The opportunity for partners to participate in the AI market is omnipresent and significant. In Canada, we are leading the way, locally and globally, in amplifying human ingenuity with AI. Irrespective of industry, whether healthcare, finance, manufacturing, retail, government, or education, organizations of all sizes are exploring how to leverage AI-based capabilities to modernize their operations, improve their customer experience or more broadly, enable themselves to become a digital business.

AI will not only create endless business opportunities for partners, but also will provide competitive advantages and tremendous benefits to those who are leading.

As I indicated in my post “The incredible AI opportunity for the Canadian Ecosystem”, we have some incredible work being done by our partners to lead with AI, that we wanted to share. As the third in a series of “unplugged” Q&A, I’d like introduce Quartic ai, and have some thoughts shared from Rajiv Anand, CEO and Co-founder.

 

About Quartic AI, and their core business

Rajiv Anand: Process manufacturers recognize the impact that AI and Industry 4.0 can have on increased productivity, competitiveness and agility. Manufacturers in mature markets like North America face the challenge of legacy infrastructure and lack of digital talent. Many, however possess valuable data and operating experience. Quartic.ai has developed a proven Industrial AI and IoT solution that allows industries to turn their legacy assets into smart, Industry 4.0 assets. With Quartic.ai, manufacturers can liberate the stranded intelligence in their plants and enable their subject matter experts and engineers to turn their experience and knowledge into AI applications without extensive data science experience.

Thinking about your business, what type of customer/buyer do you target? Is there a specific functional area that you focus on?

Rajiv Anand: We started out by focusing on life-sciences and Food & Beverage industries which still remain our key focus industries. However, we are finding a lot of high ROI use cases and a desire to apply AI and IoT in the primary manufacturing, metals and mineral processing and also upstream energy industries where we are able to make a business impact.

For manufacturing, we generally find that business line leaders such as plant manager, operations managers/VP of operations/manufacturing have a much better understanding of the practical day-to-day business pains. Given our domain expertise on the manufacturing floor, we are able to collaborate very well with these experts and find that they are able to qualify good opportunities very well. Once a PoC/Pilot has been planned, the customer team typically will comprise of an operations engineer/maintenance engineer and an OT (automation) person. However, once you get beyond PoC into real-time deployments, IT and Information systems leaders need to be involved. Where ever possible, we therefore try to engage IT early wherever possible. We are also finding a growing shift where IT/IS teams and CIO are becoming increasingly aware of and wanting to take the lead in IIoT and AI projects.

 

How have the advances in Artificial Intelligence helped your business grow?

Rajiv Anand: While we are technically a software company, our key value proposition is our subject matter expertise in manufacturing processes and how best to automate them. Previously, our ability to grow our business was limited by the number of subject matter experts we could add and to “sell subject matter expertise by the hour”. With AI, we are able to much better monetize our expertise and intellectual property. We are also able to capture “tribal knowledge” we had gathered from years of experience in the form of algorithms and models. This allows us to reach a lot more customers and to move from selling hours to selling outcomes.

Generally, when you engage with a new customer, what is the key business challenge(s) they are looking for your help with?

Rajiv Anand: Use of IoT and AI for predictive maintenance to reduce unplanned downtime and increase equipment availability continues to be the first business challenge and opportunity that is at the top of the list where customers are looking for us to help them with. However, we are finding increasingly so that reduction in process variability and increasing throughput/yield tend to have a much higher business ROI. Processes that make multiple products (SKU) using different combination of feedstock; and processes with high variability in the feedstock are not able to manage throughput and quality variability in the final product with traditional process control techniques and are benefitting greatly from AI applications.

 

Is there a specific customer that you would highlight where you’ve had a direct impact on their business outcomes? 

Rajiv Anand: Increasing equipment reliability is often seen from the perspective of increasing uptime. However, for this large chemical processing customer, repeated failure of a shaft seal of an agitator had led to safety issues due to the leak of dangerous materials from a sealed, high pressure vessel. Traditional condition monitoring technologies – like vibration and temperature measurements were not able to detect the problem and there is no commercially available technology to detect the leakage from the seal. This was an ideal application of AI; the problem could not have been solved without using machine learning models. Using historical data from past seal failures, we were able to develop machine learning models that start alerting operations staff when a seal leak is developing and is likely to occur. They are now able to take corrective action, and if necessary shut down the process safely to avoid costly and catastrophic safety incidents which not only threatended human safety in the past, but also had resulted in labor compliance issues due to near-miss incidents.

i.e. Transformative benefits
By empowering manufacturing teams to integrate their data and deploy their own machine learning applications, Deming gives manufacturers insights and a platform to transform processes that unlock significant new benefits. For instance, Quartic.ai monitors the performance of their industrial assets in real-time to avoid production delays, mitigate waste, and predict throughput accurately.

“Recovering stranded intelligence allows manufacturers to broaden their focus from automation alone to operational excellence and value stream optimization. This application of artificial intelligence for predictive analytics defines modern IoT.” – Rajiv Anand, CEO and Co-founder

 

Lastly, what are your thoughts on the future of AI and its impact on society?

Rajiv Anand: Manufacturing users are rapidly realizing that AI is the best path for them to be more productive and competitive and to create value for their shareholders and customers. Users are seeing the benefits of AI as an enabler for them to delegate repetitive tasks to AI and to focus on the more productive and creative tasks. As AI becomes more automated and interpretable, users confidence in it will continue to increase and we will realize the vision of Industry 4.0 – where man and machine collaborate to create value for society.

 

“IoT is far from new in manufacturing. It’s just a new name for connecting sensors to software. Before modern IoT, those sensors only worked on isolated, proprietary computers and software controlling each production line. The focus was only on automation. Today, with cloud computing and artificial intelligence, we can at last recover stranded intelligence otherwise left on the factory floor.” – Rajiv Anand, CEO and Co-founder