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Kasal Documentation Hub

Enterprise AI Agent Orchestration Platform

Quick Start

Find the right documentation for your role and get productive fast.

Choose your documentation based on your role:

Technical Documentation

Developer-focused guides, code structure, and API reference.

Code structure Guide

For Software Engineers and Developers

Build and integrate with Kasal's powerful AI orchestration platform. From quick starts to advanced implementations.

Key Topics:

  • High level code structure
  • Different folders and underlying components

Developer Guide

For Software Engineers and Developers

Build and integrate with Kasal's powerful AI orchestration platform. From quick starts to advanced implementations.

Key Topics:

  • 30-Second Quick Start with Code Examples
  • API Integration and SDK Usage
  • Testing Strategies and Best Practices
  • Production Deployment Guides

API Reference

For API Integrators and Backend Engineers

Complete REST API documentation with examples, WebSocket events, and SDK libraries.

Key Topics:

  • RESTful Endpoints Documentation
  • WebSocket Real-time Events
  • Authentication and Authorization
  • Rate Limits and Error Handling

Architecture Documentation

System design, patterns, and enterprise integration guidance.

Solution Architecture Guide

For Solution Architects and Technical Leaders

Understand Kasal's architecture, design patterns, and enterprise integration strategies.

Key Topics:

  • System Design and Components
  • Security Model and Compliance
  • Scaling Strategies and Performance
  • Integration Patterns and Best Practices

Getting Started in 30 Seconds

One command sequence to run both backend and frontend locally.

# Clone the repository
git clone https://github.com/databrickslabs/kasal

# Start the backend (uv syncs dependencies automatically)
cd kasal/src/backend && ./run.sh

# In another terminal, start the frontend
cd kasal/src/frontend && npm install && npm start

Access the application at http://localhost:3000

Key Features

What Kasal provides out of the box to build, operate, and govern AI workflows.

Feature Description
AI Agent Orchestration Create and manage teams of AI agents working together
Visual Workflow Designer Drag-and-drop interface for creating complex workflows
Enterprise Security SOC2 compliant with role-based access control
Databricks Integration Native integration with Databricks platform
Scalable Architecture Microservices-ready, horizontally scalable design
Multi-Model Support Support for GPT-4, Claude, Databricks models, and more

Documentation Structure

How this folder is organized and where to find topics.

docs/
├── README.md                    # This file - Documentation hub
├── CODE_STRUCTURE_GUIDE.md      # Code structure documentation
├── DEVELOPER_GUIDE.md           # Developer documentation
├── ARCHITECTURE_GUIDE.md        # Architecture documentation
├── API_REFERENCE.md             # API reference
└── archive/                     # Legacy documentation
    ├── technical/               # Technical deep-dives
    ├── security/                # Security documentation
    └── guides/                  # Various guides

Technology Stack

Core frameworks and platforms used across the project.

  • Backend: FastAPI, SQLAlchemy 2.0, Python 3.9+
  • Frontend: React 18, TypeScript, Material-UI
  • AI Engine: CrewAI, LangChain
  • Database: PostgreSQL / SQLite
  • Authentication: JWT + Databricks OAuth

Support and Resources

Where to get help and how to contribute.

Getting Help

Contributing

We welcome contributions! Please see our Contributing Guide for details.

License

This project is licensed under the Apache License 2.0 - see the LICENSE file for details.

Version Information

Project and documentation version details.

  • Current Version: 2.0.0
  • Documentation Updated: December 2025
  • Minimum Python Version: 3.10
  • Minimum Node Version: 16.0

Built by Databricks Labs