Hire the Best OCR Algorithms Specialists

I help businesses stop wasting hours on manual document processing by building Python, OCR, AI, and automation systems that convert messy documents into clean, structured, usable data. 🚀 My work is not just “OCR” or simple copy-paste automation. I build practical tools, Python scripts, REST APIs, and MVP workflows that can extract data from PDFs, scanned documents, invoices, receipts, purchase orders, bank statements, forms, reports, and images — then clean, validate, review, and export the results into Excel, CSV, JSON, Google Sheets, databases, or API-ready formats. ⚙️ What I can help you build: ✅ Python scripts for PDF, OCR, image, and data extraction automation ✅ PDF to Excel / CSV / JSON conversion workflows ✅ OCR pipelines using Google Vision OCR, Tesseract, OpenCV, PyMuPDF, and AI models ✅ Invoice, receipt, purchase order, bank statement, and form parsing systems ✅ REST APIs for document upload, processing, extraction, and export ✅ MVP tools for document processing platforms and internal business automation ✅ Human-in-the-loop review systems to improve accuracy before final export ✅ Excel automation, data cleaning, matching, validation, and reporting ✅ Google Sheets automation and structured data workflows ✅ Web scraping and API-based data collection when needed ✅ Custom automation tools that replace repetitive manual work 🧠 My main advantage: I combine strong manual data extraction experience with real Python automation skills. That means I understand both sides of the problem: 1. The accuracy needed when dealing with messy, real-world documents 2. The technical automation needed to process files faster and more reliably at scale I have worked on OCR and document automation projects involving scanned PDFs, financial documents, purchase orders, invoices, receipts, bank statements, forms, Google Drive OCR pipelines, Excel automation, structured data conversion, and AI-assisted document parsing. I also build review workflows where uncertain values are flagged for human review instead of blindly exporting incorrect data. This is especially useful for businesses that need high accuracy, auditability, and clean final outputs. 💡 Example workflows I can build: A user uploads PDFs or scanned images → the backend extracts the required fields → low-confidence or unclear values are sent to a review screen → the final approved data is exported to Excel, CSV, JSON, Google Sheets, or sent through a REST API. Another example: A business receives invoices, POs, or reports every day → a Python automation processes the files → extracts key fields and line items → validates the data → highlights missing or uncertain values → generates a clean Excel report ready for use. I care about building solutions that are practical, accurate, and useful in real daily work — not just scripts that work on one perfect sample file. If you have sample files, send me 1–3 examples and I can review the structure, suggest the best workflow, and explain the expected accuracy, cost, and implementation approach.

I am not just an AI Engineer; I am a storyteller who connects the dots between complex data and business growth. With 5 years of hands-on experience and a robust academic foundation in Statistics and Engineering, I specialize in building AI systems that don't just work they innovate. Why work with me? I don’t just deliver code; I translate your high-level business needs into high-performing, production-ready AI systems that solve real-world bottlenecks. My Core Expertise: - AI Solutions: Text analysis & image recognition - AI Search: Smarter answers with RAG & advanced prompt design - Custom AI Models: Tailored GPT, Gemini, LLaMA, Claude & more - Vibe Coding: Cursor, Lovable, Antigravity, etc.. - AI Workflows: Multi-agent automation for complex tasks - Voice AI: Text-to-speech & speech-to-text (AWS, Google, Azure) - AI Visuals: From idea to image using DALL·E, Midjourney, Stable Diffusion - Automation: Zapier, Make, n8n & custom workflows - Smart Pipelines: Event-driven triggers, error handling & smooth operations AI Agents & Chatbots: I build sophisticated multi-agent and RAG frameworks. Examples include E-commerce virtual associates that drive sales and POS customer support agents that handle complex queries autonomously. Text-to-SQL & Analytics: I enable non-technical users to "talk to their data," providing instant, natural-language insights into sales, inventory, and KPIs. Intelligent Automation (n8n): I streamline operations by eliminating repetitive tasks. My AI-powered HR Agent workflow automatically parses, scores, and ranks candidates to find your "best fit" instantly. Computer Vision & OCR: Expert in YOLO and Qwen2.5-VL. I automate data entry from handwritten or digital invoices directly into structured JSON for accounting and inventory software. Full-Stack AI Deployment: I take models from notebooks to production. Expert in the full AI lifecycle, including MLOps, containerization (Docker), and scalable cloud deployment on GCP. The Toolbox: Frameworks: PyTorch, Keras, TensorFlow, Scikit-learn, OpenCV. LLM Ops & Orchestration: LangChain, LangFlow, DSPy, OpenAI API, Apple MLX. Deployment: Docker, GCP, MLOps pipelines. I am dedicated to delivering results that exceed expectations always on time and within budget. Let’s build your success story. Click the 'Invite' button to start a conversation!

