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I am an AR/VR Solution Architect and Idea Generator with 10+ years of hands-on experience creating immersive 3D, AR, VR, and real-time web solutions. My primary value lies in transforming raw ideas into clear, viable, and scalable technical concepts. I generate product ideas, define system architecture, choose the right technologies, and design the overall technical vision that turns concepts into real, working products. I stay personally involved in the most critical parts of implementation to ensure that the original idea is executed correctly and reliably. I specialize in projects where there is no ready-made solution and where strong architectural thinking is required — including AR/VR platforms, interactive simulations, digital twins, product configurators, and experimental real-time 3D applications. What you can expect: • Clear product and technical vision from the very first discussion • Thoughtful architecture built for scalability and long-term use • Hands-on implementation of core and complex components • Direct communication with the person responsible for technical decisions • Production-ready solutions, not just prototypes or demos Core expertise: AR / VR / XR • WebXR, 8th Wall, ZapWorks, Spark AR • Unity (C#): AR, VR, MR applications • AR Foundation, ARCore, ARKit, Vuforia, EasyAR • VR frameworks: XR Interaction Toolkit, VRTK, Oculus SDK Unreal Engine • Unreal Engine 4 / 5 (Blueprints & C++) • Real-time visualization and architectural walkthroughs • Interactive simulations and product configurators • CARLA Simulator for autonomous driving and simulation • Niagara VFX, Sequencer, Metahuman integration Web & Real-Time 3D • Three.js, A-Frame, PlayCanvas • WebGL, GLSL • React, Vue.js • Desktop packaging with Tauri and Electron Backend & System Architecture • Node.js, PHP, Laravel • MySQL, PostgreSQL, MongoDB • Docker, Nginx • API integration and system design How I work: I work directly with clients from the idea stage. I help shape the concept, define the architecture, validate technical assumptions, and personally implement or prototype the most critical parts of the system. My goal is to ensure that the final solution is technically sound, scalable, and aligned with the original vision. Typical use cases: • Turning early-stage ideas into technical concepts and prototypes • Designing architecture for complex AR/VR and 3D systems • Interactive simulations and digital twins • 3D product configurators and visualization platforms • Technical consulting and architecture reviews My goal is to help you move from an idea to a clear, technically grounded solution that can grow into a real product. Feel free to book a consultation to discuss your idea, concept, or technical challenge. Keywords: AR, VR, XR, WebXR, Unity, Unreal Engine, Three.js, WebGL, Simulation, Digital Twin, Product Configurator, Real-Time 3D, Interactive Visualization, ARKit, ARCore, Vuforia, Mixed Reality, Oculus, HTC Vive, HoloLens

I build native iOS and Android applications that work in the real world - in the field, offline, in complex physical environments where most mobile solutions fall apart. My focus is on technically demanding work: augmented reality and spatial computing, LiDAR-based 3D reconstruction and site scanning, GIS and GNSS field data collection, BLE and IoT device integration, and AI/ML features that actually ship. Not demos — production systems. I'm the founder of Quality Wolves, a senior-only engineering team. Everyone on the team has owned full project cycles and made architectural decisions. That's not a recruiting pitch, it's what determines how we engage with clients. Most development relationships are high-maintenance by design: status check-ins, approvals on every decision, the client becomes a de facto project manager. I work the opposite way. I take ownership of the technical scope, surface what matters, and keep things moving. You stay focused on your product. I handle the build. What I build: Native Mobile — Swift, SwiftUI, Kotlin, full-cycle iOS & Android development, App Store and Google Play delivery AR / Spatial Computing — ARKit, ARCore, RealityKit, LiDAR scanning, point cloud processing, 3D reconstruction, Apple Vision Pro GIS & Field Data — GNSS/RTK integration, offline-first architecture, geospatial data pipelines, custom map layers, QGIS compatibility AI & ML — LLM integration, computer vision, NLP, on-device inference with Core ML and TensorFlow Lite, OpenAI and custom model pipelines, TTS/STT Connectivity — BLE pairing flows, LoRa, IoT sensor integration, background sync, beacon tracking On AI tools: senior engineers using them deliberately, not as a substitute for judgment. Faster delivery, no technical debt traded for speed. Good fit if you: — Need someone who operates independently without hand-holding — Are building something with real operational complexity — Have been burned by teams that shipped demos and called it done Tell me what you're building, send a message

