Hire the Best OCR Algorithms Specialists
in India

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!

I help enterprise organizations eliminate LLM hallucinations, slash operational overhead, and scale intelligent document automation. By anchoring cognitive vision frameworks with strict runtime schema validation, I engineer custom, production-grade RAG pipelines and Intelligent AI OCR architectures that deliver deterministic data workflows with a verified 96.8% field-level accuracy across 10,000+ complex corporate pages. If you are dealing with standard vector-search chatbots that hallucinate, lose context, or fail to read dense data tables, or if your legacy OCR tools are outputting broken, chaotic text from blurry scans, faxes, and invoices, I build the automated bridge to clean, database-ready structured data. Unlike generalist script-writers who blindly dump data into basic vector stores, I design enterprise-ready, layout-aware, cost-optimized pipelines engineered specifically for highly confidential, unstructured, multi-column, and multi-page corporate assets. CORE WORKFLOWS & SEARCH-OPTIMIZED ARCHITECTURES: 1. Production RAG Pipelines & Enterprise Knowledge Bases • Advanced Hybrid Search Indexing: Fusing dense semantic vector embeddings (Pinecone, Qdrant, ChromaDB) with sparse keyword retrieval (BM25) to guarantee specific alphanumeric codes, legal sections, and invoice serial numbers are never missed during a query. • Two-Stage Context Reranking: Implementing Cross-Encoder Rerankers (Cohere Rerank, FlashRank) to filter retrieved document nodes down to the absolute best context chunks, slashing downstream LLM token costs by up to 40% while accelerating system execution speed. • Layout-Aware Hierarchical Chunking: Parsing structured document layouts natively to maintain strict parent-child context windows, preventing sentences or complex financial data tables from being blindly split in half during vector indexing. 2. Intelligent AI OCR & Multi-Modal Document Intelligence • Vision-Based Pre-Processing: Utilizing OpenCV, PaddleOCR, and LayoutLMv3 to automatically de-skew, binarize, and map out the multi-column reading order of messy scanned PDFs, faxes, or smartphone images before running extraction. • Multi-Modal LLM & Vision Data Extraction: Routing raw text tokens and visual patches through state-of-the-art vision-language models (GPT-4o, Claude 3.5 Sonnet, or local open-source models like Llama-3.2-Vision and Qwen2.5-VL) to automatically repair transcription typos and misaligned characters by understanding the surrounding industry context. 3. Schema Enforcement & Human-in-the-Loop (HITL) Guardrails • Strict Schema Enforcement: Employing programmatic validation frameworks like Instructor and Pydantic to mathematically force LLM outputs into 100% compliant, database-ready JSON, CSV, or SQL structures at the native API level. • Algorithmic Triage: Tracking model confidence log-probabilities. High-confidence data saves instantly to production databases, while low-confidence edge cases route seamlessly to custom Streamlit dashboards for rapid human validation. PROVEN ENTERPRISE CASE STUDIES & SUCCESS METRICS: • Enterprise Document Intelligence: Multimodal AI OCR, Pydantic Extraction & Hybrid RAG Pipeline Designed and engineered an end-to-end production pipeline to automate the processing of dense, unstructured corporate assets (including scanned PDFs, financial statements, and high-volume faxes). Used LayoutLMv3 to preserve structural hierarchies and the Instructor library paired with strict Pydantic schemas to achieve an elite 96.8% verified field-level extraction accuracy across 10,000+ pages. • AI OCR Automation for High-Volume Faxes: Engineered a highly resilient extraction and contextual text-cleaning pipeline running flawlessly for complex, handwritten and blurry business records. • Markdown Data Extraction Specialist: Built a hyper-accurate pipeline converting complex document styles into structured markdown format for seamless vector indexing and RAG ingestion • Enterprise Document Parsing: Consulted on and deployed custom backend AI microservices to clean, parse, and automate unstructured multi-page document flows. MODERN PRODUCTION TECH STACK: • LLMs & Vision-Language Models: GPT-4o, Claude 3.5 Sonnet, Llama-3.2-Vision, Qwen2.5-VL, DeepSeek-VL2 • Frameworks & Validation: Instructor (Pydantic), LangChain, LlamaIndex, vLLM, Ollama, LangGraph • OCR & Computer Vision: Tesseract OCR, EasyOCR, PaddleOCR, OpenCV, LayoutLMv3, Marker, Text Extraction • Infrastructure & Vector DBs: Python, AI Chatbot Development, VectorDBs (Pinecone, Chroma, Qdrant), PostgreSQL, Docker, Data Scraping, Web Scraping, PDF to Excel Ready to eliminate hallucinations, protect your data privacy, and automate your critical document workflows with deterministic accuracy? Click "Invite to Job" to review your current pipeline architecture.

