# Rendered.ai Documentation

> Rendered.ai provides two products: **Agent Studio** and **Synthetic Data Studio**. Agent Studio is a cloud platform for building AI-powered development environments with context-aware Agents, containerized services, and collaborative workspaces. Synthetic Data Studio is a platform for generating high-quality synthetic data using configurable pipelines for computer vision and machine learning applications.

## Documentation Site

- URL: https://docs.rendered.ai
- Publisher: Rendered.ai

## Product-Specific Documentation

For deeper product context including data models, resource hierarchies, and architecture:

- [Agent Studio](https://docs.rendered.ai/agent-studio-llms.txt): AI-enabled workspaces, Agents, services, skills, and developer tools
- [Synthetic Data Studio](https://docs.rendered.ai/synthetic-data-studio-llms.txt): Synthetic data generation, channels, graphs, nodes, and datasets

---

## Synthetic Data Studio

### General Concepts

- [Overview](https://docs.rendered.ai/synthetic-data-studio/general-concepts): Overview of Rendered.ai general concepts
- [Introduction to Rendered.ai](https://docs.rendered.ai/synthetic-data-studio/general-concepts/introduction): What is synthetic data and why Rendered.ai
- [The Rendered.ai Platform](https://docs.rendered.ai/synthetic-data-studio/general-concepts/platform): Overview of the Rendered.ai Platform
- [Who Uses Rendered.ai?](https://docs.rendered.ai/synthetic-data-studio/general-concepts/who-uses): Workflows for synthetic data engineers and data scientists
- [Licensing and Offerings](https://docs.rendered.ai/synthetic-data-studio/general-concepts/licensing): Subscription tiers and licensing options

### Application User Guides

- [Quick Start Guide](https://docs.rendered.ai/synthetic-data-studio/application-user-guides/quick-start-guide): Get started with Rendered.ai
- [Terminology](https://docs.rendered.ai/synthetic-data-studio/application-user-guides/quick-start-guide/terminology): Common terms used in the Rendered.ai platform
- [Content Codes](https://docs.rendered.ai/synthetic-data-studio/application-user-guides/quick-start-guide/content-codes): Getting started with content codes
- [Getting Started with the SDK](https://docs.rendered.ai/synthetic-data-studio/application-user-guides/quick-start-guide/getting-started-with-the-sdk): Using the anatools SDK to connect to the Rendered.ai platform
- [Tutorials](https://docs.rendered.ai/synthetic-data-studio/application-user-guides/tutorials): Step-by-step tutorials for using the Rendered.ai Synthetic Data Studio
- [Organization & Workspace Resources](https://docs.rendered.ai/synthetic-data-studio/application-user-guides/tutorials/organization-and-workspace-resources): Managing organization-level and workspace-level resources
- [Creating and Using Graphs](https://docs.rendered.ai/synthetic-data-studio/application-user-guides/tutorials/creating-and-using-graphs): How to create, edit, and use graphs in Rendered.ai
- [Graph Validation](https://docs.rendered.ai/synthetic-data-studio/application-user-guides/tutorials/creating-and-using-graphs/graph-validation): Understanding graph validation rules and warnings
- [Graph Best Practices](https://docs.rendered.ai/synthetic-data-studio/application-user-guides/tutorials/creating-and-using-graphs/graph-best-practices): Best practices for building effective graphs
- [Creating and Using Datasets](https://docs.rendered.ai/synthetic-data-studio/application-user-guides/tutorials/creating-and-using-datasets): Working with datasets generated by the Rendered.ai platform
- [Annotations](https://docs.rendered.ai/synthetic-data-studio/application-user-guides/tutorials/creating-and-using-datasets/annotations): Annotation formats and mapping in Rendered.ai
- [Analytics](https://docs.rendered.ai/synthetic-data-studio/application-user-guides/tutorials/creating-and-using-datasets/analytics): Dataset analytics tools in Rendered.ai
- [Domain Adaptation](https://docs.rendered.ai/synthetic-data-studio/application-user-guides/tutorials/creating-and-using-datasets/domain-adaptation): Using CycleGAN models for domain adaptation
- [Comparison](https://docs.rendered.ai/synthetic-data-studio/application-user-guides/tutorials/creating-and-using-datasets/comparison): Comparing datasets using feature analysis
- [Training and Inference](https://docs.rendered.ai/synthetic-data-studio/application-user-guides/tutorials/creating-and-using-datasets/training-and-inference): Training CV models and running inference with synthetic data
- [Mixing Datasets](https://docs.rendered.ai/synthetic-data-studio/application-user-guides/tutorials/creating-and-using-datasets/mixing-datasets): Combining images from multiple datasets
- [Best Practices](https://docs.rendered.ai/synthetic-data-studio/application-user-guides/tutorials/creating-and-using-datasets/best-practices): Dataset directory structure and file format specifications
- [Creating and Using Volumes](https://docs.rendered.ai/synthetic-data-studio/application-user-guides/tutorials/creating-and-using-volumes): Working with volumes for 3D models and content
- [Inpaint Service](https://docs.rendered.ai/synthetic-data-studio/application-user-guides/tutorials/creating-and-using-volumes/inpaint-service): Using the inpaint service for image manipulation
- [Collaboration](https://docs.rendered.ai/synthetic-data-studio/application-user-guides/tutorials/collaboration): Sharing and collaborating on the Rendered.ai platform