Most computer vision projects fail not in training — but in deployment. Models that hit 95% accuracy in the lab break down when lighting shifts, hardware stutters, or the camera feed isn't clean. I build systems engineered to survive those conditions — and I've done it across industries, hardware platforms, and deployment environments. I'm a Computer Vision Engineer specializing in end-to-end AI pipelines — from raw camera input to real-time inference, deployed on edge hardware, cloud APIs, or both. ━━ Core services ━━ → Object detection & multi-object tracking — YOLOv8, YOLOv5, ByteTrack, BOTSort, MMDetection → Segmentation, pose estimation & keypoints — MediaPipe, custom model architectures → Edge AI deployment — NVIDIA Jetson Orin/Nano, Raspberry Pi, Hailo — TensorRT, ONNX, INT8/FP16 → Cloud & API deployment — FastAPI, Docker, AWS GPU instances, REST & WebSocket inference APIs → Video analytics & smart camera systems — safety monitoring, defect detection, zone tracking, people counting ━━ Systems I've shipped ━━ ✓ Real-time fall detection on NVIDIA Jetson — production-deployed, sub-100ms latency ✓ Zone-based people tracking & monitoring for safety-critical environments ✓ Industrial defect detection pipeline — TensorRT-optimized, running on constrained edge hardware ✓ End-to-end smart camera system: camera → inference → dashboard & real-time alerts ✓ OpenCV video analytics pipelines with custom pre/post-processing and business logic ━━ What makes my work different ━━ Most CV engineers deliver a model file. I deliver a working system — optimized, integrated, and running reliably in your environment. I lead a small team and personally own system architecture, optimization strategy, and core AI engineering on every project. You get senior-level technical execution, not delegation to juniors. Edge or cloud. Jetson or GPU server. Prototype or production scale. I've built across all of it. ━━ How a typical project runs ━━ 1. Discovery — review your hardware targets, data sources, and latency requirements before any code is written 2. Architecture — design the full pipeline: model selection, optimization path, deployment stack, integration points 3. Build & optimize — iterative development with benchmarked FPS and accuracy metrics at each stage 4. Deployment — containerized, documented, and running on your target environment 5. Handover — clean codebase, inline documentation, and a session so your team can maintain it independently ━━ Full tech stack ━━ Models: YOLOv8, YOLOv5, YOLOv7, MMDetection, Detectron2, PyTorch, TensorFlow, ONNX Runtime Tracking: ByteTrack, BOTSort, DeepSORT, StrongSORT, custom zone logic & counting algorithms Optimization: TensorRT INT8/FP16, ONNX quantization, model pruning, batch inference tuning Edge hardware: NVIDIA Jetson Orin/Nano, Raspberry Pi 4/5, Hailo-8, Coral TPU Cloud & infra: FastAPI, Flask, Docker, AWS EC2/Lambda, GCP, RTSP/RTMP stream processing Vision utilities: OpenCV, FFmpeg, GStreamer, PIL/Pillow, custom pipeline components ━━ Project types I take on ━━ → Greenfield CV systems — full pipeline from scratch to production deployment → Model optimization — take an existing model and make it production-fast on your hardware → Edge porting — migrate a cloud-based CV system to Jetson, Raspberry Pi, or Hailo → Pipeline debugging — diagnose and fix latency, accuracy, or stability issues in live systems → Inference API — wrap your CV model as a scalable, low-latency REST or WebSocket API → PoC → production — take a working demo and harden it for real-world deployment at scale → Team augmentation — embedded senior CV engineer for sprints or longer-term engagements ━━ Industries served ━━ Manufacturing & quality control — defect detection, visual inspection, production line monitoring Safety & security — real-time threat detection, perimeter monitoring, crowd analytics Retail & logistics — shelf analytics, people counting, queue management, warehouse tracking Healthcare — patient monitoring support systems, lab automation, medical imaging pipelines Agriculture — crop health detection, drone-based aerial inspection, field monitoring systems ━━ Common questions ━━ Work with our existing dataset? Yes — I assess quality, recommend augmentation strategies, and fine-tune models on your labeled data. Edge or cloud deployment? Both — Jetson, Raspberry Pi, and Hailo at the edge; AWS GPU instances and containerized APIs in the cloud. Can you take our prototype to production? That's one of my most common engagements — hardening, optimizing, and deploying existing concepts for real-world reliability. Documentation and handover included? Always. Clean code, inline comments, deployment instructions, and a dedicated handover session on every project. If you need computer vision that performs beyond lab conditions — on real hardware, with real data, in real-world environments — let's talk.

