High-Accuracy Computer Vision & OCR Engineering for US Platforms
Automate visual inspections, document processing, and spatial object detection. Senior software architect Mr Umer Malik builds production-ready computer vision pipelines utilizing YOLOv10, OpenCV, and PyTorch for American industrial, healthcare, and enterprise platforms under Delaware mutual NDA.
Core Capabilities & Production Deliverables
Direct architectural execution by senior engineer Mr Umer Malik with zero agency dilution.
Real-Time Object Detection & Tracking
High-speed object identification, counting, and boundary tracking running at 30+ fps on video feeds via YOLO and OpenCV.
Automated Document OCR & Field Extraction
Extracting structured data from physical invoices, shipping manifests, receipts, and IDs with custom Transformer-based OCR pipelines.
Industrial Quality Inspection & Defect Detection
Automating manufacturing defect detection on production assembly lines, identifying micro-scratches and dimensional anomalies.
Edge Device & Mobile Video Optimization
Optimizing vision models via TensorRT and CoreML for real-time inference on iPhone, Android, and edge computing hardware (Jetson).
Facial Recognition & Biometric Liveness
Passive 3D liveness detection and facial biometric verification preventing spoofing attacks on digital identity platforms.
Cloud GPU Inference & Scaling Pipelines
Containerized model deployment on AWS G4/G5 GPU instances capable of processing thousands of incoming video streams simultaneously.
Why US Enterprises Hire Umer for Vision AI
Direct access to senior computer vision engineering capable of deploying models to production.
Sub-50ms Inference on Video Feeds
Optimized TensorRT models delivering real-time frame analysis with minimal GPU hardware overhead.
Delaware Mutual NDA Protection
Strict confidentiality protecting proprietary image training datasets, CAD drawings, and customer records.
Predictable Milestone Pricing
Transparent fixed pricing per computer vision pipeline in USD with zero surprise compute fees.
Synchronized US Daytime Collaboration
Direct Slack collaboration with lead architect Mr Umer Malik during your working hours.
Phased Delivery Roadmap & How This Project Runs
Structured from initial discovery call to production deployment and 100% intellectual property transfer.
Phase 01: Image Dataset & Accuracy Goal Scoping
Auditing sample images, defining mAP/accuracy targets, and setting fixed milestone pricing in USD.
Phase 02: Model Training & Hyperparameter Tuning
Annotating images, fine-tuning YOLO/PyTorch models, and evaluating accuracy on validation sets.
Phase 03: Inference API & Edge Optimization
Exporting models to TensorRT/CoreML and building containerized FastAPI inference microservices.
Phase 04: Production Deployment & Camera Integration
Connecting live video streams, verifying real-time detection, full repository handover, and 30-day warranty.
US Founder Frequently Asked Questions
Clear answers on US business hours alignment, USD milestone billing, and Delaware mutual NDA protection.
Can computer vision models run directly on mobile phones or edge devices? ▼
How many sample images are needed to train a custom detection model? ▼
Can you extract structured data from unstructured physical documents? ▼
How do you handle privacy and compliance with video surveillance feeds? ▼
Who owns the trained model weights and training scripts? ▼
What warranty is included after computer vision deployment? ▼
Great dreams deserve craftsmanship, not compromises. Let’s build yours.
US METROS & STATES ACTIVELY SERVED
© 2026 UMER XPERT. SERVING THE UNITED STATES — COAST TO COAST. All rights reserved. Contracts executed under Delaware mutual NDA.