Computer Vision Solutions
End-to-end computer vision systems that turn visual data into actionable insights. We design, build and deploy robust CV pipelines for image and video that scale from prototypes to production, with an emphasis on accuracy, latency, and maintainability.
What We Deliver
For each engagement we focus on measurable outcomes: product-market fit, reliable models and systems, and an engineering setup for safe, maintainable production. Below are the core features and capabilities we implement as part of this service.
Custom Object Detection & Multi-class Tracking (YOLO/DETR-based pipelines)
Instance & Semantic Segmentation (Mask R-CNN, U-Net, custom models)
Pose Estimation & Human Activity Recognition for safety and analytics
Real-time Video Intelligence & Stream Processing (RTSP, WebRTC)
Edge & On-device Inference (TensorRT, OpenVINO, CoreML)
High-quality dataset curation, annotation pipelines, and active learning
Model optimization, quantization and pruning for production efficiency
Automated monitoring, drift detection and retraining workflows
Our Approach
- 1
Discovery & Feasibility
We run a short discovery to validate data availability, define success metrics and create a technical feasibility plan with a clear MVP scope.
- 2
Prototype & Validation
Rapid prototyping to validate model quality and integration assumptions. We include human-in-the-loop evaluation and benchmarks.
- 3
Productionization
Harden the best models into reproducible pipelines, add monitoring, CI/CD, and optimize for latency and cost (edge or cloud deployment as required).
- 4
Scale & Operate
Ongoing improvements, retraining pipelines, A/B testing and performance SLAs.
Technology We Use
We use industry-leading technologies and best practices to deliver high-quality, scalable solutions.
AI & Machine Learning
- PyTorch & TensorFlow
- YOLO, Mask R-CNN models
- OpenCV for image processing
- TensorRT optimization
- Edge deployment (Jetson, CoreML)
Infrastructure & Deployment
- GPU infrastructure (CUDA)
- Model versioning & MLOps
- Real-time video processing
- Cloud & edge deployment
Representative Case Studies
Automated Visual QC for Manufacturing
Delivered an edge-deployable computer vision pipeline for defect detection reducing inspection time by 85% and improving defect catch-rate by 30%.
- Throughput ↑ 5x
- Defect detection ↑ 30%
- Operational cost ↓ 40%
Object Detection System
Built real-time object detection and tracking system for retail analytics with 95% accuracy.
- Detection accuracy: 95%
- Processing speed: 30 FPS
- Insights generation ↑ 200%
Deliverables & Engagement Models
Proof of Value
2–6 week spike to validate feasibility and demonstrate measurable improvement on a target metric.
Product Delivery
Full implementation from prototype to production with monitoring and training pipelines.
Staff Augmentation
Embed our engineers with your team for ongoing development and maintenance.
Frequently Asked Questions
What is the typical project timeline?
Project timeline varies based on complexity and requirements. Small projects take 4-8 weeks, medium projects 2-3 months, and large projects 4-6 months or more. We provide detailed timelines after understanding your specific needs.
Do you offer post-launch support?
Yes, we provide comprehensive post-launch support including bug fixes, performance monitoring, security updates, and feature enhancements. We offer various support packages to meet your needs.
What is your pricing model?
We offer flexible pricing models including fixed-price projects, time & materials, and retainer agreements. Contact us for a customized quote based on your specific requirements.
How do you ensure project quality?
We follow best practices including code reviews, automated testing, continuous integration, quality assurance testing, and regular client feedback sessions to ensure the highest quality deliverables.
Ready to Get Started?
Book a free discovery call and receive a tailored roadmap and estimate for your project.