🔹 Top Rated Machine Learning Engineer | Expert in Detection, Tracking, Classification & OCR I specialize in building high-accuracy computer vision models — from object detection and classification to keypoint detection and OCR. With deep experience in YOLO (v8–v11), TensorFlow, and PyTorch, I’ve delivered results across industries including healthcare, logistics, and agriculture. 🚀 Highlighted Projects: 🔍 License Plate Recognition & Number Swapping — for Korean and Kazakh vehicles 🏥 COVID-19 & Viral Pneumonia Detection — 95%+ accuracy using X-ray images 🍎 Fruit Detection (Apple, Peach, Potato) — precision object detection with YOLO 📄 OCR & Keypoint Detection — paper/card ID localization and tracking 🏎️ Speed Estimation & Vehicle Tracking — model fusion using YOLO + Deep SORT ⚙️ Core Skills & Tools: YOLOv5/v8 | TensorFlow | PyTorch | OpenCV | ONNX Object Detection, Classification, OCR, Keypoint Detection High-speed model training on RTX 4080 Super As a Top Rated freelancer, I deliver clean, efficient, and production-ready models on time and with clear communication. Let’s bring your vision to life. 📩 Message me — I respond quickly and build fast.

Most Machine Vision projects fail between the prototype and production. I've shipped 54+ that didn't. ⚙️YOLO Detection | Pose Estimation | Object Tracking | AI Agents | LLM Integration Sports & Fitness AI | CCTV & Surveillance AI | Retail AI | Healthcare AI 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. LLM APIs (OpenAI, GPT-4o, Gemini, Claude) | AWS (EC2, S3, Lambda) | Azure Cloud Services | MLOps & API Integration | Model Deployment & Scaling While most CV engineers stop at training the model, I go further: → High-speed inference optimization using TensorRT, ONNX, OpenVINO, FP16/INT8 (up to 5× faster) → LLM agents integrated with vision pipelines for alerts, reasoning, and automation → Mobile AI deployment using Core ML (iOS) and TFLite (Android) with 10+ shipped apps → Edge AI deployment on Jetson, OpenVINO, CUDA, and embedded systems → End-to-end pipelines: data → training → optimization → real-time deployment Key Accomplishments: ⭐ $5M+ revenue from AI solutions ⭐ 100+ computer vision systems delivered ⭐ Built and launched 2 SaaS products ⭐ Real-time sports AI (7+ sports, 15+ teams) ⭐ 10+ mobile AI apps (iOS Core ML, Android TFLite) ⭐ Production AI for surveillance, industrial & safety use cases ⭐ Medical imaging AI deployed in 5+ hospitals ⭐ Up to 5× faster inference (ONNX, TensorRT, FP16/INT8) ⭐ Large-scale tracking & re-ID (1M+ labeled data) ⭐ Agentic AI systems for autonomous decision-making 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: ✅ athlete tracking | shot detection | scoring | drill analysis | pose estimation ✅ defect inspection | PPE compliance | staff monitoring | meter reading | quality control ✅ ANPR | crowd monitoring | people counting | intrusion detection | perimeter security ✅ tumor detection | ultrasound | X-ray/CT analysis | lesion segmentation | medical imaging ✅ aerial monitoring | traffic flow | license plate recognition | vehicle & accident detection ✅ customer analytics | receipt extraction | shelf monitoring | inventory tracking Tech Stack: YOLOv5–YOLOv8–YOLOv11, Detectron2, MMDetection, DeepSORT, StrongSORT, MediaPipe, OpenPose, Pose Estimation, Action Recognition, Segmentation (semantic & instance), OCR, anomaly detection, object tracking, PyTorch, TensorFlow, TFLite, Core ML, OpenCV, FastAPI, Flask, ONNX, TensorRT, OpenVINO, CUDA, AWS, Azure, GCP, edge AI, mobile AI, real-time inference, video analytics, AI automation, LLM integration (GPT-4o, Claude, Gemini, Groq), LangChain, LangGraph, CrewAI, RAG systems. 💬 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.

