Kasal turns complex AI orchestration into an intuitive visual experience. Design, deploy, and monitor autonomous AI agents that collaborate to solve real-world business problems — without writing orchestration code.
- Visual Workflow Designer — Drag-and-drop canvas for composing sophisticated agent interactions
- Enterprise-Ready — Built for Databricks with OAuth, workspace isolation, and scale in mind
- Extensible Toolkit — A rich library of tools, including Genie, MCP servers, custom APIs, and data connectors
- Real-Time Monitoring — Live execution tracking with detailed logs, traces, and performance insights
- Production-Grade — Robust error handling, retry logic, and enterprise deployment patterns
- Data Analysis Pipelines — Agents that query, analyze, and visualize your data
- Content Generation Systems — Collaborative agents for research, writing, and content creation
- Business Process Automation — Intelligent workflows that adapt and make decisions
- Customer Support Assistants — Multi-agent systems with specialized knowledge domains
- Research & Development — Agents that gather, synthesize, and present insights
Install directly from the Databricks Apps Marketplace with one click — the best path for production, with automatic updates and enterprise support.
Use the deployment script in this repository for custom installations. Ideal for tailored configurations and advanced setups.
A quick setup for testing and development — requires Python 3.9+ and Node.js.
The visual workflow designer for building AI agent collaborations
Create your first agent workflow in under two minutes:
- Design — Drag agents onto the canvas and define their roles
- Connect — Link agents together to form collaboration flows
- Execute — Hit run and watch your agents work as a team
- Monitor — Follow real-time logs and execution traces
| Topic | Description |
|---|---|
| Why Kasal | What problems it solves and who it's for |
| Solution Architecture | Layers, lifecycles, and platform integration |
| Code Structure | Where things live and how to navigate the repo |
| Developer Guide | Local setup, config, and extension patterns |
| API Reference | REST endpoints, payloads, and errors |
- Docs Hub - Documentation index
- End‑User Tutorial Catalog - Screenshot-ready walkthroughs
- Testing Guide - Testing strategy and coverage
Kasal follows a clean, layered architecture designed for scalability and maintainability:
Frontend (React) → API (FastAPI) → Services → Repositories → Database
The CrewAI engine plugs in at the service layer to drive intelligent agent orchestration.
Entity extraction in memory backends has known compatibility issues with:
- Databricks Claude (
databricks-claude-*) — JSON schema validation errors - Databricks GPT-OSS (
databricks-gpt-oss-*) — empty response errors
Automatic fallback: When these models are detected, Kasal transparently uses databricks-llama-4-maverick for entity extraction while keeping your chosen model for every other agent task.
Licensed under the Databricks License
Unlocking Databricks Marketplace: A Hands-On Guide for Data Consumers