React Native + Expo developer who takes apps from an empty repo to live on the App Store and Google Play. Five years in, usually the only mobile engineer, shipping AI, health, and marketplace apps and rescuing the ones that crash, lag, or get rejected Some of what I've shipped: Fitra360: an AI wellness platform that analyzes DNA, bloodwork, symptoms, and lifestyle data to generate personalized health and routine plans. FIXA: a car services and AI diagnostics app with camera-based tire scanning and Elasticsearch-powered search, in production. Gayar: Kuwait's first car parts marketplace. Three years in production with full ad-platform integration (TikTok, Snap, Meta, Google) and deep-linked campaigns. Other production work spans health insurance telemedicine, Saudi enterprise ERP (POS, inventory, geofenced HR attendance), university apps with campus security systems, and AI-assisted real estate platforms. The work tends to land in two buckets. New builds: production React Native + Expo apps from MVP through enterprise scale. AI features like health analysis, in-app assistants, image recognition, and smart recommendations. Healthcare and telemedicine platforms with video consultations, secure data, and prescriptions. Marketplaces and e-commerce apps with deep linking and full event tracking. Enterprise ERP, POS, inventory, and HR systems. Supabase, Firebase, and GraphQL backends (auth, RLS, realtime, edge functions, storage). Pixel-perfect UI from Figma, REST and GraphQL APIs, push notifications, in-app purchases, geolocation, maps, geofencing, deep linking. App Store and Google Play submissions end-to-end, including rejection appeals. Rescues: crashes, white screens, broken navigation. Performance issues like slow lists, laggy animations, high memory, slow cold start. Auth and session problems (Supabase, Firebase, OAuth, expo-auth-session). App Store and Play Store rejections. TestFlight build and distribution issues. Send a quick description, a Loom, or an error log. I'll come back with a clear plan, a realistic timeline, and what it'll actually take.