𝗜 𝗯𝘂𝗶𝗹𝗱 𝗽𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻 𝗿𝗲𝗮𝗱𝘆 𝗔𝗜 𝘀𝘆𝘀𝘁𝗲𝗺𝘀 𝘁𝗵𝗮𝘁 𝗽𝗮𝘆 𝗳𝗼𝗿 𝘁𝗵𝗲𝗺𝘀𝗲𝗹𝘃𝗲𝘀: I saved a fintech client €𝟰𝟬,𝟬𝟬𝟬 𝗽𝗲𝗿 𝘆𝗲𝗮𝗿 by automating their KYC pipeline (𝟵𝟵%+ 𝗲𝘅𝘁𝗿𝗮𝗰𝘁𝗶𝗼𝗻 𝗮𝗰𝗰𝘂𝗿𝗮𝗰𝘆) and cut clinical documentation time by 𝟲𝟬% with an AI medical scribe inside a live EMR platform. If you have messy documents, manual workflows, or an agent or chatbot idea that needs to actually work in production, not just in a demo, I can ship it fast without sacrificing accuracy or scalability. 𝗪𝗛𝗔𝗧 𝗜 𝗕𝗨𝗜𝗟𝗗 🔹 𝗔𝗜 𝗔𝗴𝗲𝗻𝘁𝘀 & 𝗠𝘂𝗹𝘁𝗶 𝗔𝗴𝗲𝗻𝘁 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻: autonomous, decision making agents with LangChain, LangGraph and CrewAI that automate real backend processes: document review, support, lead handling, internal ops. 🔹 𝗥𝗔𝗚 𝗖𝗵𝗮𝘁𝗯𝗼𝘁𝘀 & 𝗞𝗻𝗼𝘄𝗹𝗲𝗱𝗴𝗲 𝗔𝘀𝘀𝗶𝘀𝘁𝗮𝗻𝘁𝘀: retrieval augmented generation chatbots over your PDFs, docs and databases. Hybrid GraphRAG (Neo4j) plus vector search for grounded, accurate answers with strict guardrails against hallucination. 🔹 𝗢𝗖𝗥 & 𝗗𝗼𝗰𝘂𝗺𝗲𝗻𝘁 𝗔𝗜: invoice, ID and form data extraction with PaddleOCR, AWS Textract, YOLO and LayoutLM. 𝟵𝟵%+ 𝗲𝘅𝘁𝗿𝗮𝗰𝘁𝗶𝗼𝗻 𝗮𝗰𝗰𝘂𝗿𝗮𝗰𝘆 on IDs, invoices, tables and unstructured documents. 🔹 𝗛𝗲𝗮𝗹𝘁𝗵𝗰𝗮𝗿𝗲 𝗔𝗜 & 𝗘𝗠𝗥 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻: HIPAA compliant medical scribes (Whisper speech to text, speaker diarization, auto generated SOAP notes and ICD 10 codes), wound analysis computer vision, clinical RAG with PII redaction. 🔹 𝗞𝗬𝗖 & 𝗜𝗱𝗲𝗻𝘁𝗶𝘁𝘆 𝗩𝗲𝗿𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻: document localization, MRZ parsing, ArcFace biometric matching, liveness detection, real time transaction risk engines. 𝗥𝗘𝗦𝗨𝗟𝗧𝗦 𝗖𝗟𝗜𝗘𝗡𝗧𝗦 𝗣𝗔𝗜𝗗 𝗙𝗢𝗥 €𝟰𝟬𝗞 𝗽𝗲𝗿 𝘆𝗲𝗮𝗿 𝘀𝗮𝘃𝗲𝗱: automated fintech KYC pipeline (OCR plus face match plus verification agents) 𝟲𝟬% 𝗹𝗲𝘀𝘀 𝗱𝗼𝗰𝘂𝗺𝗲𝗻𝘁𝗮𝘁𝗶𝗼𝗻 𝘁𝗶𝗺𝗲: AI medical scribe running in a production EMR 𝟰𝟬% 𝗮𝗰𝗰𝘂𝗿𝗮𝗰𝘆 𝘂𝗽𝗹𝗶𝗳𝘁: hybrid GraphRAG retrieval for complex financial queries 𝟭𝟬𝘅 𝗳𝗮𝘀𝘁𝗲𝗿 𝗱𝗼𝗰𝘂𝗺𝗲𝗻𝘁 𝗽𝗿𝗼𝗰𝗲𝘀𝘀𝗶𝗻𝗴: logistics and finance workflows 𝗦𝘂𝗯 𝟮𝟬𝟬𝗺𝘀 𝗿𝗲𝘁𝗿𝗶𝗲𝘃𝗮𝗹 𝗹𝗮𝘁𝗲𝗻𝗰𝘆: FastAPI microservices with Redis caching 𝗧𝗘𝗖𝗛 𝗦𝗧𝗔𝗖𝗞 Python, FastAPI, Docker, AWS, GCP | LangChain, LangGraph, CrewAI, OpenAI, Claude, Hugging Face | Pinecone, FAISS, Weaviate, Neo4j, MongoDB, Redis | OpenCV, YOLO, PaddleOCR, Tesseract, LayoutLM | PyTorch, TensorFlow 𝗛𝗢𝗪 𝗜 𝗪𝗢𝗥𝗞 Fast execution with production discipline: clear milestones, regular updates, clean documented code, containerized deployment. I use modern AI dev tooling (including Claude Code) to ship in days what normally takes weeks, without cutting corners on architecture. If you want an AI system that works in production, send me an invite or message and let's scope it in a quick call. 𝗞𝗲𝘆𝘄𝗼𝗿𝗱𝘀: AI Engineer, AI Agent Developer, AI Agents, Multi Agent Systems, RAG, Retrieval Augmented Generation, Chatbot Development, LLM Integration, GPT 4o, Claude, LangChain, LangGraph, CrewAI, OCR, Document AI, Data Extraction, Computer Vision, Healthcare AI, EMR Automation, KYC Automation, Identity Verification, NLP, Python, FastAPI