### Development Guides

- [Ana Software Architecture](https://docs.rendered.ai/synthetic-data-studio/development-guides/ana-software-architecture): Overview of the architecture that powers the Rendered.ai synthetic data platform
- [Basic Components](https://docs.rendered.ai/synthetic-data-studio/development-guides/ana-software-architecture/basic-components): Overview of the fundamental components in the Ana synthetic data architecture
- [Graphs](https://docs.rendered.ai/synthetic-data-studio/development-guides/ana-software-architecture/graphs): Understanding the graph structure that defines synthetic data generation pipelines
- [Channels](https://docs.rendered.ai/synthetic-data-studio/development-guides/ana-software-architecture/channels): Channel structure and configuration for Rendered.ai synthetic data pipelines
- [Packages](https://docs.rendered.ai/synthetic-data-studio/development-guides/ana-software-architecture/packages): How packages provide nodes for graphs in the Rendered.ai platform
- [Package Volumes](https://docs.rendered.ai/synthetic-data-studio/development-guides/ana-software-architecture/package-volumes): Using volumes to store and access large asset files in Rendered.ai packages
- [Nodes](https://docs.rendered.ai/synthetic-data-studio/development-guides/ana-software-architecture/nodes): Creating node classes that implement processing steps in Rendered.ai graphs
- [Schema](https://docs.rendered.ai/synthetic-data-studio/development-guides/ana-software-architecture/schema): Defining node interfaces with YAML schema files in Rendered.ai
- [Ana Modules](https://docs.rendered.ai/synthetic-data-studio/development-guides/ana-software-architecture/ana-modules): Core library components available to node developers on the Rendered.ai platform
- [Anatools Package](https://docs.rendered.ai/synthetic-data-studio/development-guides/ana-software-architecture/anatools-package): Built-in utility nodes available in every Rendered.ai channel
- [Graph Validation](https://docs.rendered.ai/synthetic-data-studio/development-guides/ana-software-architecture/graph-validation): How graph validation works using JSON Schema and Rendered.ai extensions
- [Preview](https://docs.rendered.ai/synthetic-data-studio/development-guides/ana-software-architecture/preview): Using preview mode for fast iteration during channel development
- [In-Tool Help](https://docs.rendered.ai/synthetic-data-studio/development-guides/ana-software-architecture/in-tool-help): Adding documentation and help content to nodes and channels in Rendered.ai
- [Setting Up the Dev Environment](https://docs.rendered.ai/synthetic-data-studio/development-guides/setting-up-dev-environment): How to set up a local development environment for Rendered.ai channel development
- [Deploying a Channel](https://docs.rendered.ai/synthetic-data-studio/development-guides/deploying-a-channel): How to deploy a channel to the Rendered.ai platform using anadeploy

