Computer vision projects succeed or fail on details: lighting, camera angles, rare edge cases, and how fast a decision must be made. As a dedicated practice within our custom AI development services, our computer vision engineers handle every stage, from proving feasibility on your images to running models reliably on the factory floor, in stores, or in the field.
Our computer vision consulting helps you decide what is technically possible before you invest. We review your use case, camera setup, and sample data, test feasibility, and recommend models, hardware, and accuracy targets.
Clear deliverables: A feasibility report, data plan, architecture, hardware recommendations, and a phased cost and timeline estimate.
When off-the-shelf APIs can't recognize your products, parts, or defects, we train custom models on your data using transfer learning, fine-tuning, and modern architectures such as YOLO, vision transformers, and segmentation models.
Built for your conditions: Models are tested against your real lighting, angles, backgrounds, and edge cases, not just clean benchmark images.
We build systems that find, count, and follow people, vehicles, products, and equipment across frames and cameras, supporting inventory counts, traffic analysis, queue monitoring, and workplace safety.
Real-time ready: Multi-object tracking, zone and line-crossing rules, and alerts that trigger the moment an event happens.
We develop models that categorize images and outline objects at the pixel level, used for medical image analysis, crop and land monitoring, product sorting, and measuring areas, sizes, or damage.
Precise measurement: Instance and semantic segmentation turn images into measurable data for reports, pricing, and quality decisions.
We build inspection systems that spot scratches, cracks, misalignments, missing components, and labeling errors on production lines, catching defects consistently at line speed.
Works with rare defects: Anomaly detection lets you start with mostly good samples when defect images are scarce.
We extract text and fields from invoices, IDs, labels, serial plates, meters, and handwritten forms, including text in difficult conditions such as curved surfaces, glare, and low resolution.
Connected to your systems: Extracted data is validated and pushed straight into your ERP, WMS, or back-office tools.
We turn live and recorded video into searchable events, heatmaps, counts, and alerts, helping teams monitor safety, footfall, operations, and security without watching hours of footage.
Scales across sites: Pipelines process many camera streams in parallel and feed results into dashboards and incident workflows.
We work with depth cameras, LiDAR, and stereo vision to measure volumes and dimensions, guide robots, create 3D reconstructions, and power AR experiences such as virtual try-ons and guided assembly.
Practical uses: Parcel dimensioning, pick-and-place robotics, construction progress tracking, and spatial measurement apps.
We optimize and deploy models to NVIDIA Jetson devices, industrial PCs, smart cameras, and mobile phones, so decisions happen in milliseconds and video doesn't need to leave your site.
Optimized for hardware: Quantization, pruning, and runtimes such as TensorRT, OpenVINO, and ONNX Runtime keep models fast on limited hardware.
Cameras move, lighting changes, and products evolve. We monitor model accuracy in production, collect hard examples, retrain on new data, and roll out updated models safely across devices.
Long-term reliability: Versioned datasets and models, drift alerts, and staged rollouts keep accuracy steady over time.
Need to add vision expertise to your own team? Hire a computer vision engineer at the level your project needs, from model training and data pipelines to edge optimization and production MLOps.
| Engineer Level | Computer Vision Engineer | Senior Computer Vision Engineer | Computer Vision Lead / Architect |
|---|---|---|---|
| Experience | 2 to 4 years | 5 to 8 years | 8+ years |
| Best For | Data preparation, model training, and feature work on defined tasks | Custom models, real-time pipelines, and edge deployment | Architecture, multi-site rollouts, and team leadership |
| Core Skills | Python, OpenCV, PyTorch, YOLO, data labeling | Segmentation, tracking, TensorRT, ONNX, video pipelines | System design, MLOps, hardware selection, evaluation strategy |
| Engagement | Full-time, part-time, or hourly | Full-time, part-time, or hourly | Full-time or part-time |
| Rates | Shared after a short requirements call, based on skills, duration, and team size | ||
Add a vetted computer vision engineer to your in-house team. You interview them first, assign the work, and they join your stand-ups and tools.
Get engineers, data annotators, a QA specialist, and a project manager working only on your product, scaling up or down as your roadmap changes.
Hand us the outcome. We run consulting, data, training, integration, and deployment against agreed milestones and accuracy targets.
Send us a few sample images or a short video clip. Our computer vision engineers will review feasibility, expected accuracy, and the right hardware, then recommend the fastest path to a working proof of concept.
We choose frameworks, models, and hardware based on your accuracy targets, speed requirements, deployment environment, and budget.
A computer vision model that scores well on test images can still fail on a dusty camera, a night shift, or a new product variant. Our engineers start every project by studying your actual environment and data, define accuracy targets that match the business cost of a missed detection or a false alarm, and test against the edge cases most likely to break the system.
With an office in Rochester, New York, and a delivery center in New Delhi, we combine US-based project leadership with cost-effective engineering and overlapping working hours. After launch, the same team monitors accuracy, retrains models as conditions change, and manages updates across every camera and device.
SATISFIED CUSTOMERS
YEARS IN BUSINESS
EXPERT DEVELOPERS
PROJECTS DELIVERED
In our long relationship with Alcax over past 5+ years, we have witnessed a significant expansion in the range of their services and products and we have always enjoyed a high level of customer-focused mentality, professionalism and sustainability.
Understanding the needs of customers is the key to any successful business. Alcax perfectly understands these needs and knows how to translate them into applicable strategies. Alcax's software developers are world class experts in their field and they were more eager than us to get things done.
Alcax has demonstrated a high degree of flexibility and scalability to enable us meet our strategic goals. Their commitment, execution excellence and ability to work with us has made a tremendous difference. Alcax has the advantage of deep domain expertise and provides industry's best ROI.
We review your use case, cameras, and sample data, confirm feasibility, set accuracy and speed targets, and agree on scope, hardware, and budget.
We gather representative images and video, label them with quality checks, and add augmentation or synthetic data to cover rare cases.
We train and benchmark models, optimize them for your hardware, and connect them to cameras, dashboards, alerts, and business systems.
We roll out in stages, monitor accuracy in production, collect hard examples, and retrain models as your environment and products change.
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