You will get an AI healthcare compliance or medical AI system
Project details
You will get a secure, intelligent medical AI system designed specifically for healthcare applications. I specialize in building advanced AI solutions including healthcare compliance validation, medical lab automation, RAG-based medical document analysis, and medical image segmentation systems.
With over 5 years of technical experience and hands-on expertise in Generative AI, LLM workflows, and deep learning models, I build scalable, production-ready healthcare AI platforms. My systems combine Large Language Models, medical imaging (CNN-based segmentation), and structured compliance engines to ensure accuracy and reliability.
Unlike generic AI solutions, I focus on real-world healthcare workflows, regulatory considerations (FDA/WHO standards), and secure deployment practices. Every project is architected for performance, scalability, and maintainability.
If you're building a healthtech startup, medical automation platform, or compliance system, I deliver enterprise-grade AI solutions tailored to your clinical and operational needs.
With over 5 years of technical experience and hands-on expertise in Generative AI, LLM workflows, and deep learning models, I build scalable, production-ready healthcare AI platforms. My systems combine Large Language Models, medical imaging (CNN-based segmentation), and structured compliance engines to ensure accuracy and reliability.
Unlike generic AI solutions, I focus on real-world healthcare workflows, regulatory considerations (FDA/WHO standards), and secure deployment practices. Every project is architected for performance, scalability, and maintainability.
If you're building a healthtech startup, medical automation platform, or compliance system, I deliver enterprise-grade AI solutions tailored to your clinical and operational needs.
AI Algorithms
Convolutional Neural Network, Large Language Model, Long Short-Term Memory Network, Multimodal Large Language Model, Recurrent Neural Network, Transformer ModelAI Applications
AI Chatbot, AI-Enhanced Classification, AI-Enhanced Medical Imaging, Anomaly Detection, Conversational AI, Image Analysis, Image Processing, Image Recognition, Natural Language Generation, Natural Language Understanding, Object DetectionAI Development Language
PythonAI Tools
Hugging Face, PyTorch, Streamlit, TensorFlow, Word2vecAI Models
BERT, ChatGPT, GPT-4, LLaMA, WhisperWhat's included
| Service Tiers |
Starter
$400
|
Standard
$900
|
Advanced
$1,800
|
|---|---|---|---|
| Delivery Time | 7 days | 14 days | 21 days |
Number of Revisions | 1 | 2 | 2 |
AI Model Integration | |||
Batch Normalization | - | - | |
Database Integration | - | ||
Detailed Code Comments | - | ||
Image Upscaling | - | - | - |
MLOps | - | - | |
Model Deployment | - | ||
Model Documentation | |||
Model Monitoring | - | - | |
Model Testing & Optimization | - | ||
Model Tuning | - | ||
Natural Language Processing | |||
NLP Tokenization | - | - | - |
Pre-Training | - | - | - |
Prompt Engineering | |||
Setup File | |||
Source Code |
About Anjum
AI & Machine Learning Engineer | Generative & Agentic AI | NLP
Rawalpindi, Pakistan - 4:05 am local time
✅ 𝗖𝗼𝗿𝗲 𝗘𝘅𝗽𝗲𝗿𝘁𝗶𝘀𝗲
𝗔𝗴𝗲𝗻𝘁𝗶𝗰 𝗔𝗜 & 𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝘃𝗲 𝗔𝗜 𝗦𝘆𝘀𝘁𝗲𝗺𝘀: Design and develop autonomous Agentic AI systems using LangGraph and LangChain with tool orchestration, stateful workflows, and LLM-driven decision-making. Build production-ready AI services with FastAPI and scalable backend integration.
𝗥𝗔𝗚 (𝗥𝗲𝘁𝗿𝗶𝗲𝘃𝗮𝗹-𝗔𝘂𝗴𝗺𝗲𝗻𝘁𝗲𝗱 𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝗼𝗻) 𝗣𝗶𝗽𝗲𝗹𝗶𝗻𝗲𝘀: Design and build scalable RAG architectures using FAISS and vector databases for semantic search, document intelligence, compliance validation, and knowledge-grounded question answering.
𝗠𝗼𝗱𝗲𝗹 𝗖𝗼𝗻𝘁𝗲𝘅𝘁 𝗣𝗿𝗼𝘁𝗼𝗰𝗼𝗹 (𝗠𝗖𝗣) 𝗜𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗶𝗼𝗻: Integrate MCP-based tool calling to connect LLM agents with external APIs, enabling real-time data retrieval, validation, and context-aware reasoning.
𝗙𝘂𝗹𝗹-𝗦𝘁𝗮𝗰𝗸 𝗔𝗜 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁: Deliver end-to-end Full-Stack AI solutions using Python, FastAPI, Streamlit, Docker, TensorFlow, PyTorch, and Hugging Face — from model development to scalable production deployment.
𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 & 𝗗𝗲𝗲𝗽 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴: Strong foundation in classical machine learning (Linear/Logistic Regression, SVM, Decision Trees, Random Forest, KNN) and deep learning architectures (CNNs, RNNs, LSTMs, Transformers), with expertise in optimization, regularization, and hyperparameter tuning.
𝗧𝗲𝗰𝗵 𝗦𝘁𝗮𝗰𝗸:
Python, SQL, FastAPI, Django, Streamlit, LangChain, LangGraph, TensorFlow, PyTorch, Hugging Face, Scikit-learn, XGBoost; PostgreSQL, MySQL, MongoDB; Docker, GitHub Actions (CI/CD); AWS, Render Cloud; VS Code.
Let’s collaborate and discuss how we can harness these technologies to achieve your goals.
Steps for completing your project
After purchasing the project, send requirements so Anjum can start the project.
Delivery time starts when Anjum receives requirements from you.
Anjum works on your project following the steps below.
Revisions may occur after the delivery date.
Medical Requirements Analysis
I analyze your medical use case, datasets, regulatory standards (FDA/WHO/local), and system goals to design a secure and scalable AI architecture before development begins.
AI System Design
I design the system architecture including LLM workflows, RAG pipelines, medical imaging models, database structure, and API integrations.