Expert-Vetted Top 1% on Upwork | Top 10 Machine Learning Agency on Upwork | 7+ Years in Production AI | Sports, Industrial, Satellite, Healthcare I'm a Computer Vision Engineer and Machine Learning Engineer with 7+ years delivering production-grade AI systems. Upwork has Expert-Vetted me as a Top 1% specialist in this niche, and our team is ranked among the Top 10 Machine Learning agencies on Upwork. I work with product teams and startups across sports analytics, industrial inspection, satellite and aerial imagery, access control, healthcare, and generative AI — any domain where visual data needs to become reliable, actionable output running in production. As a Computer Vision Engineer, my core work covers object detection, multi-object tracking, pose estimation, image segmentation, image processing, and real-time video analysis. I build end-to-end pipelines in Python using OpenCV, PyTorch, TensorFlow, and Keras, from dataset preparation and model training through TensorRT optimization and Docker deployment on cloud or NVIDIA Jetson edge hardware. I use C++ for performance-critical components where Python latency is a bottleneck. The domains where computer vision engineer experience creates the most value: sports analytics (player tracking, performance metrics, automated statistics from broadcast video), industrial inspection (defect detection and quality control on production lines), satellite and aerial imagery (object detection and segmentation for infrastructure analysis), access control and security (vehicle identification, multi-camera real-time monitoring), and healthcare and biomechanics (pose analysis, body measurement, and biomedical signal processing connected to AI coaching backends). As a Machine Learning Engineer and Data Scientist, I also build systems for structured and time-series data: demand forecasting, anomaly detection, biomedical signal analysis, and structural health monitoring. My data scientist workflow covers scikit-learn, pandas, NumPy, and SciPy alongside deep learning frameworks, with experiment tracking and evaluation metrics to ensure models perform consistently in production. When projects require generative AI or LLM components, I deliver RAG pipelines with LangChain and vector databases, synthetic dataset generation tools, and document processing systems using the Gemini API. Regardless of domain, the computer vision engineer approach stays the same: combine OpenCV-based preprocessing with deep learning inference into a scalable, testable pipeline that holds up under real-world conditions — variable lighting, occlusion, low resolution, multi-camera setups, and edge hardware constraints. I work with YOLO-family models, ByteTrack and DeepSORT for tracking, MediaPipe and MMPose for pose estimation, TensorRT and ONNX for inference optimization, and FastAPI with Docker for production deployment. I work with a specialized team that includes a computer vision PhD, deep learning researchers, and mathematical optimization specialists. This lets me scope complex systems, split parallel workstreams, and deliver a full Computer Vision Engineer engagement faster than a solo contributor could. Clients typically work with me when they need: - a Computer Vision Engineer to build detection, tracking, or segmentation systems from scratch - a Machine Learning Engineer to productionize a research model and meet latency requirements - a Data Scientist who can go from raw data to a deployable model end-to-end - an AI engineer to integrate LLM or generative components into an existing backend - real-time or edge inference optimized for NVIDIA Jetson or mobile deployment - a Python developer who understands both the AI pipeline and the surrounding system architecture If you need a Computer Vision Engineer with the full stack from dataset to deployed API, let's talk. Main stack: Python, OpenCV, PyTorch, TensorFlow, Keras, YOLO, ByteTrack, MediaPipe, MMPose, CoreML, TFLite, TensorRT, ONNX, scikit-learn, FastAPI, Docker, PostgreSQL, C++, NumPy, pandas, SciPy.