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.” 
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    ⇲ 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. 
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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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        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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          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


                  How Much Data Do We Need?

                  When you think you don't have enough data to start an important machine learning project, ask Tim.

                  In this presentation, Dr. Tim Oates discusses transfer learning, open source datasets and synthetic data, few shot learning, active learning, and semi-supervised learning. By the end of the session, you should understand what all of these methods are, when they are applicable, and what kinds of results you can expect from using them.



                  More questions? Request a 1-1 with Dr. Tim Oates.

                  Related Reading

                  How Much Data Do We Need?

                  by Tim Oates, Chief Data Scientist at Synaptiq

                  I’ve spent hundreds of hours speaking with potential clients about how Synaptiq can help unlock value in their data. I really enjoy these conversations; each one is different and I always learn something new, especially about the amazingly creative...