Improve the user experience of shared spaces by anticipating discomfort factors.

Who benefits from our products?

Cities and Metropolises

With urbanization, they want to reinvent themselves to improve the quality of life in their territory. It is becoming increasingly complicated to objectively characterize the perception of a city’s inhabitants or tourists to anticipate discomfort. Perception varies according to multiple factors (weather, events, traffic…).

Train stations and Airports

They are looking to reinvent themselves to improve the experience at stations and airports. It is becoming more and more complicated to objectively qualify the perception of users to anticipate discomfort. The perception varies according to multiple external factors that are complicated to understand in order to make the right redevelopment decision.

Cleaning & Street Sweeping Operators

They need to ensure an excellent experience for users, respect the service levels imposed by their contract while managing their teams and budgets. The perception of cleanliness is difficult to quantify and depends on many external factors. It is not easy to integrate them and make the right decision quickly at the right time.

Real Estate Developers & Asset Managers

Developers wish to create spaces that will be appreciated by their users. Managers wish to optimize existing spaces. Everyone wants to provide the best experience for their users. The notion of well-being is difficult to objectify. Uses are changing and depend on external factors. It is difficult to anticipate the perception of an design before implementing it.

Our products

Our 2 products are based on the same technology. It combines both contextual data to represent the city or space in which users are located and data on the perception of people obtained through a survey (cleanliness, safety, stress, comfort, beauty, etc.). Since 2014, we have developed a proprietary algorithm that allows us to anticipate the perception of a person according to his or her surroundings.

The machine learning technology is used to get objective information on a user’s perception of a street, city or an indoor space by taking into account all the existing context variables during the survey campaign.

Explanatory models make it possible to explain objectively the contextual variables that have a positive or negative impact on a user’s perception.

ComfortPredict User

  • Predicts user perception based on location and time of day in a street, city or shared space
  • Objectively quantifies external factors that have a positive or negative impact on the perception of a user.
  • Available as an API or dashboard

ComfortPredict Optimization

  • Identifies areas and times when a user’s perception is likely to be degraded
  • Analyses the impact of actions undertaken to improve user perception

They trust us

Their testimonies

“Qucit’s approach is innovative, combining planning, flow, environmental and qualitative data obtained through a simple, geolocated questionnaire. The proposed comfort indices allow a new understanding of the use and apprehension of the public space, and thanks to the analysis of the explanatory factors of the indices. ComfortPredict becomes a decision-making tool for urban planning.”

Sabine Romon
Responsible for the Smart and Sustainable City Mission
City of Paris

“Selected from nearly 200 candidates during the first DataCity Paris edition, Qucit invested a lot in the program by involving team members and their expertise to meet the challenge suggested by the City of Paris and Cisco through the use of a large amount of data.”

Mael Inizan
Innovation Program Manager

Interested in ComfortPredict?