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]
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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.

  1. 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

  2. Future-proof value

    We enable a feedback loop that makes the system smarter over time by continually learning from real production data

  3. 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

  4. Higher accuracy

    Our XAI accelerates the creation and calibration of AI models to your specific use case, improving accuracy for better results

  5. 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

  6. 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

  • Surface defects

    Including distinguishing between cracks, dents, etc.

  • Coatings

    Ensure desired coverage uniformity

  • Tiny, high volume parts

    Distinguish between debris vs damage, to inform rework decisions

  • Additive manufacturing

    Inspect melt pool; measure surface density and weld quality from LPBF

  • CT-based

    Non-destructive testing

  • Metal alloy

    Inspect grain size

  • Solder joint

    Inspect solder joints for worker and non-worker defects

  • Predictive maintenance

    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

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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.

  1. 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

  2. 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

  3. Regulatory Compliance

    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

Trusted By Innovators

Our technology is trusted by some of the world’s leading enterprises.

Increase profitability and outperform your competition by introducing AI you can trust.