Hello, I'm Anup Patil, an AI-powered Web Scraping & Data Engineer with 12+ years experience in building intelligent data extraction systems, automation pipelines, and dashboards for AI/ML and business intelligence projects. Today, I leverage modern AI coding tools (Codex, Claude, Cursor, Copilot) together with strong Python expertise to deliver faster, scalable, and cost-efficient solutions for complex data problems. I help companies collect, structure, and transform data into usable formats for Machine Learning, analytics dashboards, and business automation. 🚀 Core Expertise 🤖 AI-Powered Web Scraping Intelligent scraping using LLMs + Python Dynamic websites, login systems, pagination, JS rendering Scrapy, Selenium, Playwright, Requests, BeautifulSoup Automatic data cleaning and structuring for AI usage 🧠 AI & LLM Automation GPT / Claude powered workflows AI agents for decision making pipelines prompt engineering & structured output pipelines automated classification & enrichment of datasets 📊 Data Engineering for ML Projects dataset preparation for ML models data normalization and transformation structured JSON, CSV, database pipelines large-scale scraping (millions of records) 📈 Dashboard & Web Apps for Data Projects dashboards for scraped or AI processed data FastAPI / Django APIs Next.js dashboards data visualization pipelines ⚙️ Automation Systems workflow automation using Python & APIs n8n, cron jobs, server automation PDF parsing, document extraction business process automation ☁️ Cloud & Infrastructure AWS deployment (EC2, S3, Lambda) proxy rotation, captcha solving scalable scraping architecture Docker based deployments 💡 Example Projects I Can Build AI-powered lead generation scraper ML training dataset collection pipelines automated competitor price monitoring document & PDF data extraction systems AI classification pipeline for companies or products dashboard showing real-time scraped insights automation bots for repetitive online tasks 🛠 Tech Stack Python • Scrapy • Selenium • Playwright • FastAPI • Django LLM APIs • OpenAI • Claude • Prompt Engineering Next.js • API Integration • PostgreSQL • MongoDB AWS • Docker • Proxy rotation • CAPTCHA solving AI Tools: Codex • Cursor • Copilot • Claude • ChatGPT ⭐ Why hire me? ✔ Combine 12 years scraping experience + modern AI tools ✔ faster development using AI-assisted coding ✔ scalable architecture for large datasets ✔ clear communication & reliable delivery ✔ long-term collaboration mindset If your project involves AI data collection, automation, or ML dataset preparation, I can help you build a reliable system quickly. 📩 Send me a message — I can suggest best architecture for your project.

I've built a system that reads ID cards from a live video call without any human involved. I've built a platform where logistics clients record themselves on camera and admins track every document they submit. I've shipped real work to real clients — a 3D product animation for a skincare brand and a portfolio site someone actually uses today. That's the kind of work I do. - Computer vision & OCR pipelines - AI apps using OpenAI and Gemini - Full-stack with Python + React - 3D modeling and product animation in Blender Stack I work with: Python, FastAPI, OpenCV, YOLO, Tesseract OCR, React.js, Node.js, MongoDB, Supabase, OpenAI API, Gemini API, Hugging Face, Docker, Git, Blender I'm straightforward to work with, I ask the right questions upfront, and I deliver what I said I would.

