Overview:
Bubble Lab is an open-core workflow engine that serves as the infrastructure for a Slack-native AI operator platform. It is designed to help teams automate operational tasks directly within Slack using an AI assistant. This repository contains the core execution runtime that can be run, hosted, and extended independently, allowing developers to build and execute custom workflows locally. The engine is suitable for teams using the managed Bubble Lab platform, developers seeking full control over workflow execution, organizations needing self-hosted automation, and engineers building custom agents.
Core Features:
Workflow execution runtime: A fully functional engine that executes workflows, including tracing, logging, and observability.
Agent and integration primitives ("Bubbles"): Pre-built components that serve as nodes for workflows, such as tools for scraping or AI analysis.
Local workflow studio: A graphical interface accessible via a local URL for building, editing, and running workflows.
Exportable workflows: The ability to package and deploy workflows created in the studio to other environments.
CLI tooling: A command-line interface for scaffolding new projects with pre-configured TypeScript setups and sample workflow templates.
TypeScript support: Full type safety and proper interfaces for building workflows.
Use Cases:
Teams automating operational work: Automate recurring tasks and system access directly within Slack using the AI operator without switching between tools.
Developers building and testing custom workflows: Use the local studio and runtime to create, edit, and debug workflows before deployment.
Organizations requiring self-hosted automation infrastructure: Host the entire workflow engine on their own infrastructure for data control and custom deployment.
Engineers embedding workflows into products: Use the exportable engine and primitives to integrate Bubble Lab workflows into proprietary applications.
Why It Matters:
As an open-core project, Bubble Lab provides transparency into its core workflow execution engine, which is also used internally by its commercial platform. Its modular design allows for independent hosting, local development, and direct extension through TypeScript, without requiring use of the managed service. The engine includes production-ready features like error handling and performance tracking, making it a practical foundation for teams and developers who need a customizable, self-hosted automation layer rather than a fully managed AI assistant alone.
