Iguazio Receives Honorable Mention in Gartner MQ for Data Science and ML Platforms Second Year in a Row
Smart mobility is all about creating a cleaner, safer, and more efficient way of getting around. As urban transportation becomes more of a challenge, and air travel becomes more and more frequent, it is imperative to leverage AI to create new ways to revolutionize transportation and cater to growing customer demands.
The Iguazio Data Science Platform for Smart Mobility enables you to develop, deploy and manage AI applications, transforming AI projects into real-world business outcomes. With Iguazio, you can build and run AI models in real time, deploy them anywhere (multi-cloud, VPC or on-prem), and bring to life your most ambitious data-driven strategies for smarter ways to travel.
Optimize on-demand transportation and enhance driver and passenger experience.
Maximize efficiency to ensure supplies arrive on time and unharmed with location-based heat-maps and real-time data regarding fuel consumption, weather, road conditions and more.
Manage and optimize logistics at scale, including meals, rosters, machines and more
Detect patterns of suspicious behavior and prevent fraudulent transactions before they occur.
"The Iguazio Data Science Platform has made our product viable by slashing costs and time getting AI to production. Without this partnership, we would never have been able to harness and process data from so many sources, to make accurate predictions in an efficient and reproducible way."
CEO and Founder, Airvi
"Iguazio provides us with an integrated platform which makes the job of better detecting fraud and ride usage much easier and efficient in the doing.”
Lead Data Scientist and Growth Hacker
PickMe is the leading on-demand transportation service in Sri Lanka, with over 2.5 billion downloads and $1bn in revenue. In order to meet rising demand, PickMe uses the Iguazio Data Science Platform to optimize ride-hailing with real-time heatmaps and prevents fraud by detecting suspicious behavioral patterns in real-time.