With DarwinAI’s unique Explainable AI (XAI) technology, manufacturers enable new processes, unlock new efficiencies—and increase profitability.
The next manufacturing revolution relies upon a synthesis of technologies including AI, automation, the Industrial Internet of Things (IIoT), on-premise and cloud services, and centralized management systems.
To outperform your competition and thrive within the Industry 4.0 paradigm and beyond, manufacturers must unlock the value of their data by using it in innovative and effective ways—and AI is the key.
Let’s Unlock the Value of Your Data
Because of its enormous potential and broad range of applications, AI is on the brink of mass adoption. This growth is driven by the increasing number of large and complex datasets, and the parallel rise of Industrial IoT and automation.
Beyond the Industry 4.0 Manufacturing Paradigm
- AI represents perhaps the greatest leap from what was to what will be
- The promise and potential is such that the widespread adoption of AI is a matter of “when” rather than “if”
- The AI opportunity is forecast to reach $16.7B USD by 2026 [Markets and Markets]
- First-movers will gain valuable competitive advantages in the global marketplace
- of US manufacturers believe smart factories will be the main competition driver by 2025 [Deloitte]
- of US manufacturers believe smart factories will transform production [Deloitte]
- of manufacturers in Asia believe AI will drive growth and innovation [Deloitte]
Explainable AI, Remarkable Real-World Results
Our high-performance, Explainable AI solutions are built with our proprietary XAI technology—a differentiator that delivers important business benefits.
Unlike inflexible AI technologies or time-consuming in-house projects, our manufacturing products quickly deliver unmatched accuracy and reliability, backed by our renowned deep learning experts.
More AI use cases
Our technology creates AI models that run on less-powerful, less-costly edge equipment, with higher performance than those produced by other AI offerings—unlocking new deployment possibilities and use cases that aren’t possible with alternative approaches
We enable a feedback loop that makes the system smarter over time by continually learning from real production data
Trust and transparency
Explainability illustrates why AI does what it does, which is important for optimizing performance and building trust with users—and which will soon be critical for using AI in regulated industries
Our XAI accelerates the creation and calibration of AI models to your specific use case, improving accuracy for better results
Faster project timelines
Getting started with our product requires only a fraction of the number of data samples needed by traditional AI systems, making it much easier to get started; plus, the overall design and optimization process is dramatically accelerated
Superior real world utility
Unlike technologies that only work in ideal scenarios, we solve problems in the real world—where data quality and quantity may be limited, computing resources are scarce, and trust is an absolute necessity
Inspection & Defect Detection
Including distinguishing between cracks, dents, etc.
Ensure desired coverage uniformity
Tiny, high volume parts
Distinguish between debris vs damage, to inform rework decisions
Inspect melt pool; measure surface density and weld quality from LPBF
Inspect grain size
Inspect solder joints for worker and non-worker defects
Monitor machine health to predict when product variability may arise
Adaptive Factory Automation
Robotic pick and place
Enable new movements while ensuring safety and improve grasp point detection
Adaptive control systems
Implement real-time automated control systems and enhance human-in-the-loop operation
A global aerospace & defense manufacturer improves production efficiency with DarwinAI’s Explainable AI platform
Aspire Food Group fully automates a protein production facility with DarwinAI’s adaptive control technology
The Explainability Imperative
As manufacturers increasingly turn to AI, “explainability” features that reveal how an AI model works and why it has made a particular decision will be especially important—for a few reasons.
Effectiveness and Efficiency
Explainability makes the development, maintenance, and extension of AI-powered solutions both more effective and more efficient—helping manufacturers to introduce better solutions, sooner, to maximize lifetime ROI
Assistance and Auditability
Some manufacturing use cases leverage explainability as part of their operational implementation, literally revealing to an operator in real time the reasons why a particular decision—for example, an inspection outcome—has been made and forever logging that information in an auditable database
Because of concerns about bias, privacy, security, and other factors, many regulators are introducing rules that govern the use of artificial intelligence. As a result, businesses subject to such legislation—which includes many manufacturers—may not be able to use AI solutions that lack explainability features
More From Our Team
One of our primary insights in working with manufacturing clients is their need for practical AI solutions that provide transparent, purpose-specific benefits that operators can trust. Enterprises routinely turn to our technology to maximize the value of their operational data to unlock new value opportunities in a rapid and reliable manner. To this end, we are thrilled to continue to partner with innovative clients to transform their manufacturing processes through our unique ability to make Artificial Intelligence transparent and trustworthy.Sheldon Fernandez CEO, DarwinAI
Madiha Jafri Asc. Fellow (Artificial Intelligence & Cybersecurity)
Lockheed Martin is paving the way to fully align with the DoD’s AI Ethics Principles and we’re proud to have DarwinAI as one of our trusted and strategic partners. Besides differentiated IP and advanced offerings around Explainable AI (XAI) and ML trustworthiness, the DarwinAI team understands Enterprise-level complexities, and have fused their impressive AI technology with robust product features required by large defense primes. We’re excited for our continued collaboration on this journey.
Mike Stewart Vice President Of Advanced Technology, Honeywell Aerospace
DarwinAI’s platform facilitates improved performance in deep learning models on our embedded platforms, providing greater accuracy with a smaller footprint. Explainability is crucial to certifying AI models for airborne applications and we believe Darwin’s capabilities will enable us to develop trustworthy AI.
Mohammed Ashour Co-Founder, CEO, Aspire Food Group
Aspire Food Group is collaborating with DarwinAI to optimize the biological and breeding processes to produce high quality insect protein in our new plant in London, Ontario. Aspire and DarwinAI share a common goal which is to produce better food more efficiently. The value of AI has been proven with crops, in greenhouses and with vertical agriculture. This project shows the value of AI in applications that meld agricultural production with industrial technologies such as automated storage and retrieval.
Jan Seyler Head of Advanced Develop. Analytics and Control, Festo SE & Co. KG
In the FLAIROP research project we are developing new ways for robots to learn from each other without sharing sensitive data and company secrets. In this way, they can take over many tasks more quickly. The collaborative robots can then, for example, support production workers with repetitive, heavy and tiring work. DarwinAI together with the University of Waterloo are our partners in the project and are aiming to support us with Neural Network design.
Lee Rhitholtz Director & Chief Architect, Applied Artificial Intelligence · Lockheed Martin
DarwinAI’s technology, particularly around explainability and transparency, was key in helping us develop robust Machine Learning systems for numerous use-cases at Lockheed Martin. The company’s recent work around Explainable AI (XAI) is truly groundbreaking and will be a critical offering for the defense space in general.
What differentiates the DarwinAI team as compared to other AI organizations is their unique ability to fuse the theoretical and practical to deliver tangible business results. Their recent work in manufacturing – harnessing XAI to assist human-in-the-loop decision-making – is a testament to this capability. It’s been a joy to work with such an innovative and highly professional team.
Trusted By Innovators
Our technology is trusted by some of the world’s leading enterprises.