I turn complex products and ideas into immersive, interactive 3D experiences — whether that's a WebAR try-on that runs directly in the browser, a real-time 3D product configurator that cuts return rates, or a VR training simulation that replaces costly in-person sessions. With a background spanning native AR, WebAR, interactive web experiences, and VR, I sit at the intersection where technology meets measurable business outcomes — more conversions, deeper engagement, and fewer abandoned carts. 🎯 What I Build: 𝐖𝐞𝐛𝐀𝐑 & 𝐍𝐚𝐭𝐢𝐯𝐞 𝐀𝐑— App-free augmented reality via 8th Wall, WebXR, and A-Frame, or production-grade native apps built on Unity AR Foundation with full ARCore and ARKit support. Face tracking, image tracking, SLAM world tracking, virtual try-on (VTO), and geo-based AR — all optimized for real mobile hardware. 𝐈𝐧𝐭𝐞𝐫𝐚𝐜𝐭𝐢𝐯𝐞 𝟑𝐃 𝐖𝐞𝐛 𝐄𝐱𝐩𝐞𝐫𝐢𝐞𝐧𝐜𝐞𝐬 — High-performance product visualizers, 3D configurators, and immersive landing pages using Three.js, React Three Fiber, Babylon.js, and WebGL. Customers interact with your product in real time — rotating, customizing colors, swapping materials — before they ever hit "add to cart." 𝐕𝐑 𝐄𝐱𝐩𝐞𝐫𝐢𝐞𝐧𝐜𝐞𝐬 — Training simulations, virtual showrooms, architectural walkthroughs, and branded VR environments for Meta Quest, PC VR, and WebVR using Unity and WebXR. Ideal for enterprise training, real estate, and education. 𝟑𝐃 𝐀𝐬𝐬𝐞𝐭 𝐏𝐢𝐩𝐞𝐥𝐢𝐧𝐞 — Optimized, web-ready 3D models via Blender and Maya, glTF/GLB pipeline, PBR materials, Draco compression, and GLSL/HLSL shaders — ensuring your experience loads fast and looks stunning across device tiers. 🛠 Core Tech Stack: WebAR: 8th Wall (Niantic Lightship), A-Frame, Three.js, Babylon.js, React Three Fiber, WebXR Device API, Zappar, Banuba Web SDK Native AR: Unity AR Foundation, ARKit (iOS), ARCore (Android), LiDAR integration, XR Interaction Toolkit Interactive 3D Web: Three.js, WebGL, GLSL Shaders, React Three Fiber, GSAP, Draco compression, glTF/GLB VR: Unity, Meta Quest SDK, OpenXR, WebXR 3D Art Pipeline: Blender, Maya, Substance Painter, PBR materials, real-time occlusion, HDR lighting Backend & Cloud: Firebase, REST APIs, AWS S3, Niantic VPS, Mixpanel, Firebase Analytics 💼 Use Cases I Specialize In: E-commerce & Retail — View-in-room furniture placement, virtual try-on for eyewear, jewelry, footwear and cosmetics, real-time 3D product configurators with color and material swapping Interactive Marketing — Scan-to-launch brand activations, AR product packaging, shareable social face filters, gamified brand experiences Architecture & Real Estate — On-site BIM/CAD visualization at 1:1 scale, virtual property walkthroughs for off-plan developments Enterprise Training & Education — Step-by-step AR maintenance overlays, VR simulations replacing costly in-person training Beauty & Cosmetics — Real-time foundation shade matching, lipstick and eyeshadow try-ons using facial color analysis Events & Entertainment — Stadium fan engagement, AR scavenger hunts, live venue navigation overlays 📦 What You Get Working With Me: ✅ A technical scoping document before a single line of code is written ✅ Regular build deliverables with video walkthroughs — no black-box development ✅ Fully documented, commented source code handed off at project close ✅ Performance reports covering polygon counts, draw calls, load times, and device compatibility ✅ Post-launch support and A/B testing guidance to measure real impact 𝐓𝐨𝐩 𝐑𝐚𝐭𝐞𝐝 · 𝟏𝟎𝟎% 𝐉𝐨𝐛 𝐒𝐮𝐜𝐜𝐞𝐬𝐬 · 𝐀𝐯𝐚𝐢𝐥𝐚𝐛𝐥𝐞 𝐍𝐨𝐰 Let's talk about your project — click Invite or Contact and I'll respond within a few hours.

