Investor Connect: Eyal Amir of Parknav

Investor Connect: Eyal Amir of Parknav

March 30, 2021 by investor

In this episode, Hall welcomes Eyal Amir, Founder and CEO of Parknav.

Headquartered in San Francisco, California, and founded in 2015, Parknav revolutionizes real-time on-street parking with a highly accurate and scalable solution. Using big data and AI, Parknav brings the most advanced precise parking availability information for mobility, smart city, transportation, and automotive. They provide on-street parking, free, metered, permit, curbside restrictions, traffic control data as well as data acquisition from city sensors. Parknav is available for over 1000+ cities across North America & Europe and has over 5.5 billion recorded parking events!

Eyal is an AI leader with 20 years of artificial intelligence excellence, winning the best-Ph.D. award at Stanford University computer science and the Top-10 Young AI award from IEEE. He has helped successful startups 6Sense, Reflektion, and Fraud Science, and was tenured Associate Professor of Computer Science (now Adjunct Professor) at UIUC.

Among others, he was a gold medalist (Israel) in Olympic Rifle Shooting at age 20 and is a black-belt in karate (Shotokan JKA).

Eyal shares with Hall what led him to start working in this space. He discusses some of the challenges he has faced and advises investors and entrepreneurs.

You can visit Parknav at www.parknav.com, via LinkedIn at www.linkedin.com/company/parknav, and via Twitter at www.twitter.com/parknav

Eyal can be contacted at eyal@aiincube.com and eyal@parknav.com, and via LinkedIn at www.linkedin.com/in/eyalamir1.

For a full transcript, click here.

Music courtesy of Bensound.



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Disclaimer:
Hall T Martin is the director of Investor Connect, which is a 501(c)(3) nonprofit dedicated to the education of investors for early-stage funding. All opinions expressed by Hall and podcast guests are solely their own opinions and do not reflect the opinion of Investor Connect. This podcast is for informational purposes only and should not be relied upon for the basis of investment decisions.