✔️ TOP RATED Freelancer specializing in Computer Vision and AI-based image processing systems. I enjoy building practical, production-ready solutions for real-world visual problems and would be glad to contribute to your project in a meaningful way. My core focus is on computer vision, especially tasks involving image understanding, detection, and extraction from complex or noisy inputs. I have strong experience working with: ✔️Image Classification & Fine-Grained Recognition (handling subtle visual differences) ✔️Object Detection (YOLO, SSD, Faster R-CNN, TFOD API) ✔️Image Segmentation (Mask R-CNN, semantic & instance segmentation) ✔️OCR & Text Extraction (structured documents, multi-format, noisy images) ✔️Image Preprocessing (denoising, deskewing, perspective correction, enhancement) ✔️OpenCV-based pipelines for real-time and production use ✔️Deep Learning frameworks: TensorFlow, Keras, PyTorch ✔️CNN Architectures: ResNet, VGG, Inception, EfficientNet ✔️Transfer Learning & Custom Model Training ✔️Synthetic Data Generation & Augmentation ✔️Vector Embeddings & Image Similarity Systems ✔️End-to-End CV Pipelines (data collection → training → deployment) Alongside this, I also have a solid foundation in: ✔️Machine Learning & Deep Learning ✔️Mathematics & Statistics (for model understanding and optimization) ✔️Python ecosystem (NumPy, Pandas, SciPy, etc.) ✔️API Development & Deployment(Docker, AWS, GCP) I hold a Bachelor’s degree in Computer Engineering and am currently pursuing a Master’s in AI, which helps me stay aligned with the latest advancements in the field. My approach is always to first understand the business problem and real-world constraints, and then design a solution that is accurate, scalable, and practical to use. I care deeply about delivering solutions that actually work for clients not just in theory, but in real-world conditions. Thanks & Regards, Ruchir

Experienced data scientist with over 4 years of experience in machine learning projects. Active participant on Kaggle, a google backed platform for data science competitions, rated within Top 1% data scientists globally. Have experienced in deep neural networks, convolution neural networks, recurrent neural networks, genetic algorithms, natural language processing, support vector machines, and generative adversarial networks. 𝐒 𝐊 𝐈 𝐋 𝐋 𝐒 ------------------------- 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗹𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗘𝘅𝗽𝗲𝗿𝘁𝗶𝘀𝗲 : - CNN, - DNN, - RNN/LSTM, - GAN, - Transformers, - Auto-Encoders, - HMM-GMM - SVM, - Boosting, - Random forest, 𝗣𝗿𝗼𝗴𝗿𝗮𝗺𝗺𝗶𝗻𝗴 𝗹𝗮𝗻𝗴𝘂𝗮𝗴𝗲 𝗘𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲 : - C, - C++, - Python, - R, - Matlab, - CUDA(Beginner). 𝗙𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸/𝗟𝗶𝗯𝗿𝗮𝗿𝗶𝗲𝘀 𝗘𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲 : - Tensorflow, - Tensorflow lite, - Tensorflow js, - Keras, - Pytorch, - RASA, - Pandas, - Scikit-learn, - Open CV, - Tesseract OCR, - Kaldi, - OpenFace, - SpaCy, - NLTK, - Open Pose, - Others as well based on experience. 𝗧𝗼𝗼𝗹 𝗘𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲 : - Jupyter-notebook - Google Colab - Pycharm - R-Studio 𝗣𝗮𝘀𝘁 𝗘𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲 𝘄𝗼𝗿𝗸 : - Generating karyotype from Chromosome micro slide image. - Identify boundaries of wound and measurement of wound - Extensive object detection, Detection of Sky, Window, Glass, Tree, building. - automated tool for detecting norms and stereotypes in popular culture. - Deep Learning with Image processing for the transformation of style from one image to another. - Mobile embedded object detection model with TF-lite. - Developed an algorithm to generate a 3D model of faces from a single 2D mobile selfie using Python, Convolutional Neural Networks, PyTorch, and CUDA. - Created an algorithm for image and video compression using similarity between images with the help of OpenCV. - Developed an algorithm for the classification of different sounds of drones using MFCC and LPCC features and then SVM and HMM-GMM classifiers. - Created a default loan predictor algorithm with 99.4% accuracy using Python and deep neural networks. - Created an optical character recognition for English language using Python and OpenCV,. - Extracted the Legos from the videos and the classify it into 52 different classes using the convolutional neural network using Python. - Worked on the CNN based binary text classification for the movie reviews to identify the positive and negative reviews with neural networks and Python. - Developed an algorithm for moving object detection, which can find a moving object in a vibrant environment using deep neural networks, OpenCV, and Python. - Many other projects I have worked on. Few of them are signed with NDA. I shall be glad to provide any information/clarification that you might need to make a better decision. If you like my work. Please Direct Message me OR invite me to your job. I will happy to connect and take your project to success. Thanks for taking the time to read through my profile. Looking forward to talking to you. Thanks