Most machine learning projects fail between the prototype and production. I've shipped 54+ that didn't. 🎯 YOLO Detection | 🧍 Pose Estimation | 🏋️ Sports AI | 🛒 Retail AI | 🛡️ CCTV Analytics | 🔄 Tracking | 🧠 ML Pipelines | 🤖 AI Agents | 💬 LLM Integration You have a working concept — or a clear problem involving cameras, video, or image data. The challenge is making it fast, accurate, and stable under real-world conditions. Wrong framework choices. Inference too slow for live video. Models that break the moment lighting, angle, or environment changes. And systems that detect things but can't reason about them or act on them autonomously. That's exactly where most builds stall. I design and build real-time computer vision pipelines that go all the way — from model training to live deployment — and increasingly, from visual perception to autonomous AI agents that understand, decide, and narrate. Object detection · Machine learning · Pose estimation · Multi-camera tracking · Segmentation · Re-identification · Anomaly detection · OCR & ANPR · Optical flow · Depth estimation · LLM-powered reasoning · Agentic decision pipelines While most CV engineers stop at training the model, I go further: → Accelerated inference with TensorRT, ONNX, OpenVINO, and FP16/INT8 quantization (up to 5× faster) → LLM agents layered over CV pipelines for real-time decisions, alerts, and natural language outputs → Mobile deployment via CoreML (iOS) and TFLite (Android) with 10+ live apps shipped → Edge deployment on Jetson, OpenVINO, Apple Neural Engine, and CUDA/cuDNN → End-to-end pipeline: camera input → training → optimization → real-time actionable output Key Accomplishments: ⭐ Generated $5M+ in client revenue ⭐ Delivered 100+ end-to-end computer vision systems ⭐ Successfully launched my own 2 SaaS products ⭐ Real-time sports AI for 7+ sports, improving analytics for 15+ teams ⭐ Mobile AI on iOS (Core ML) & Android (TFLite), powering 10+ apps ⭐ Surveillance, safety, and industrial AI solutions ⭐ Medical imaging AI for 5+ hospitals: tumor detection, ultrasound, test strips ⭐ Model optimization: up to 5× faster inference using FP16/INT8, ONNX, TensorRT, OpenVINO ⭐ Multi-object tracking, re-identification, Model Training 1M+ labelled Dataset ⭐ Agentic CV systems that perceive, reason, and act without human input in the loop If you have read this far, please note that I appreciate you taking the time to learn about me. Personally, it’s been an amazing journey and knowledge exercise to get to this level of competence in AI and software development. Domain Expertise: - Sports & Fitness: athlete tracking, shot detection, scoring automation, drill analysis, pose estimation - Industrial & Workplace: tire defect inspection, PPE compliance, staff monitoring, meter reading, machine vision inspection, automated quality control - Surveillance & Security: ANPR, crowd monitoring, people counting, animal attack detection, exam cheating detection, perimeter security, intrusion detection - Healthcare & Medical: tumor detection, ultrasound processing, test strip analysis, X-ray/CT scan processing, lesion segmentation, medical image annotation - Traffic & Transport: aerial monitoring, traffic flow AI, license plate recognition, vehicle detection, accident detection, parking management - Retail & Business: customer analytics, receipt extraction, retail intelligence, object recognition, shelf monitoring, inventory management Tech Stack: Machine Learning, Deep Learning, YOLOv5, YOLOv8 - YOLO26, Detectron2, DeepSORT, StrongSORT, MMDetection, MediaPipe, OpenPose, PoseTrack, Action Recognition, Semantic Segmentation, Instance Segmentation, OCR, Anomaly Detection, Motion Detection, Object Counting, License Plate Recognition, PyTorch, TensorFlow, TensorFlow Lite, Keras, OpenCV, FastAPI, Flask, Core ML, TFLite, ONNX, TensorRT, OpenVINO, CUDA, Swift, Kotlin, Flutter, Python, C++, AWS, GCP, Azure, Edge Deployment, Mobile AI, Real-Time Inference, Surveillance AI, Aerial Drone Analytics, Video Stream Analytics, AI Automation, LLM Integration (GPT-4o, Claude, Gemini, Groq), AI Agent Frameworks (LangChain, LangGraph, CrewAI), RAG Pipelines, Streaming LLM Inference license plate recognition, aerial drone analytics, surveillance AI, mobile AI, embedded systems, deep learning pipelines, inference optimization, video stream analytics, AI automation, AI for industry 4.0, computer vision pipelines. If your project involves cameras, video, or images — and you need it fast, accurate, fully deployed, and intelligent enough to reason and act autonomously — I am the engineer you are looking for.