Our AI Impact

 for the health of people

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 Our AI Impact

 for the health of planet

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 Our AI Impact

 for the health of business

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FOR THE HEALTH OF PEOPLE: EQUITY
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“The work [with Synaptiq] is unprecedented in its scale and potential impact,” Mortenson Center’s Managing Director Laura MacDonald MacDonald said. “It ties together our center’s strengths in impact evaluation and sensor deployment to generate evidence that informs development tools, policy, and practice.” 
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    ⇲ Implement & Scale
    DATA STRATEGY
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    A startup in digital health trained a risk model to open up a robust, precise, and scalable processing pipeline so providers could move faster, and patients could move with confidence after spinal surgery. 
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      PREDICTIVE ANALYTICS
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      Thwart errors, relieve in-take form exhaustion, and build a more accurate data picture for patients in chronic pain? Those who prefer the natural albeit comprehensive path to health and wellness said: sign me up. 
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        MACHINE VISION
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        Using a dynamic machine vision solution for detecting plaques in the carotid artery and providing care teams with rapid answers, saves lives with early disease detection and monitoring. 
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          INTELLIGENT AUTOMATION
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          This global law firm needed to be fast, adaptive, and provide unrivaled client service under pressure, intelligent automation did just that plus it made time for what matters most: meaningful human interactions. 
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            Mushrooms, Goats, and Machine Learning: What do they all have in common? You may never know unless you get started exploring the fundamentals of Machine Learning with Dr. Tim Oates, Synaptiq's Chief Data Scientist. You can read and visualize his new book in Python, tinker with inputs, and practice machine learning techniques for free. 

            Start Chapter 1 Now ⇢ 

             

              How Should My Company Prioritize AIQ™ Capabilities?

               

                 

                 

                 

                Start With Your AIQ Score

                  INDUSTRY AI SERVICE
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                  HIGHER EDUCATION AND NONPROFIT CUSTOM AI SOLUTIONS, ACCELERATION TEAMS MACHINE VISION
                   

                   

                  How a Machine Vision Model Counts Bridge Crossings in Rural Rwanda

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                  Learn how a constructed machine vision model preserves essential modes of transportation for people in rural Rwanda.

                  Problem:

                  According to the World Bank, more than a billion people worldwide currently lack access to an all-season road. These individuals suffer limited access to safe water, sanitation, energy, food, healthcare, shelter, schools, and other infrastructure and services. It’s a problem the Mortenson Center in Global Engineering is working to better quantify and solve with Bridges to Prosperity and other collaborators.

                  Bridges to Prosperity builds bridges to connect rural communities facing isolation. To date, the nonprofit has built more than 350 trail bridges in 21 countries. Their standard monitoring methods typically rely on manual, in-person data collection that’s time-consuming, produces temporally limited data, and is labor-intensive. A continuous and automated method was needed.

                  What can you learn from this partnership in social good?

                  The successful pilot program provides an unprecedented opportunity to study the correlation between bridge use and several key economic, health, agricultural, and educational outcomes in rural communities. Automated counting methods and analysis tools can track mobility trends elsewhere in the world, too. “This work is unprecedented in its scale and potential impact,” Mortenson Center’s Managing Director Laura MacDonald. MacDonald said. “It ties together our center’s strengths in impact evaluation and sensor deployment to generate evidence that informs development tools, policy, and practice.”
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                  Solution:

                  Synaptiq partnered with the Mortenson Center in Global Engineering at the University of Colorado at Boulder. The Mortenson Center’s teams constructed several bridges across high-traffic flood zones, hoping to preserve communities’ access to healthcare and other services. They needed an accurate count of the pedestrians crossing each bridge to determine their use and impact on trade, economic prosperity, and more. The team developed, implemented, and validated a novel method using low-cost, readily available motion-activated digital cameras in combination with open-source computer vision algorithms for measuring the use of bridges.
                   
                  In summary, Synaptiq:
                  • Built a machine vision model to count pedestrian bridge-crossings
                  • Used motion-activated digital cameras in combination with open-source computer vision algorithms

                  Outcome:

                  Our work allowed the Mortenson Center to determine that the bridges were indeed effective, advancing an effort to protect a significant number of Rwandan communities’ access to essential services. 33,800 pedestrian crossings were counted in one observation period. Now thousands of Rwandans can sell goods at their local market or attend school without fear of their surroundings.

                  HUMANKIND OF IMPACT

                  33,000 more Rwandans can now access healthcare, education, and markets year-round, growing communities.

                   
                   

                  33,000 more Rwandan’s could be accessing their local markets again.

                  HUMANKIND OF IMPACT

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                  AI IS HOW WE DO IT,

                  humanity

                  is why we do it