> ## Documentation Index
> Fetch the complete documentation index at: https://docs.sinkove.com/llms.txt
> Use this file to discover all available pages before exploring further.
# Introduction
> Generate synthetic medical imaging datasets with advanced AI
## Overview
Sinkove provides a powerful platform for generating synthetic medical imaging datasets leveraging advanced generative AI, primarily diffusion models. Users can easily create customized datasets suitable for AI model training, clinical trials and general research around medical imaging. We provide a python SDK and a web application to interact with our AI models.
Get started generating your first synthetic medical imaging dataset
Download and manage datasets programmatically with our Python SDK
## Key Features
Leverage state-of-the-art diffusion models for high-quality synthetic
medical images
Configure datasets with specific medical conditions and imaging parameters
Seamlessly integrate with your workflows using our REST API
Ready-to-use Python SDK with practical examples for rapid integration
## Getting Started
Ready to create your first synthetic medical imaging dataset? Our platform makes it simple:
1. **Select a Model** - Choose from our collection of advanced generative models
2. **Configure Parameters** - Specify medical conditions and imaging requirements
3. **Generate Data** - Create preview samples or full datasets up to 1000 images
4. **Download Results** - Use our Python SDK for efficient dataset management
Follow our quick start guide to generate your first synthetic dataset in
minutes
## Developer Resources
Set up the Python SDK in your environment
Browse practical code examples and patterns
Complete SDK API documentation