AI service · Computer Vision
Computer Vision Development
We build computer vision systems that watch what humans can't watch continuously: every unit on the line, every frame of the feed, every incoming document. Defect detection, counting, OCR, and safety monitoring — engineered for your lighting, your cameras, and your accuracy requirements, running on the edge or in the cloud.
Free scoping call · Clear ROI plan before any commitment
The challenge
Visual work doesn't scale on human attention. Inspectors sample a fraction of production and fatigue on repetitive checks; document teams re-key what's printed on paper; safety compliance depends on whoever happens to be looking. Generic vision APIs demo well on stock photos but fall apart on your actual conditions — glare on the line, motion blur, unusual parts, low-quality scans.
How we solve it
We engineer vision for your real conditions, not benchmark images. That starts with a data strategy — collecting and labeling images from your environment, augmenting for the variations that break naive models — and continues through model selection (modern vision-language models where they suffice, custom-trained detectors where they don't), edge deployment when latency or bandwidth demands it, and a feedback loop where flagged cases retrain the system. We validate against your ground truth before rollout, so the accuracy number is real.
Capabilities
What we deliver
The building blocks of a production-grade computer vision engagement.
Visual quality inspection
Automated defect detection on production lines — surface flaws, assembly errors, missing components — at 100% inspection rates humans can't sustain.
Object detection & counting
Real-time detection, counting, and tracking of products, pallets, vehicles, and people for inventory, throughput, and yard management.
Document OCR & visual extraction
Vision-model pipelines that read scans, handwriting, labels, and photos of documents into clean structured data — beyond what template OCR can handle.
Video analytics & safety monitoring
Continuous analysis of camera feeds for PPE compliance, restricted-zone entry, and incident detection, with privacy-conscious design and human-verified alerts.
Edge deployment
Optimized models running on-site — NVIDIA Jetson, industrial PCs, smart cameras — for millisecond decisions without shipping video to the cloud.
How we work
A clear path to production
Five stages, each with visible output — you're never waiting on a black box.
Discovery & scoping
We map the problem, success metrics, constraints, and existing systems before writing code. You leave with a clear scope, timeline, and a fixed view of what 'done' means.
Architecture & design
We design the system end to end — data model, integrations, security, and a path to scale — and validate it against your real workloads, not a demo.
Iterative delivery
We ship in short, reviewable increments. You see working software every sprint, give feedback early, and never wait months to find out it missed the mark.
Hardening & launch
Testing, observability, performance, and security are built in, not bolted on. We launch with monitoring in place and a rollback plan ready.
Support & iteration
After launch we stay on — measuring outcomes, fixing fast, and iterating on what the data tells us actually moves the metric.
Representative stack
- PyTorch / YOLO
- OpenCV
- Vision-language models (Claude, GPT-4V)
- NVIDIA Jetson / TensorRT
- ONNX Runtime
- Python / C++
Where it applies
Computer Vision in the industries we serve
Vertical context changes what good looks like — see how this capability lands in your space.
Manufacturing
MES, IoT, and predictive AI that improve throughput, quality, and uptime on the floor.
Explore ManufacturingLogistics
Tracking, routing, and warehouse software with real-time data and AI-driven optimization.
Explore LogisticsHealthcare
HIPAA-aware platforms, patient-facing apps, and clinical automation built for security and reliability.
Explore HealthcareAnswers
Frequently asked questions
How accurate can automated visual inspection get?
On well-scoped defect classes with decent imaging, custom-trained models routinely match or beat sustained human inspection — while checking every unit instead of a sample. We establish your accuracy requirement first, validate against labeled ground truth from your line, and report the real number before you rely on it.
Do we need special cameras or new hardware?
Often your existing cameras are usable, and we always evaluate them first. Where imaging is the bottleneck — resolution, lighting, angle — we specify cost-effective industrial cameras and lighting as part of the design. Compute can run on a single edge device or your cloud, sized to the workload.
How many labeled images does training require?
Far fewer than a few years ago. Pre-trained foundations and synthetic augmentation mean many detection tasks start from hundreds of labeled examples per class, not tens of thousands — and the system keeps improving as production data flows through the feedback loop. We handle labeling tooling and strategy.
Can vision systems run without internet on the factory floor?
Yes — edge deployment is standard for us. Models run locally on industrial hardware with millisecond latency and no dependency on connectivity; results sync to your systems when a connection is available, and model updates roll out remotely under your control.
Ready to build with Computer Vision?
Book a free consultation and we'll map the fastest path to a working system — with the metric that proves it.