### Open Source Channels

- [Toybox](https://docs.rendered.ai/synthetic-data-studio/open-source-channels/toybox): Overview of the Toybox open-source channel for physics-based synthetic image generation
- [Run and Deploy](https://docs.rendered.ai/synthetic-data-studio/open-source-channels/toybox/run-and-deploy): Tutorial for cloning, running, and deploying the Toybox example channel
- [Add a Modifier Node](https://docs.rendered.ai/synthetic-data-studio/open-source-channels/toybox/add-modifier-node): Tutorial for creating a Scale Modifier node in the Toybox channel
- [Add a Generator Node](https://docs.rendered.ai/synthetic-data-studio/open-source-channels/toybox/add-generator-node): Tutorial for adding a new object type to the Toybox channel
- [DIRSIG](https://docs.rendered.ai/synthetic-data-studio/open-source-channels/dirsig-channel): Overview of the DIRSIG Rendered.ai channel for simulation-based synthetic data generation

---

## Agent Studio

### Getting Started

- [Welcome](https://docs.rendered.ai/agent-studio): Welcome to the Agent Studio documentation
- [Examples](https://docs.rendered.ai/agent-studio/examples): Browse example templates for workspaces, services, volumes, and rules to quickly get started in Agent Studio.
- [Collaboration](https://docs.rendered.ai/agent-studio/collaboration): How to invite team members to your Organization, manage roles, and share workspaces.
- [Costs and Billing](https://docs.rendered.ai/agent-studio/costs-and-billing): Understanding costs and billing in Agent Studio

### Basics

- [Workspaces](https://docs.rendered.ai/agent-studio/basics/workspaces): Workspaces bring your tools and data together in one place. Launch servers to access context-aware Agents that understand your problem space and help you build solutions.
- [Servers](https://docs.rendered.ai/agent-studio/basics/servers): Servers are cloud-based development environments running within your workspaces. Each server provides an integrated IDE where you and your Agents collaborate to build, test, and iterate on your work.
- [Web IDE](https://docs.rendered.ai/agent-studio/basics/servers/web-ide): The Web IDE is a browser-based development environment that lets you work with Agents directly from your browser without any local setup.
- [Tyrell Agent](https://docs.rendered.ai/agent-studio/basics/servers/tyrell-agent): The AI-powered assistant within your server that understands your workspace context and helps you build.
- [Rendered.ai Extension](https://docs.rendered.ai/agent-studio/basics/servers/rendered-ai-extension): The workspace synchronization extension that keeps your server environment in sync with your workspace configuration.
- [Services](https://docs.rendered.ai/agent-studio/basics/services): Services are containerized tools with specified inputs and outputs. They can be used to process data, run simulations, and much more.
- [Volumes](https://docs.rendered.ai/agent-studio/basics/volumes): Volumes are persistent data storage attached to workspaces. They make it easy to share data between projects and retain it long-term, even after servers are terminated.
- [Rules](https://docs.rendered.ai/agent-studio/basics/rules): Rules provide context that guides Agents in performing tasks. They can be applied at the Organization, Workspace, Service, or User level.
- [MCP Configs](https://docs.rendered.ai/agent-studio/basics/mcp-configs): MCP Configs let you connect additional Model Context Protocol servers to your Agent, extending its capabilities with new tools and data sources.
- [Agent Skills](https://docs.rendered.ai/agent-studio/basics/skills): Agent Skills are packaged capabilities that can be uploaded to the platform and added to servers, giving Agents pre-built expertise for common tasks.
- [Secrets](https://docs.rendered.ai/agent-studio/basics/secrets): Secrets securely store API keys and sensitive configuration as environment variables on your servers.

### Developer Guide

- [Creating Services](https://docs.rendered.ai/agent-studio/develop/creating-a-new-service): Guide to creating, testing, and deploying custom containerized services for Agent Studio.
- [Creating Persistent Services](https://docs.rendered.ai/agent-studio/develop/persistent-services): Services that run continuously in the background, providing always-ready tools with warm instances and maintained state.
- [Creating Agent Skills](https://docs.rendered.ai/agent-studio/develop/creating-skills): Guide to creating, testing, and publishing Agent Skills that give Agents pre-built expertise for common tasks.
- [Creating MCP Servers](https://docs.rendered.ai/agent-studio/develop/mcp-servers): How to integrate custom MCP servers into Agent Studio to extend your Agent with new tools and data sources.