Hire the Best Taxonomy Specialists
in Pakistan

Imagine spending thousands of dollars training an AI model—only to realize the labels were flawed. That’s where I come in. I’m 𝐁𝐞𝐡𝐳𝐚𝐝 𝐀𝐥𝐢 𝐊𝐡𝐚𝐧 and Founder of 𝐒𝐖𝐀𝐓𝐀𝐢, a data annotation and AI development platform trusted by AI startups and enterprises worldwide. With 4+ years of experience and a team of 178+ skilled annotators, I’ve personally led projects that helped train over 100 production-grade AI models from medical image segmentation, agriculture dataset annotations, AI-based electric poles condition monitoring system to autonomous vehicle perception systems. 🌐𝗪𝗵𝘆 𝗖𝗹𝗶𝗲𝗻𝘁𝘀 𝗧𝗿𝘂𝘀𝘁 𝗠𝗲: 𝗣𝗿𝗲𝗰𝗶𝘀𝗶𝗼𝗻-𝗟𝗲𝘃𝗲𝗹 𝗦𝗲𝗴𝗺𝗲𝗻𝘁𝗮𝘁𝗶𝗼𝗻: I specialize in polygonal, pixel-wise and semantic segmentation with an obsessive attention to detail. 𝗔𝗜-𝗔𝘄𝗮𝗿𝗲 𝗔𝗻𝗻𝗼𝘁𝗮𝘁𝗶𝗼𝗻: Unlike generic labelers, I understand the AI pipeline. I don’t just label, I label for performance. Every dataset is annotated with model training, accuracy and edge-case handling in mind. 𝗘𝗻𝘁𝗲𝗿𝗽𝗿𝗶𝘀𝗲-𝗦𝗰𝗮𝗹𝗲 𝗢𝗽𝗲𝗿𝗮𝘁𝗶𝗼𝗻𝘀: Delivered $500,000+ worth of labeled data to top AI companies (like Moonvalley, SaharLabs etc) with proven systems for scalability, security and deadlines. 𝗖𝘂𝘀𝘁𝗼𝗺 𝗧𝗼𝗼𝗹𝘀, 𝗥𝗲𝗮𝗹 𝗜𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗶𝗼𝗻: Worked across CVAT, Labelbox, SuperAnnotate, Roboflow and even client-specific proprietary tools. 🌐𝗦𝘁𝗼𝗿𝘆 𝗼𝗳 𝗚𝗿𝗼𝘄𝘁𝗵: What began as a solo freelancing gig on Fiverr has now become a global agency delivering AI-ready data for some of the most innovative companies on Earth. Now offering our services on Upwork as well. 🛠️𝗦𝗲𝗿𝘃𝗶𝗰𝗲𝘀 𝗜 𝗢𝗳𝗳𝗲𝗿: ✦ Image & Video Segmentation (polygon, semantic, instance-based) ✦ Bounding Box, Keypoint & Landmark Annotation ✦ Text & Audio Annotation (multilingual available) ✦ Dataset Cleaning, Structuring & Preprocessing ✦ Consultancy on AI Dataset Design and Labeling Strategies ✦ AI Model Training and development Image annotation, Bounding boxes, 3D boxes, Video annotation, instance and semantic, Object labeling/tagging,Segmentation, Polygons masks, Text annotation, Line annotation, Key Points annotation, Cuboids, Image classification and categorization.

