In contrast to a couple of years ago, Deep Learning is no longer an exclusive technology. Once groundbreaking and complex, it has now become accessible to many businesses thanks to ready-to-use tools and open-source software. At CQM, we know this better than anyone, having used Machine Learning and Deep Learning in pioneering projects early on. A prime example of such an early adopter project was the successful collaboration with VolkerRail/Inspectation. There, we were able to deliver measurable results while being ahead of the market. This project was even awarded the prestigious Dutch Data Science Award. But what did this groundwork mean in practice? And how can businesses today leverage this powerful technology?
Smart image recognition in the VolkerRail case
In collaboration with VolkerRail and Inspectation, CQM automated the labor-intensive process of rail inspection. Previously, inspectors manually reviewed thousands of rail images—an error-prone and monotonous task. Using advanced image recognition and self-learning algorithms, we made this process five times more efficient.
The impact:
- 80% fewer images needed manual review.
- Improved accuracy and reliability in detecting rail defects.
- Enhanced safety and availability of railways through early detection of potential issues.
This project was not just a technological breakthrough; it set the standard for intelligent automation in the rail sector. Read the full story here.
How to apply Deep Learning for your business
What once required pioneering effort has now become a commodity. Thanks to modern hardware, open-source libraries (such as TensorFlow and PyTorch), standard services (like Amazon Rekognition and Google Cloud Vision API), and vast amounts of data, Deep Learning solutions are widely available.
Yet, one thing remains constant: success depends on a combination of expertise with a deep understanding of business challenges, and a tech savvyness that creates practical solutions. That’s where CQM has a proven trackrecord in.
From challenge to solution
Whether it’s image recognition, complex predictive models, or optimization, we develop smart solutions that make a real impact. Here are some examples of how businesses are leveraging Deep Learning:
- Product Development: Predicting product performance.
- Manufacturing: Automatic quality control and anomaly detection.
- Warehousing: Optimizing logistics and inventory management.
- Transportation: Planning customer demand, vehicles, and staff.
Why choose CQM?
At CQM, we combine years of experience in Machine Learning and Deep Learning with a deep understanding of business processes in different domains. Our approach is unique because of:
- Pragmatic implementation: We develop models that deliver immediate value.
- Quality over quantity: No hype—just proven technology and reliable results.
- Tailored solutions: Every organization is unique, so we create solutions that fit your specific needs.
- Continuous improvement: Our models learn from your data and keep optimizing over time.
Whether you want to streamline existing processes or uncover new insights, we help you unlock the full potential of your data.
Ready to translate technology into tangible results?
Deep Learning offers countless opportunities, but success requires a partner who understands how to translate technology into tangible results. At CQM, we have the knowledge, experience, and passion to turn your challenges into success stories—just as we did for VolkerRail.
Discover how we can empower your organization. Contact Matthijs Tijink today, and let’s explore the possibilities together.
