application, web application, or other solution where it becomes viewable to the end user.
How do you compare with other parking information companies?
Some other solutions specialize in static (non-changing) off-street parking information, while we are strongest in dynamic (real-time) on-street parking availability information.
How do you compare with parking-payment and off-street reservation companies?
We provide real-time on-street parking availability information, while off-street parking reservation companies focus on reserving off-street parking spaces and parking payment providers focus on paying for parking once parked; both are natural partners for us.
How do you compare with parking sensor companies?
Sensors are expensive to buy, install, connect, and service. Also, sensors by themselves still provide low quality availability information for large areas and entire streets. Parknav is scalable and typically costs 100x lower than same area coverage with sensors.
Can you also integrate sensors?
Yes, when those are available; however, we do not require them.
Who do you sell it to?
Mobility companies (car manufacturers, parking-payment companies, oil companies, mapping companies, mobile apps) typically want to embed our parking data so that they can provide it to their customers to help them find parking. For example, mobile parking payment apps can provide our real-time parking availability information to their customers so they can both find parking faster and then press "pay", all in the same app. We refer to this as the complete "in the car to out of the car" experience.
Who competes with you? What do you understand that they don't?
Traditionally, cities and enterprises rely on the installation of dedicated parking sensors to determine real-time parking availability. This is not scalable nor cost effective. Comparably, our solution is a precise artificial intelligence (AI) data-driven product that can be even more accurate at 100x lower cost (so 100x more scalable).
What is your market?
Mobility Providers and Smart Cities.
How will you make money?
Selling SaaS (software as a service) solutions and API access to enterprises and governments. This means that we sell licenses to our parking information and charge for it per request or per user per month. We make money with every request for our parking data, and also have monthly subscriptions to users.
What are the biggest risks? If you fail, what would be the reason? What has to go right for you to succeed?
Speed to market is key because the Smart Cities market is growing exponentially right now. There is a risk that we shall not be fast enough and others shall conquer the market before we expand. There is also a risk that the Mobility and Smart Cities sectors would change in such a way that parking would not be needed as much.
This startup seems old, why?
It has taken time for us to develop the technology while we were doing it part time in the early years. In 2017 (3 years ago), we launched in a large scale customer's application (the in-car navigation system of BMW), and since then, the mobility and smart city markets have opened up. We are now ready to scale.
How would you spend the proceeds of the raise?
We plan to invest in go-to-market, including some technology, aiming to provide diverse customers and surpass revenue milestones that would enable us to grow faster in 2021.
What is the vision?
We envision a world where mobility solutions and applications quickly find parking for us, especially when cars become autonomous. We understand that autonomous vehicles can both identify parking in their immediate surroundings and physically park themselves. We believe Parknav is the missing piece of the autonomous parking experience that informs autonomous vehicles where available parking is 3-4 streets away.
Will your current investors invest?
Yes, one of them is leading this round.
How does Covid-19 affect your business and opportunity?
Parknav and mobility providers did suffer some setbacks in 2020, but we believe the industry shall come back stronger in 2021. Our data science team wrote a blog entry about it: https://medium.com/parknav/how-covid-19-affects-parking-congestion-832efb066232
Where are you guys based?
We are based in Chicago, with an office in San Francisco. We also have a subsidiary based in Munich that is in charge of execution for our European business.
What is Ai Incube and how does it relate to Parknav?
Ai Incube and Parknav are the same. Parknav is our main brand name, and Ai Incube is the corporate name (Ai Incube Inc).
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