CURRANT.AI believes that better street level data will drive our society to a safer and smarter future. We aggregate street level information and apply urban analytics to provide:

(1) safer driving to individual drivers;

(2) smarter mobility to cities; and

(3) spatial intelligence to business organizations.

Copyright: CURRANT.AI

Video taken in Cambridge, MA, USA

 
OUR

SERVICES

01

Driving Assistant
  • Alert drivers to potential driving hazards such as incoming vehicles and pedestrians

  • Share aggregated and anonymized weather hazards and congestion information for smarter routing

02

Liability Claim
  • Apply artificial intelligence to intelligently store critical video data

  • Generate collision report with video data together with estimated collision statistics

03

Urban Informatics
  • Integrate video footage analysis and geospatial data to provide real time parking availability

  • Pioneer a universally-applicable, manufacturer-independent, non-intrusive driver/vehicle-to-vehicle communication standard

  • Other crowdsourcing urban data particularly from streets and roads

04

Business Intelligence
  • Provide businesses with information like pedestrian volume and socio-economic estimates to assess commercial attractiveness

To Individual Drivers (2C)

The App will provide smarter and safer driving assistantships (such as hazard alerts, distance alerts, real-time parking assistant ) during driving and generate liability claim reports for drivers in case of accidents.

To Business & Cities (2B)

The smart urban analytics platform will generate street-level urban information, such as pedestrian volumes, usage of parking lot. All such information would provide new insight for commercial companies and government agencies.

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ABOUT

Currant.AI is founded in Cambridge, Massachusetts in 2017 by a group of graduates from Massachusetts Institute of Technology (MIT). While the co-founders have very various training and backgrounds ranging from computer science, urban planning, transportation, and geography, they share the same vision that better street-level data will lead to a better city.

Our Team

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Waishan Qiu
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GIS Scientist

Xiaojiang LI

Li Xiaojiang is a postdoctoral fellow at MIT Senseable City Lab (SCL), and is an expert in data-driven geospatial analysis. His work has been featured in popular media outlets like the TIME, Wall Street Journal, Wired, The Guardian and Forbes.

AI & ML Scientist

Bill CAI

Bill has a S.M. in Computational Engineering from MIT and specializes in deep learning and computer vision. As a data scientist in One Concern, he builds deep learning pipelines for city-wide analysis. He previously interned in Thumbtack and Arcstone.

Urban Planner & Designer

Waishan QIU

Waishan obtains city planning master degree from MIT and is now a Ph.D. student in Regional Science at Cornell University. He is an experienced front-end designer. He was a researcher at the Media Lab, Center for Advanced Urbanism, SCL working on geospatial analysis and urban computing.

Transportation Planner

Jintai LI

Jintai is a Ph.D. student in Transportation at MIT. His current research work with the Transit Lab and the Urban Mobility Lab focuses on 1) demand prediction in response to the introduction of ride-hailing services provided by autonomous vehicles, and 2) user preference and segmentation.

 
CASE

STUDIES