First, they were helping Audi develop far more efficient autonomous driving technology. Then they started helping Lockheed Martin with their artificial intelligence applications. When COVID-19 spread across the world, they applied their Explainable AI (XAI) platform toward developing unique new ways to detect positive cases.
And now, DarwinAI is becoming the leader in applying machine learning to challenges in the manufacturing sector, an industry that is ripe with opportunities to innovate with new technologies.
Who are they helping? What types of problems are they solving? How can companies looking to innovate work with them?
We asked Sheldon Fernandez, CEO at DarwinAI, to answer these questions and more.
Q: Let’s start with something that’s pretty central to this whole discussion – what is explainable AI?
FERNANDEZ: Explainable AI (XAI) is essentially a collection of technologies that reveals how and why AI makes the decisions that it does. This capability is important for optimizing performance and building trustworthy applications.
Darwin’s XAI technology applies to a wide range of automation and human-in-the-loop decision-making use cases, which enables us to build superior enterprise solutions that have a smaller memory footprint, [are] more computationally efficient and perform with high levels of precision.
Q: When manufacturers come to you, what kinds of problems are they usually trying to solve? Are they looking to improve processes, products or both?
FERNANDEZ: The problems that we encounter most often from manufacturing clients relate to visual quality inspection. Visual quality inspection can be a long and tedious process that manufacturers struggle with due to missed defects, the need for more lead time and high rework costs. It is one of the most crucial steps in the production process as quality inspection can prevent and limit defects before a product hits the shelf.
Darwin’s Explainable AI helps manufacturers improve both processes and product quality by locating defects and implementing continuous AI learning to make the solution smarter and more accurate over time.
Q: Is there a particular type of manufacturing that DarwinAI’s platform is best suited to help? Automotive? High tech? Or is the platform flexible to potentially help any company?
FERNANDEZ: DarwinAI can help customize a solution for any manufacturer in need of visual quality inspection. We help clients from industries such as aerospace, automotive, consumer goods, electronics and healthcare. Some examples of manufacturing solutions we’ve devised include scratch detection, PCB inspection and melt pool inspection.
Our mission is to help manufacturers adopt AI they can trust. In order to achieve this, we deliver robust and best-in-class quality inspection solutions with a relentless focus on customer success so manufacturers can transform their business using this technology.