This AI Startup’s Data Platform is Helping Cities Become Truly Smart!


Smart cities, those integrated with IoT and technological solutions to enhance their urban living environment, are on the core agenda for municipalities all over the world. The smart cities market was valued at $50 billion last year and is expected to reach a $1.56 trillion market value by 2025. Hundreds of cities have strategic initiatives put forth to enhance their urban environment. Chicago’s Array of Things project is wiring the city with environmental and congestion sensors; The Hague has auto-adjusting street lamps that senses pedestrians; Barcelona provides drivers with a real-time map of vacant parking spaces; and Seoul has solar powered trash bins that use machine learning to optimize the waste collection routes.

The collected civic data is a strategic asset that moves the industry forward and provides cities with the ability to make the transformational leap to become truly smart. A large majority of tier 1 cities in the US today have started to recognize the potential of their data and built open data programs to stimulate innovation and urban development. But the concept of open data is struggling due to the unstructured nature of municipal data. Access to high quality data is known to be a core problem of every smart city developer (startup, enterprise, researcher, etc.). In fact, scaling from one city to another requires enduring and tedious process of utilizing datasets for every municipality from scratch.

Israeli startup, Urbanico, solves this problem with their smart city data marketplace. Using a standardization layer powered by natural language processing (NLP) and machine learning, Urbanico connects municipalities with external smart city developers to build smart city solutions. The platform enables developers to use civic data in order to rapidly scale their solution to new cities, build a data-driven decision-making processes and expedite their R&D projects.

Urbanico’s co-founders (left to right): Cfir Rahimi and Yuval Shafrir. Photo: Urbanico


Urbanico was founded by Yuval Shafrir (CEO) and Cfir Rahimi (CTO), alumni of elite intelligence units in the IDF (unit 8200 and a highly classified unit), with experience working and building core AI startups. Cfir previously worked as a data scientist at various deep-tech startups, with expertise in machine learning and natural language processing (NLP), while Yuval is a serial tech entrepreneur, who previously led a successful tech startup in the retail industry.

“We don’t have to go as far as a global scale for data standardization in order to create value. Even within a single municipality, related datasets are often structured entirely different” explained Yuval. “Despite their similarity, there could be no resemblance between data collected on restaurants and data collected on other points of interest like bars or beauty salons.”

Urbanico’s core technology is based on the ability to automatically classify the fundamental building blocks of each dataset, identify their most valuable representation and examine whether those datasets can be merged. Using contextual word embedding, statistical distance and other NLP methodologies, Urbanico’s platform standardizes the data, making it accessible, valuable and reliable.  

Urbanico’s standardization layer at work – Core component of the smart city data life-cycle. Graphic: Urbanico


“Using various techniques, Urbanico automatically creates features from both data and metadata of each dataset, in order to calculate the similarities between datasets and the potential they hold. Urbanico’s advanced technology is able to understand what are the most valuable and reachable granularity levels of the different fields. In some cases, we go as far as enriching those datasets to extract that potential” Cfir says. “For example, while analyzing data from different sources, we found that even though a dataset from one city can be used to intuitively determine if a certain location represents a school or kindergarten, in other municipalities, educational institute records can be labeled in a very generic manner. Using numerous machine learning methods allows us to extract indirect indicators, such as the location’s area size, to classify records according to those hidden labels.”

Smart city developers are utilizing Urbanico’s platform to develop cutting edge solutions, improving the urban environment. Right-Hear, a navigation and orientation platform for blind and visually impaired individuals, uses Urbanico’s platform to enhance accessibility across the city. Urbanico’s civic data allows Right-Hear to improve their services and rapidly scale.

To attract smart city technology developers, cities are using wide set of tools, such as: hackathons, accelerators and public grants. “Their spendings demonstrate an overlooking of their most valuable asset: their data,” explained Yuval. “Providing developers with easy access to high quality data heavily incentivizes those developers to launch their smart products and services in the specific city. Bringing this kind of innovation to the residents is what smart cities are all about”.

Urbanico is a two sided marketplace: It provides a pay-as-you-go model to developers seeking civic data, priced by the number of API calls. On the other side, municipalities can join Urbanico’s marketplace through a subscription fee, priced according to the number of data points uploaded to the platform. In addition, municipalities will receive an analytics dashboard, helping them with utilizing their data to support the city’s strategy. 

The startup was recently accepted to Expert Dojo, a leading US accelerator in Santa Monica, California, and are building their initial customer base in the US. They’re currently conducting a pilot with the municipality of Santa Monica and are raising their Pre-Seed funding round.

”We’re finding more municipal representatives enthusiastic to start using their data in a way that creates value” said Yuval. “There’s growing awareness in the municipal market as municipalities are beginning to realize the potential impact that their data can generate.”


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