Computer Vision & Vision Models. In focus.
Vision trained on your line, your parts, your defects. Deploy custom vision AI for image recognition, object detection, visual inspection, and video analytics tailored to your business needs.
Book a Fusion WorkshopThe spec.
The build, stage by stage. This is what the design phase papers and prices.
You own the build. The workflow, the integrations, and the credentials live in your accounts, not ours. Documented, handed over, yours.
Fixed price. Fixed date.
The walk-away: If automation will not pay for itself in your operation, we say so at the workshop, and you keep the map.
What we need from you: a decision-maker in the workshop, system access by week one, and honest answers about how the work really flows.
The receipts.
Builds on the same system. Every number is measured, not promised.
Adjacent builds.
Most engagements expand into one of these after the first build proves out.
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Straight answers.
How is this different from your existing Computer Vision Solutions service?
Our Computer Vision Solutions service focuses on deploying complete vision-powered business solutions end-to-end. This Computer Vision and Vision Models service is specifically about building and training custom vision AI models tailored to your unique visual domain. Think of it as the model-building expertise behind the solutions. Clients who need custom-trained models for novel use cases, fine-tuned detection for their specific products, or multimodal AI that combines vision with language come to this service for the specialized model development work.
How many training images do I need for a custom vision model?
Thanks to modern transfer learning and foundation models, you need far fewer images than you might expect. For many object detection and classification tasks, 200 to 1,000 labeled images per category produce strong results. For more nuanced tasks like defect detection with subtle visual differences, 500 to 2,000 examples may be needed. We assist with data collection strategies, annotation, and augmentation techniques that maximize model performance from limited data. A pilot with sample data helps us establish exact requirements for your use case.
Can vision models work in challenging lighting or environmental conditions?
Yes. We specifically train and test models under the real-world conditions they will encounter in your environment. This includes varying lighting conditions, camera angles, weather effects for outdoor applications, motion blur from moving conveyor belts, and occlusion from overlapping objects. We use data augmentation techniques during training to make models hold up to these variations, and we can recommend environmental adjustments like supplemental lighting that improve performance cost-effectively.
Do vision models require powerful hardware to run?
The hardware requirements depend on the application. Many vision models run efficiently on affordable edge devices like NVIDIA Jetson or even optimized mobile processors, processing video feeds in real-time at low power consumption. More demanding applications, like analyzing multiple high-resolution camera feeds simultaneously, may require dedicated GPU servers. We optimize model architectures for your deployment target, balancing accuracy against computational efficiency to ensure the model runs reliably on the hardware that fits your budget.