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

                  3 min read

                  AI Supports ESG in the  Food & Beverage Industry

                  Featured Image

                  An organization’s environmental, social, and governance (ESG) score evaluates its performance on various sustainability metrics, including environmental impact, social responsibility, and corporate governance. In recent years, large-scale businesses have faced mounting pressure from consumers, investors, and regulators to improve their ESG scores. Mainstream coverage of the consequences of climate change and pollution has tipped the scales in favor of sustainable business models. Many investors now regard an organization’s ESG score as a strong indicator of its long-term viability and a critical factor in its growth (or failure).




                  Large-scale stakeholders in the Food & Beverage industry have a particular incentive to improve their ESG scores. McKinsey & Company found that “[food] products making ESG-related claims generated outsize growth,” indicating a more significant consumer preference for high-ESG Food & Beverage products than products from other industries. [1] Additionally, research suggests that improving ESG helps large-scale Food & Beverage businesses cut costs. A four-year study found “companies with high ESG scores, on average, experienced lower costs of capital compared to companies with poor ESG scores in both developed and emerging markets.” [2]

                  One of the world’s largest industries, Food & Beverage is also its most egregious polluter. Food production generates about 35 percent of global man-made greenhouse gas emissions, and beverage packaging accounts for hundreds of millions of tonnes of plastic in the oceans. [3, 4] Consumers, investors, and regulators are increasingly aware of this issue — and expect a solution.

                  In this blog, we'll explore some of the most promising applications of artificial intelligence for large-scale Food & Beverage businesses to improve their ESG scores: (i) optimizing operational efficiency, (ii) automating data collection, and (iii) reducing waste along the supply chain.  [5]




                  Predictive Optimization

                  The Food & Beverage industry relies on a complex web of logistics and operations: production, procurement, processing, packaging, distribution, and retail. Operational inefficiencies can occur anywhere along the supply chain and create unnecessary waste. Every day, equipment breakdown leaves produce rotting on the vine, suboptimal fleet routing generates excessive emissions, and machinery malfunction creates deformed products designated for the landfill.

                  Predictive analytics, or using AI to predict future phenomena, can prevent operational efficiencies. For example, large-scale Food & Beverage businesses can use predictive analytics to identify the most fuel-efficient shipping routes, minimizing emissions. Alaska Airlines saved 480,000 gallons of fuel over the course of a sixth-month predictive routing pilot program. [6]

                  “Smart” Data Processing

                  Large-scale Food & Beverage companies need to process large volumes of data to calculate their ESG metrics: a time-consuming process for people — but not for AI. “Smart” tools save time, reduce labor costs, and eliminate the risk of (human) errors in data collection and analysis. Starbucks, for example, has rolled out more than 4,000 AI-enabled espresso machines in an effort (called “Deep Brew”) to integrate AI-powered data-processing tools into its equipment. [7]

                  Automated Waste Reduction

                  Fourteen percent of food is wasted between harvest and retail, according to the United Nations. [8] AI-enabled inventory management can help large-scale F&B businesses reduce waste and improve their ESG scores. With automated inventory management systems, businesses gain insight into their inventory levels, expiration dates, and ordering patterns, allowing them to reduce overstocking and spoilage. This not only helps to cut down on waste but can also result in significant cost savings. In addition, automated inventory management can reduce the need for manual labor, allowing employees to focus on more valuable tasks.


                  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

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