Your model is only as smart as the person labeling its data! Bad training data is the #1 reason ML projects miss the accuracy targets. Mislabeled frames and skipped edge cases compound into models that fail on real-world inputs. I am Iqra and I treat your annotation guidelines as a contract. My passion for AI is reflected in my role as a Data Annotation Specialist with hands-on CVAT experience labeling images and video for computer vision models. I deliver pixel-accurate bounding boxes, polygons, and segmentation masks that train production-ready AI not "good enough" data that breaks your model in deployment. ✅ WHAT I ANNOTATE IMAGE ANNOTATION — Bounding boxes, polygons & polylines — Semantic & instance segmentation — Object detection & classification labeling — Landmark & keypoint annotation — Image tagging and categorization TEXT ANNOTATION — Named entity recognition (NER) — Sentiment analysis & intent labeling — Text classification & topic tagging AUDIO & VIDEO ANNOTATION — Transcription and speaker diarization — Audio event tagging & classification — Subtitle alignment and timestampin ✅ Tools I work with daily: CVAT • LabelBox • Label Studio • Roboflow • SuperAnnotate • V7 Labs • Amazon SageMaker Ground Truth • Encord ✅Who I work best with: — ML/AI startups building computer vision or NLP products — Companies running ongoing annotation pipelines who need a reliable long-term labeler — Teams doing RLHF or LLM evaluation work ✅How I work: — I start every project by reviewing your guidelines and annotating a small test batch (20-50 items) so you can verify quality before scaling — I document edge cases as I find them and ask clarifying questions in batches — not one-by-one interruptions → I deliver in your preferred format with a short QA summary noting any uncertain labels for your review — I'm available 30+ hours/week and respond to messages within a few hours during my workday. ✅What you actually get when you hire me: — 98%+ annotation accuracy verified through QA review cycles — Edge cases flagged and discussed — not silently guessed at — Consistent labeling logic across large datasets — Fast turnaround on bulk work without quality drop-off in the last 10% Send me your annotation guidelines and a sample batch — I'll return a labeled test set within 24 hours so you can verify accuracy before committing to a larger contract. Looking forward to helping you build training data your model can actually learn from. Iqra Akram

Building High-Quality AI Datasets requires more than just drawing boxes. It requires consistency, strong QA processes, attention to detail & an understanding of how Annotated Data impacts Machine Learning models in production. With 𝟴+ 𝘆𝗲𝗮𝗿𝘀 of experience in Data Annotation, Computer Vision, AI Training Data & Dataset QA, I help AI startups, Enterprise teams & Computer Vision Companies build accurate, scalable & production-ready datasets for Machine Learning workflows. I also previously worked as a 𝗖𝗼𝗺𝗽𝘂𝘁𝗲𝗿 𝗩𝗶𝘀𝗶𝗼𝗻 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿, which gives me a strong understanding of how Annotation quality directly affects Object Detection, Segmentation, Tracking, OCR systems, Autonomous Driving pipelines & overall AI model performance. Currently, I am working as a Senior 𝗗𝗮𝘁𝗮 𝗔𝗻𝗻𝗼𝘁𝗮𝘁𝗼𝗿 at Motive (formerly KeepTruckin), where I handle large-scale AI datasets and annotate approximately 3000–5000 videos weekly, totaling nearly 300GB of data every week. Over the years, I have contributed to annotating more than 𝟭 𝗠𝗶𝗹𝗹𝗶𝗼𝗻 𝘃𝗶𝗱𝗲𝗼𝘀 & 𝟱𝟬𝟬𝗞+ 𝗶𝗺𝗮𝗴𝗲𝘀 across multiple Enterprise & AI-focused projects. I have also worked with Enterprise companies, including Adobe & multiple AI startups, maintaining Annotation accuracy between 97%–99.5% depending on project complexity. I am available Full-time for Long-term projects, AI Training Workflows, Dataset Creation, QA Review, Team Supervision & Enterprise Annotation Operations. ━━━━━━━━━━━━━━━━━━ WHAT I CAN HELP YOU WITH ━━━━━━━━━━━━━━━━━━ • Image Annotation • Video Annotation • Data Labeling & Tagging • Object Detection & Tracking • Bounding Boxes • Polygon & Polyline