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We combine traditional and innovative tools and methods that enable transparent and economical processes

for more frequently updated plans



(CI) Collective Intelligence


Collective Intelligence (CI) convenes and processes large amounts of information and values held by individuals and groups that can vary greatly in their values, resources, and status. It is particularly appropriate for aggregating qualitative information in the face of uncertainty.  

  • CI seeks new ways for these groups and individuals to think and act together, mobilizing collective knowledge more fully and effectively.

  • The collective involvement of groups and individuals can provide essential and current information about local conditions.  

Moreover, these processes can also foster collective action—the ability of diverse groups and individuals to work towards common solutions. CI offers a powerful means to make Participatory Planning more inclusive and  equitable.

Combining CI with AI can also facilitate a wider scale of social participation in decision-making processes, first by being able to process much larger amounts of data, and then by searching for alternatives that advance the broadest set of stakeholder aspirations within the available and expected resources, as well as examining systemic impacts of decisions that could otherwise remain unanticipated.


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Inspired by Mona Serageldin, Frank Vigier, Alfredo Stein and Nesta's Collective  Intelligence, England



Machine Learning


(CCR) Climate Change Resilience is An artificial intelligence (AI) tool, specifically a Machine Learning (ML) tool, that, through an integrated analysis of a variety of data including satellite or aerial images, is designed to provide a rapid and low-cost identification of: 

  • Change in urbanization trends including informal settlement patterns of growth and 

  • Exposure to climate-related risks, shocks and stresses --flooding and heat--for formal and informal settlements. 

  • Deforestation and identification of forestation efforts towards mitigation of heat-trapping greenhouse gases.

The tool can identify change patterns and exposure to these climate-related hazards more economically, quickly, frequently, and transparently than current approaches and can facilitate visual accessibility to otherwise inaccessible areas.

It can be available directly to public officials and  to the public through a user-friendly  desktop and mobile interface.

The tool adds value to planning practices, municipalities and communities, formal and informal real estate developers and insurance agencies, leading to more inclusive and equitable cities, and to governance processes that address the joint impacts of rapid formal and informal urban expansion and climate change.


Inspired by Mona Seragedlin and Frank Vigier, founders Institute for International Urban Development, I2UD


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Scenario Planning


We speak directly to the theme of Equity in Scenario Planning (SP) by seeking practical and effective ways to harness the transformative and complementary potential of Collective Intelligence (CI) and Artificial Intelligence (AI) towards more equitable SP processes and outcomes.


  • Collective Intelligence (CI) convenes and processes qualitative information and values held by individuals and groups. 

  • AI makes it possible to analyze data, images, physical patterns and relationships not readily perceived by human intelligence, at lower cost and higher speed.

Integrating this kind of data analysis with information and values from a diverse local or regional community can help correct the imbalances that limit equity in SP—imbalances in who gathers, analyzes, and communicates information, and in who makes decisions and allocates resources to implement decisions.

CI can complement AI in crucial ways to advance equity in SP in landscapes that include diverse racial and income groups, including highly vulnerable ones. Incorporating the two into SP, however, demands careful thought.


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Inspired by Mona Serageldin and Lincoln Institute of Land Policy, Cambridge, MA

We combine traditional and innovative tools and methods that enable transparent and economical processes

for more frequently updated plans.

design with nature

work all stakeholders 

focus on lower income and informal settlements  

adaptation and mitigation strategies 

leverage nodes & corridors

 work with and scale to other cites of the region

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