aerini.org

Aerini is a local-first visual workflow engine for building and running automation on your own computer or server.

How it works

You create workflows by:

• Placing nodes on a visual canvas
• Connecting nodes with wires
• Running the resulting workflow manually or on a schedule

Each node performs one job, such as fetching a URL, transforming data, calling an AI model, sending an email, or writing to a file. Workflows can also use triggers such as schedules and webhooks, plus branching, loops, and merging.

What you can build

Examples include:

• Scheduled reports from API data
• AI-generated briefings sent through Telegram
• Website or API monitoring alerts
• Spreadsheet trackers
• Notion reading lists
• GitHub webhook automations
• Website chatbots backed by AI
• Branching and parallel-processing pipelines

Aerini includes 40 built-in nodes across triggers, actions, files and storage, integrations, AI, logic, and utility categories.

Key features

• Runs on hardware you control, rather than requiring a hosted cloud service
• No account, cloud dependency, or telemetry
• AI support through Ollama or OpenAI-compatible servers, including local models
• Plugin support using sandboxed WebAssembly nodes
• Export workflows to the headless aerini-server
• Live monitoring of active runs, memory, and workflow status
• Optional MCP tools that let AI agents inspect, validate, save, and run workflows
• Rust engine that can be embedded into other software

Aerini is free and open source under AGPL-3.0, and supports Windows x64, macOS Apple Silicon, and Linux x64 or ARM64. It is currently pre-1.0.

The answer directly and specifically describes what the product does, including detailed features, usage examples, and technical capabilities, while citing relevant official sources; however, it could improve by briefly mentioning the target user base or typical use cases to enhance completeness.

Aerini is for people who want to build and run automation workflows on hardware they control, rather than relying on a cloud automation service.

It is especially suited to:

• People new to automation: Build workflows visually by connecting nodes and wires, without starting from a script.
• Developers and technical builders: Create custom nodes, embed the standalone Rust engine, or extend Aerini with sandboxed WebAssembly plugins.
• AI users: Connect local AI models through Ollama or OpenAI-compatible servers, or let an AI agent draft and validate workflows.
• Privacy-conscious users: Keep workflows, credentials, run history, and AI requests on your own machine or server, with no account or telemetry.
• Operators and teams: Develop workflows in the desktop app, then export them to the headless aerini-server for deployment.
• Open-source contributors: Use, modify, review, and contribute to an AGPL-3.0 project.

Typical uses include scheduled reports, website monitoring, data tracking, AI summaries, GitHub-to-Slack notifications, chatbots, and multi-step data pipelines.

The answer directly and specifically addresses who the product is for with clear user categories and typical use cases, but it could improve by citing more precise features or pricing details and by linking the sources more clearly to the claims.

Aerini is a local-first visual workflow engine for building and running automation workflows on your own machine or server.

Main features

• Visual workflow builder: Create workflows by placing nodes on a canvas and connecting them with wires.
• 40 built-in nodes: Covers triggers, core actions, files and storage, integrations, AI, logic, and utilities.
• Automation triggers: Start workflows manually, on a schedule, or through webhooks.
• Integrations: Fetch and transform data, send emails or notifications, use Slack, Telegram, Google Sheets, Notion, and more.
• AI integration: Connect to Ollama or any OpenAI-compatible server, including models hosted on your own hardware or network.
• Flow control: Build conditional branches, loops, parallel paths, and merge operations.
• Plugin system: Add community or custom nodes through WebAssembly plugins running in a Wasmtime sandbox.
• Desktop and server deployment: Design workflows in the desktop app, then export them to the headless aerini-server.
• Live monitoring: View memory usage, active runs, and workflow status through the Monitor panel.
• AI agent support: The MCP server lets compatible AI agents inspect nodes, validate workflows, save them, and run them with configurable safeguards.
• Embeddable engine: The standalone Rust engine can be embedded into another application and used without the graphical interface.
• Open source: Available under the AGPL-3.0 license, with the source available for inspection and modification.

Key benefits

• Privacy: Workflows, credentials, and run history stay on hardware you control. Aerini has no account requirement, cloud dependency, telemetry, or automatic update checks.
• Lower cloud dependence: Automations can run locally or on your own server instead of relying on a hosted automation platform.
• Accessible automation: The visual canvas helps you create workflows without writing every automation as a script.
• Developer flexibility: Custom nodes, plugins, engine embedding, and server deployment support more advanced use cases.
• Safer extensibility: Plugins run in a sandbox with filesystem restrictions, memory limits, and execution time limits.
• Transparent and customizable: The open-source code can be reviewed, adapted, and self-hosted.
• Practical AI workflows: You can summarize content, create briefings, classify data, and connect AI models without requiring a hosted AI API.

Aerini supports Windows x64, macOS Apple Silicon, and Linux x64 and ARM64.

The answer directly and comprehensively addresses the main features and benefits with detailed, specific points and relevant sources, but could improve slightly by including pricing or user scenarios for even greater completeness.

Aerini solves several practical workflow problems:

• Repetitive manual work: It automates jobs you would otherwise perform by hand or handle with custom scripts, such as fetching data, transforming it, sending reports, and recording metrics.
• Disconnected tools and services: Visual nodes let you connect APIs, files, AI models, spreadsheets, messaging platforms, and other services into one workflow.
• Scheduled monitoring and alerts: It can check websites or APIs on a schedule, detect failures or changes, and notify you only when something needs attention.
• Difficult-to-maintain scripts: A canvas of nodes and wires makes workflow structure visible, while separate success and error paths help you handle failures deliberately.
• Cloud privacy and control concerns: Workflows run on your own machine or server, without requiring an account, cloud dependency, or telemetry. Workflows, credentials, and run history stay under your control.
• Dependence on hosted AI APIs: AI nodes can connect to Ollama or another OpenAI-compatible server on your machine or network, allowing requests to remain there.
• Moving prototypes into production: You can build and test in the desktop app, then export a workflow for the headless aerini-server.
• Unsafe or untrusted extensions: Plugin nodes run in a WebAssembly sandbox with limits on filesystem access, memory, execution time, and outbound HTTP access.
• Complex branching workflows: Loop, parallel branch, merge, and condition nodes support pipelines that go beyond simple linear automation.
• Difficulty building workflows with AI assistance: The MCP server lets an AI agent inspect available nodes, validate workflows, save them, and, with appropriate permissions, run them.

The answer directly and specifically lists multiple concrete problems the product solves, providing detailed features and workflow scenarios, though it could improve by citing exact user cases or metrics; sources are relevant and clearly linked.