Annotation • Semantic & Instance Segmentation • Keypoint Annotation • OCR Annotation • Medical Image Annotation • Satellite & Drone Image Annotation • NLP & Text Annotation • Prompt Evaluation & AI Response Rating • Speech & Audio Annotation • Dataset QA & Validation • AI Training Dataset Preparation • Team Supervision & QA Review ━━━━━━━━━━━━━━━━━━ COMPUTER VISION & AUTONOMOUS DRIVING EXPERIENCE ━━━━━━━━━━━━━━━━━━ I have extensive experience Annotating Autonomous driving and fleet safety datasets including: • Cars, SUVs, Pickup Trucks & Semi Trucks • Motorcycles & Bicycles • Pedestrians • Traffic Lights & Traffic Signs • Lane Lines & Road Boundaries • Crosswalks & Parking Spaces • Construction Zones & Barriers • License Plates • Dashcam & Fleet Safety Videos • Highway & Urban Driving Scenes • Driver Monitoring & Accident Detection ━━━━━━━━━━━━━━━━━━ TOOLS & PLATFORMS ━━━━━━━━━━━━━━━━━━ • CVAT • Roboflow • Labelbox • Label Studio • SuperAnnotate • LabelImg • LabelMe • Amazon SageMaker Ground Truth I can quickly adapt to Custom Annotation platforms & project workflows. ━━━━━━━━━━━━━━━━━━ FORMATS & ML UNDERSTANDING ━━━━━━━━━━━━━━━━━━ Supported formats include: • YOLO • COCO JSON • Pascal VOC XML • KITTI • CSV / JSON / TXT • TFRecord • PNG Masks • Semantic & Polygon Masks Because of my Computer Vision background, I also understand: • YOLOv5 • Detectron2 • VGG16 / VGG19 • Object Detection Pipelines • Segmentation Workflows • OCR Systems • AI Training Requirements • Dataset Quality Optimization This allows me to create Annotations that are not only visually accurate but also optimized for machine learning performance. ━━━━━━━━━━━━━━━━━━ QA & TEAM MANAGEMENT EXPERIENCE ━━━━━━━━━━━━━━━━━━ I have managed teams of up to 20 Annotators and worked as: • QA Reviewer • Team Lead • Project Coordinator • Annotation Supervisor My responsibilities included: • SOP Creation • Annotation Guidelines • Quality Assurance Workflows • Productivity Tracking • Team Mentoring • Client Communication • Task Allocation • Final Dataset Review ━━━━━━━━━━━━━━━━━━ WHY CLIENTS WORK WITH ME LONG-TERM ━━━━━━━━━━━━━━━━━━ • Strong QA-focused mindset • Enterprise-level Annotation Experience • High Accuracy & Consistency • Ability to handle High-Volume Datasets • Fast turnaround without compromising quality • Reliable Communication & Reporting • Full-time Availability • Long-term commitment to projects One of my strongest qualities is maintaining quality under pressure. During a high-priority project, I completed a critical delivery within 30 hours continuously while maintaining accuracy and QA standards. ━━━━━━━━━━━━━━━━━━ UPWORK HIGHLIGHTS ━━━━━━━━━━━━━━━━━━ • Top Rated Freelancer • 100% Job Success Score • Top 10% Talent on Upwork • Enterprise & Long-Term Project Experience • Available 40–45 Hours/Week • Flexible with US, UK & Australian time zones • NDA Friendly If you are looking for a reliable AI Data Annotation Specialist who understands both annotation quality and AI model requirements, feel free to invite me to your project. I am open to long-term collaborations, Enterprise Annotation Projects, AI Training Data Operations, QA Review Roles, and High-Volume Computer Vision Datasets. Let’s build High-Quality AI Datasets together.

Stop wasting your ML budget on noisy data. I deliver pixel-perfect semantic segmentation and high-fidelity data annotation using CVAT and Labelbox. Training a model on average data labeling fails at deployment. As an AI Data Annotation Lead, I specialize in production-ready data annotation and data labeling services that eliminate edge-case errors and accelerate your model's time-to-market. With a 5.0/5 star track record, I provide high-precision semantic segmentation, instance segmentation, and object detection for demanding industries including autonomous driving (LiDAR), healthcare (DICOM), and AgTech. Why top AI teams hire me for data annotation: * Mastery of CVAT, Labelbox, Roboflow, and Label Studio for complex polygon and mask workflows * Zero-defect quality control with inter-annotator agreement (IAA) checks for 99%+ accuracy in every data