Activepieces is the open-source automation platform that's closest to a self-hosted Zapier. It has a visual builder, 670+ community-contributed integrations, and you can run the whole thing on your own Docker host with zero per-task fees. For developers and technical ops teams who want to own their automation infrastructure completely, Activepieces is a strong, transparent choice.
The gap is in AI-native capabilities and team operations. Activepieces added AI steps and an MCP gateway, but the core experience is still a visual node builder designed for deterministic pipelines. There's no way to describe a workflow in plain English and have it built for you. And while you can self-host Activepieces, that means you're also managing Docker, updates, and infrastructure, which is a different proposition than a managed platform with self-hosted deployment.
How they compare
| General Input | Activepieces | |
|---|---|---|
| Natural language workflow building | ||
| Open source | ||
| Visual drag-and-drop builder | ||
| Built-in integrations (300+) | ||
| AI agent workflows with tool use | ||
| Apps + deterministic scripts + AI agents | ||
| Built for non-technical users | ||
| Per-execution cost transparency | ||
| Team workspaces with fine-grained permissions | ||
| Credential encryption isolated from AI | ||
| Self-hosted / on-prem deployment | ||
| MCP server support |
When to use Activepieces
Activepieces is the right choice for technical teams that want full ownership of their automation stack. If you have developers comfortable with Docker, want to contribute custom TypeScript integrations back to the community, or need to expose automation workflows as MCP servers for AI agents, Activepieces gives you a capable open-source foundation at zero marginal cost per execution.
When to use General Input
General Input is for teams that want production automation without managing infrastructure or limiting who can build.
- Non-technical users build workflows. Activepieces requires understanding the visual builder, data mapping, and piece configuration. General Input lets anyone describe what they need and deploy it.
- Three workflow types, one dashboard. Activepieces does visual flows with AI steps bolted on. General Input runs app integrations, deterministic code scripts, and autonomous AI agents in the same workspace with unified monitoring and permissions.
- Cost visibility without infrastructure work. Every General Input execution shows its dollar cost, broken down by model and integration. Activepieces doesn't track execution costs, and self-hosting means estimating your own compute costs.
- Managed self-hosting. General Input's on-prem deployment is a managed offering where the team works with you on setup and updates. Activepieces self-hosting means you own the Docker infrastructure, the upgrades, and the debugging.
- Security architecture. Credentials are encrypted at rest and in transit, isolated from LLM context, with full audit logging. Activepieces stores credentials but the credential-to-AI isolation boundary is less defined.
Better together
Activepieces gives you an open-source engine you fully control. General Input gives you an AI-native platform where non-technical teammates build workflows and every run is tracked. Use Activepieces for developer-owned, community-extensible pipelines, and General Input for the team-facing automation layer on top.