You will get Advanced AI Virtual Painter
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Project details
I built this tool for you from the ground up using MediaPipe, OpenCV, and Google Speech API to deliver a genuinely hands-free creative experience through your webcam.
Draw with finger gestures, autocomplete shapes with AI, and control everything with simple voice commands instantly.
For educators it is a compelling classroom demo. For developers it is a production-ready computer vision foundation to build on. For creatives it removes every barrier between idea and execution.
Draw with finger gestures, autocomplete shapes with AI, and control everything with simple voice commands instantly.
For educators it is a compelling classroom demo. For developers it is a production-ready computer vision foundation to build on. For creatives it removes every barrier between idea and execution.
AI Development Type
Deep Learning, Model TuningAI Tools
PyTorch, TensorFlowAI Development Language
PythonWhat's included
| Service Tiers |
Starter
$150
|
Standard
$300
|
Advanced
$500
|
|---|---|---|---|
| Delivery Time | 3 days | 5 days | 7 days |
Number of Revisions | 1 | 2 | 3 |
AI Model Integration | |||
Detailed Code Comments | |||
Knowledge Graph | - | ||
Model Documentation | |||
Ontology | - | - | |
Source Code | |||
Taxonomy | - | - |
Optional add-ons
You can add these on the next page.
Fast Delivery
+$100 - $200
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About Faizan
AI Engineer | RAG, LLM & Full-Stack Web Developer for Healthcare
100%
Job Success
Lahore, Pakistan - 9:54 am local time
I handle the full project myself, from the data work through deployment, including the web application and payment setup when needed.
Recent work:
HealthDataVitals: a live platform I built and launched that tracks healthcare cost, quality, and performance data. I managed the dashboard, the data pipeline, and payment integration from start to finish.
An agentic RAG system that lets teams upload medical documents and ask questions about them in plain language. It automatically detects and removes protected health information from medical files before storing them, so documents stay searchable without exposing patient data.
A diabetes prediction system built with ensemble models (Random Forest, XGBoost, and LightGBM) and SHAP explainability, so users can see which factors drove each prediction. I built multiple ways to access it, including a web app, a REST API, and a Discord bot.
A voice-controlled AI assistant that takes spoken questions, analyzes uploaded images, and replies out loud, useful for hands-free situations like a clinician dictating notes or reviewing an image without touching a keyboard. It supports OpenAI, Anthropic, and local models.
Tools I use most often:
LangChain and LangGraph for RAG systems, OpenAI and Hugging Face for AI models, Pinecone and ChromaDB for document search, and Docker and AWS for hosting. For the application side, I use React, Node.js, and PostgreSQL to build dashboards and connect everything together.
Healthcare data needs careful handling. On my RAG project, I built automatic detection and removal of protected health information before any data entered the system, so documents could be searched without exposing patient details. On every project, I also set up role-based access and encrypt data both in storage and in transit.
If you have a healthcare AI project in mind, send me a message with the type of data you're working with and the main question you want your system to answer. I will reply within a day with some initial thoughts.
Steps for completing your project
After purchasing the project, send requirements so Faizan can start the project.
Delivery time starts when Faizan receives requirements from you.
Faizan works on your project following the steps below.
Revisions may occur after the delivery date.
Requirement Review
Review client requirements, operating system, and any custom feature requests before starting development.
Environment Setup
Set up the Python environment, install all dependencies, and verify webcam and microphone compatibility on the target system.