Our AI Impact

 for the health of people

People_Stat-01

 

 Our AI Impact

 for the health of planet

Planet_Stat-03-01

 

 Our AI Impact

 for the health of business

Business_Stat-01-01

 

FOR THE HEALTH OF PEOPLE: EQUITY
Rwanda-Bridge-1-1
“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.” 
Read the Case Study ⇢ 

 

    ⇲ Implement & Scale
    DATA STRATEGY
    levi-stute-PuuP2OEYqWk-unsplash-2
    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. 
    Read the Case Study ⇢ 

     

      PREDICTIVE ANALYTICS
      carli-jeen-15YDf39RIVc-unsplash-1
      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. 
      Read the Case Study ⇢ 

       

        MACHINE VISION
        kristopher-roller-PC_lbSSxCZE-unsplash-1
        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. 
        Read the Case Study ⇢ 

         

          INTELLIGENT AUTOMATION
          man-wong-aSERflF331A-unsplash (1)-1
          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. 
          Read the Case Study ⇢ 

           

            strvnge-films-P_SSMIgqjY0-unsplash-2-1-1

            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

                  Malika Amoruso

                  Transparency or Complexity: Understanding the Powers and Pitfalls of Black Box AI

                  In today's rapidly evolving technological landscape, artificial intelligence (AI) has become an integral part of our lives, impacting everything from the products we buy to the decisions that shape our future. However, as AI continues to advance, so does the debate surrounding its transparency and accountability. Enter the world of Explainable AI (XAI), Black Box AI, and White Box AI, three distinct approaches to harnessing the power of artificial intelligence.

                  In this article, we'll delve into the key differences between these three approaches to AI models, explore the risks associated with Black Box AI, and discuss strategies for responsible and ethical AI use.

                  Whisking Words: Unlock the Power of LLMs for Your Business

                  In the past year Generative AI, in the form of Large Language Models (LLMs), has emerged as a...

                  Moving Too Fast Can Break People: Looking Back at HIMSS 2023

                  In the aftermath of the pandemic, our healthcare system rose to new challenges, delivered...

                  4 Ways We Can All Keep Our AI on Biodiversity

                  Did you know that biodiversity–the variety of life on earth–does more than just provide us with...