Our AI Impact

 for the health of people



 Our AI Impact

 for the health of planet



 Our AI Impact

 for the health of business



“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
    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 ⇢ 


      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 ⇢ 


        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 ⇢ 


          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 ⇢ 



            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

                  5 min read

                  The Future Is Extreme Weather & AI To Fight It

                  Featured Image

                  According to Deloitte, 48 percent of executives have experienced negative consequences from weather-related supply chain disruptions in the past five years. Moreover, 53 percent report that these disruptions have become more costly over the same period, with top costs including margin erosion, demand shifts, and product flow.

                  Make no mistake: things are not going to get better. In fact, they will get worse.

                  In 2021, the Intergovernmental Panel on Climate Change (IPCC) reported that climate change was strengthening “extreme weather” events such as heatwaves and hurricanes. In 2022, the IPCC warned that some consequences of climate change had become “irreversible.” Ultimately, the question is not “if” businesses will have to adapt to extreme weather but “how” they will do so, facing a future of destructive and escalating weather disruptions.

                  The Problem is Predictability

                  The challenge of dealing with extreme weather stems primarily from two factors: its varied nature and the difficulty in predicting it. Extreme weather manifests in diverse forms, such as flash floods, droughts, blizzards, heatwaves, hurricanes, and wildfires, each bringing its own set of unique challenges. Additionally, the unpredictability of extreme weather compounds the difficulty. The National Oceanic and Atmospheric Administration has noted that “a 10-day [weather] forecast is only right about half the time.” This is due to the many meteorological variables at play, which are constantly changing and interact in complex ways, making weather forecasts costly and imprecise. This unpredictability and variety make preparing for and combating extreme weather events a formidable task.

                  Artificial Intelligence is the Solution

                  Artificial Intelligence (AI) is emerging as a potent tool in addressing the challenges posed by extreme weather. Innovators in the industry, such as tomorrow.io, along with established giants like Google, are employing AI to enhance the accuracy and extend the forecasting range of weather predictions.

                  AI merges the efficiency of computers with a form of intelligence inspired by human cognition, particularly in predicting extreme weather events. A notable example of this is a machine learning algorithm developed by Stanford researchers, which is specifically designed to detect early signs of heavy rainfall. This algorithm, trained to recognize atmospheric patterns, has demonstrated the ability to predict heavy rain with over 90 percent accuracy.

                  Looking ahead, AI is poised to play a critical role in helping businesses anticipate weather-related disruptions in their supply chains, potentially days, weeks, or even months in advance. The key advantage of AI in this context is its capacity to overcome the traditional challenges of weather forecasting – the variability and unpredictability of extreme weather events. By offering more reliable predictions, AI provides a valuable opportunity for businesses and communities to prepare for extreme weather before it strikes, mitigating potential risks and impacts.

                  Our Work on Extreme Weather

                  Synaptiq is no stranger to extreme weather. In 2021, we assisted a client in using machine vision to develop a satellite-based system for early wildfire detection. This system utilized stratospheric balloons equipped with heat-sensing technology, capable of detecting conditions conducive to wildfires. Upon identifying these conditions, the system promptly alerts fire departments, enabling quicker response times and hopefully reducing fire damage.

                  The relevance of such systems is underscored by the fact that in the U.S. alone, approximately 4.5 million homes are at high or extreme risk of wildfire, a number that continues to grow due to extreme weather events like the Pacific Northwest's "heat dome." Although first responders are adept at managing nascent wildfires, the unpredictability of these fires' movements, influenced by weather and geography, poses significant challenges. Synaptiq's work in leveraging AI for early detection and predictive analysis is a testament to how AI can make extreme weather more predictable and manageable, thereby benefitting communities and ecosystems alike.


                  humankind of ai


                  About Synaptiq

                  Synaptiq is an AI and data science consultancy based in Portland, Oregon. We collaborate with our clients to develop human-centered products and solutions. We uphold a strong commitment to ethics and innovation. 

                  Contact us if you have a problem to solve, a process to refine, or a question to ask.

                  You can learn more about our story through our past projects, blog, or podcast

                  Additional Reading:

                  Ask Tim: Buy or Build Generative AI

                   Photo credit: Debbie Hudson via Unsplash

                  Home ownership comes with lots of decisions about whether to do it...

                  Too Much Data, Too Little Time: A Business Case for Dimensionality Reduction

                  Introduction to Dimensionality Reduction

                  High-Dimensional Data

                  Imagine a spreadsheet with one hundred columns and...

                  BETTER Customer Review Sentiment Analysis: A Business Case for N-grams

                  Sentiment analysis is a useful tool for organizations aiming to understand customer preferences, gauge public...