What others promise:
The Protocloud Difference:
Demo in controlled lab lighting 
Validated in your actual environment 
Custom vision projects at Protocloud start from $12,000 for focused single-class detection solutions. Mid-complexity multi-class inspection systems with edge deployment typically cost $30,000–$65,000. Enterprise vision platforms with multi-camera setups, continuous learning, and analytics dashboards run $65,000–$120,000+. Every project starts with a free feasibility assessment and fixed quote. FAQ Schema Note: Apply FAQ schema (application/ld+json) to this section for Google rich results.
A focused vision project (single model + deployment) typically takes 8–12 weeks. Projects requiring extensive data collection, multi-class models, or complex edge deployments take 12–20 weeks. We demo working models on your actual footage every two weeks throughout the project.
For a focused single-class detection task with low variability, 500–1,000 images per class is sufficient. For multi-class, high-variability detection (many defect types, variable lighting), 2,000–5,000+ images per class delivers the accuracy needed. Our feasibility assessment will give you the exact number based on your application.
In most cases, yes. We support NVIDIA Jetson (Nano, Xavier, Orin), Intel NCS, Raspberry Pi 4/5, and custom industrial PCs. We optimise models using TensorRT and ONNX to meet your latency budget on your specific hardware. Camera compatibility is assessed in the feasibility phase.
Custom models trained with your actual lighting conditions – including data augmentation for brightness variation, shadow, and glare – perform significantly better than generic models in variable environments. We test explicitly in your lighting conditions during acceptance testing.
For controlled industrial inspection with consistent lighting: 98–99.9% accuracy is achievable. For retail and security applications with variable conditions: 92–97% is typical. For medical imaging with curated datasets: 90–96% sensitivity with clinical validation. We define and commit to your specific accuracy target in writing before project start.
Yes – if we collect and label enough representative examples. Our feasibility assessment will tell you exactly how many images we need per defect class, and our synthetic data augmentation can supplement rare defect types. We won’t start a project if the data required to hit your accuracy target isn’t achievable.
🛡 Guarantee: If our vision system doesn’t achieve the agreed accuracy on your production line within 60 days of deployment, we iterate at no additional cost.
This is exactly where custom models outperform pre-trained APIs. We collect data under your actual lighting conditions, camera angles, and product variants. Our data augmentation pipeline simulates lighting variation, rotation, and scale changes during training – so the model is robust to the same variation it will see in production.
🛡 Guarantee: We define and agree on production accuracy targets (not lab targets) before contract signing. Acceptance testing is done on your production line.
It depends on your throughput and latency requirements. We provide a detailed hardware specification (camera model, lens, lighting rig, compute hardware) as part of our fixed-price quote – with approved vendor recommendations and total system cost before you commit to anything.
🛡 Guarantee: Hardware specification and total system cost are provided in writing before project start. No hidden infrastructure costs.
Our continuous learning pipeline collects and flags production edge cases automatically. Monthly model updates keep your vision system accurate as product variants, packaging, or defect types evolve. One model update cycle is included in the 3-month post-launch support.
🛡 Guarantee: 3 months of post-launch monitoring and one model retraining cycle are included in every vision project at no additional cost.
In most cases, yes. We assess your existing camera resolution, frame rate, field of view, and lighting as part of our feasibility study. Many retrofit projects use 90%+ of existing infrastructure. We’ll be specific about what needs upgrading and why.
🛡 Guarantee: Camera suitability assessment is completed and reported in writing before any contract is signed.
