Verified project record

superplanehq/superplane

SuperPlane orchestrates complex, multi-step engineering workflows across disparate tools with durable execution, operational guardrails, and human-in-the-loop controls for both human operators and AI agents. It supports a broad catalog of integrations spanning CI/CD, cloud providers, incident response, and communication tools.

Project overview

The platform tracks workflow runs and payloads across restarts so failed steps can resume without custom retry logic, providing deterministic execution guardrails for AI agents and humans to safely interact with connected systems.

Project type: Workflow
Deployment: Refer to project documentation
License: Apache-2.0

Best for

Operations teams, developers, and enterprise teams automating complex engineering workflows across disparate tools requiring durable execution and operational guardrails.
Teams requiring human-in-the-loop approvals, event-driven triggers via webhooks and schedules, and a dynamic operational UI for monitoring.

Key capabilities

Multi-step workflows across tools triggered by webhooks, schedules, and tool events with approvals and human-in-the-loop steps.
Per-app operational UI as a dynamic grid of panels to display KPIs, tables, charts, and workflow controls.
Tracks runs, run items, and payloads across restarts so failed steps can resume without custom retry logic.
JSON storage that persists across runs.
Per-app agent to design workflows and debug runs with CLI support.
RBAC and service accounts for API access, ensuring secure interactions.
Stores secrets encrypted.

Limitations and risks

SuperPlane is currently in beta, and breaking changes are possible.

Getting started

Setup is rated as easy due to a quick start path using a single Docker run command. You can pull the demo container, run it locally exposing port 3000, and access the platform via http://localhost:3000. Coding is optional for getting started.

Alternatives and comparisons

A fair-code platform to build and deploy AI agents and workflows with a visual canvas, custom code, and a broad integration catalog.
A platform providing a low-code interface to build, deploy, and manage continuous AI agents that automate complex workflows.
A lightweight, extensible AI assistant and agent harness that runs 24/7, supports multiple LLMs, manages long-term memory, and uses a built-in tool system.

Project comparisons

Evidence and sources

Open original GitHub project