Understand, Analyze, and Automate: The power of computer vision
In our digitalized world, data is becoming increasingly visual: photos, videos, sensor data and 3D scans make up a large part of the volume of information. Computer vision (CV) is the branch of artificial intelligence that enables machines to interpret images and videos, recognize objects and analyze complex scenes.
Applications range from industrial quality assurance and robotics to autonomous driving, medical image analysis and retail to security monitoring.
The challenge is to achieve high-precision and at the same time low-latency recognition results, to develop robust algorithms for various lighting and environmental conditions and to make solutions GDPR-compliant and explainable. In time-critical applications — such as autonomous vehicles or medical diagnostics — CV systems must evaluate images within milliseconds, finding the balance between accuracy, speed and energy efficiency.
So that users can trust the results, explainable AI (XAI) in focus: Deep learning Models are considered black boxes; XAI methods provide understandable explanations and increase transparency and acceptance.
Real Results
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Suspendisse varius enim in eros elementum tristique.
Real Results
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Suspendisse varius enim in eros elementum tristique.
Why computer vision is revolutionizing your industry: Benefits and concrete added value
- Automated image and object recognition: Efficient identification of products, defects or people in real time.
- Quality assurance in real time: Quick fault detection in production lines, reduces recall costs.
- Process optimization: Automated inspections and analyses save time and resources.
- Improved security: Face recognition, video surveillance and access controls for a higher level of security.
- Data-based insights: Visual data analytics for better decision making.
- Scalable solutions: Flexibly adapted to different requirements, from small apps to large-scale monitoring systems.
AMAI — Your partner for effective computer vision solutions
As a specialized AI service provider, AMAI develops high-performance computer vision systems that scale from edge cameras to cloud platforms. Our interdisciplinary teams of data scientists, ML engineers and software architects combine state-of-the-art deep learning (e.g. CNNs, VITs) with proven methods of classic image processing. Outcome: Solutions that work precisely, quickly and reliably, even under difficult lighting and environmental conditions.
We support you end-to-end from feasibility analysis to data preparation & model training to operation with MLOps.
Use cases: Examples of how you can use AI in your company
Our process model: This is how we move your AI initiative forward.
As a pure AI consulting and development company, we focus exclusively on AI projects. Our four-stage process model offers you maximum orientation from strategy to production-ready implementation. You don't have to go through all steps: We start right where you are and reliably bring your AI initiative to the next level.
Before individual use cases are developed and evaluated, we work with you to define your company's overall AI strategy. In doing so, we define goals, fields of action, governance objectives and long-term development directions. This creates clarity, focus and priorities and forms the basis for all next steps, from use case workshops to implementation.
With proven components, proven infrastructure and close coordination with your team, we efficiently put your AI solution into productive use. Real transfer of knowledge is taking place continuously.
✔ No prototype without a plan.
✔ No project has no effect.
✔ No effort without results.
Case studies: Successfully implemented AI projects
This is how computer vision works and these technologies are behind it
What is computer vision (CV) in a few words?
As a branch of artificial intelligence, computer vision enables machines to automatically understand visual information such as images and videos, recognize objects and analyze complex scenes.
How do convolutional neural networks (CNNs) work in practice?
CNNs break up image pixels into hierarchical patterns ranging from edges to textures to complete objects. Several folding and pooling layers filter these features so that the network reliably recognizes cats, production errors or traffic signs after training, for example.
Why do you rely on transfer learning instead of training “from scratch”?
Transfer learning uses pre-trained models (e.g. ImageNet, CLIP) as a basis and fine-tunes them to company-specific data sets. This saves up to 80% of training time, reduces the need for labeled images and leads to faster ROI.
What role do data augmentation and 3D vision play for robust models?
- Data augmentation (rotate, mirror, color shift) creates artificial training variants and prevents overfitting.
- 3D vision combines stereo or depth cameras with algorithms such as structure-from-motion and provides volumetric information, which is essential for robotics, AR/VR and logistics automation.
How do you achieve real-time performance for edge and cloud deployments?
Through lightweight models (YoloV8, MobileNet, Vision Transformers in tiny variants), quantization, pruning and hardware accelerators (GPU, TPU, Edge TPU). This achieves latencies of <50 ms, which is crucial for inline quality assurance or driver assistance systems.
What does Explainable AI (XAI) mean in the context of computer vision?
XAI methods such as Grad-CAM or SHAP visualize which areas of the image contributed to the decision. This creates trust, facilitates audits (e.g. MDR, ISO 21434) and meets GDPR transparency requirements.
How do CV models remain performant in the long term?
Through MLOPS pipelines with continuous monitoring, automated retraining for data drift and CI/CD deployment on Kubernetes. This allows models to be safely updated without interrupting live operation.
Real Results
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Suspendisse varius enim in eros elementum tristique.
Real Results
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Suspendisse varius enim in eros elementum tristique.
About AMAI: What sets us apart!
We are not a generalist with an AI connection — we are AI specialists with implementation experience. It is precisely this concentration that brings speed, quality and impact to our customers.
AI use case identification & evaluation
AI business cases & roadmaps
Model development & ML engineering
System integration & productive implementation
Productivity, Scaling & Enablement
Explainability & responsible AI