labeling batch * Expert-level handling of 3D LiDAR point clouds, 3D cuboids, and medical imaging (MRI/CT/X-Ray) * Experienced in RLHF for fine-tuning vision-language models Technical specializations in data annotation: * Semantic segmentation and instance segmentation using polygons, brushes, and Mask R-CNN * 3D point cloud and LiDAR cuboid tracking for ADAS * Object detection with high-speed bounding boxes for real-time tracking * High-volume data labeling for computer vision models Formats I deliver for every object detection and segmentation project: YOLO (v8-v11), COCO JSON, Pascal VOC, XML, and CSV. Industry experience with data annotation: * Automotive: Lane detection, pedestrian intent, autonomous vehicle training using semantic segmentation * Medical AI: Data labeling for MRI/CT scans with HIPAA-aware workflows * Agriculture: Aerial mapping and crop health analysis using instance segmentation I am reliable, detail-oriented, and ready to scale. Whether you need a pilot batch or a large-scale data annotation project, I ensure your data labeling is the strongest part of your pipeline. Click "Message" to discuss your semantic segmentation, object detection, CVAT or data annotation project

Hi, I specialize in delivering professional data annotation, data labeling, data tagging, data collection, and data enrichment services to support Artificial Intelligence and Machine Learning models. I also provide data cleaning, dataset merging, and customization based on your specific project requirements. ✅ Tools I Work With: LabelImg LabelMe VGG Image Annotator (VIA) Amazon Sagemaker CVAT Labelbox Fiji App Makesense Supervisely Label Studio Roboflow Adobe Premiere Pro And more... 📌 Types of Data I Annotate: Images Videos Text 🧷 Annotation Types: Bounding Boxes Polygons Polylines Dots / Keypoints 📁 Output Formats: Pascal VOC (XML) COCO (JSON) YOLO (TXT) CSV Or any custom format as per client requirements 🔐 100% Data Security and Client Privacy Guaranteed 🤖 Data Processing for AI and ML Applications

Imagine spending thousands of dollars training an AI model—only to realize the labels were flawed. That’s where I come in. I’m 𝗠𝗮𝘇𝗵𝗮𝗿 𝗨𝗱 𝗗𝗶𝗻, the founder of 𝗔𝗡𝗡𝗢𝗣𝗘𝗧𝗧, a data annotation and AI development agency trusted by AI startups and enterprises worldwide. With 4+ years of experience and a team of 178+ skilled annotators, I’ve personally led projects that helped train over 100 production-grade AI models—from medical image segmentation, agriculture dataset annotations, AI-based electric poles condition monitoring system to autonomous vehicle perception systems. 🌐𝗪𝗵𝘆 𝗖𝗹𝗶𝗲𝗻𝘁𝘀 𝗧𝗿𝘂𝘀𝘁 𝗠𝗲: 𝗣𝗿𝗲𝗰𝗶𝘀𝗶𝗼𝗻-𝗟𝗲𝘃𝗲𝗹 𝗦𝗲𝗴𝗺𝗲𝗻𝘁𝗮𝘁𝗶𝗼𝗻: I specialize in polygonal, pixel-wise, and semantic segmentation with an obsessive attention to detail. 𝗔𝗜-𝗔𝘄𝗮𝗿𝗲 𝗔𝗻𝗻𝗼𝘁𝗮𝘁𝗶𝗼𝗻: Unlike generic labelers, I understand the AI pipeline. I don’t just label—I label for performance. Every dataset is annotated with model training, accuracy, and edge-case handling in mind. 𝗘𝗻𝘁𝗲𝗿𝗽𝗿𝗶𝘀𝗲-𝗦𝗰𝗮𝗹𝗲 𝗢𝗽𝗲𝗿𝗮𝘁𝗶𝗼𝗻𝘀: Delivered $500,000+ worth of labeled data to top AI companies (like Moonvalley, SaharLabs etc) with proven systems for scalability, security, and deadlines. 𝗖𝘂𝘀𝘁𝗼𝗺 𝗧𝗼𝗼𝗹𝘀, 𝗥𝗲𝗮𝗹 𝗜𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗶𝗼𝗻: Worked across CVAT, Labelbox, SuperAnnotate, Roboflow, and even client-specific proprietary tools. 🌐𝗦𝘁𝗼𝗿𝘆 𝗼𝗳 𝗚𝗿𝗼𝘄𝘁𝗵: What began as a solo freelancing gig on Fiverr has now become a global agency delivering AI-ready data for some of the most innovative companies on Earth. Now offering our services on Upwork as well. 🛠️𝗦𝗲𝗿𝘃𝗶𝗰𝗲𝘀 𝗜 𝗢𝗳𝗳𝗲𝗿: ✦ Image & Video Segmentation (polygon, semantic, instance-based) ✦ Bounding Box, Keypoint & Landmark Annotation ✦ Text & Audio Annotation (multilingual available) ✦ Dataset Cleaning, Structuring & Preprocessing ✦ Consultancy on AI Dataset Design and Labeling Strategies ✦ AI Model Training and development Image annotation, Bounding boxes, 3D boxes, Video annotation, instance and semantic, Object labeling/tagging,Segmentation, Polygons masks, Text annotation, Line annotation, Key Points annotation, Cuboids, Image classification and categorization.