Activepieces

Activepieces is an open-source AI automation platform that competes with Zapier and Make.com. Built in 2022, it offers a visual workflow builder with 200+ app connectors and native AI agent steps that call language models directly inside flows. The MIT license means you can self-host it for free with no per-task fees and no vendor lock-in. A hosted cloud option is available for teams that don't want to run infrastructure. AI capabilities go beyond simple LLM calls: you can build multi-step AI agents, add human review checkpoints, and embed AI reasoning into otherwise standard automation workflows.

Activepieces came out of a straightforward frustration: Zapier's per-task pricing becomes expensive quickly, and there wasn't a clean open-source alternative with modern UX and native AI capabilities. The team building Activepieces had used Make.com and n8n and wanted something that felt more like a product and less like a developer tool, while still being open enough to self-host.

The GitHub repository launched in late 2022 and picked up traction quickly in the technical community. By 2024-2026 the platform had grown to a substantial number of deployments and a connector library that covers most common enterprise applications.

The core workflow experience

Activepieces uses a standard visual flow builder. Workflows start with a trigger: a form submission, a new record in a database, a webhook from an external service, or a schedule. Triggers connect to action steps: send an email, update a spreadsheet, create a CRM record, call an API.

The interface is clean. Connecting a new app takes finding it in the connector list and authenticating. Most major business applications are there: Slack, Google Sheets, Notion, HubSpot, Salesforce, GitHub, and a long list of others. The connector library is community-extended, which means coverage can be uneven, but the core apps are solid.

Where Activepieces earns its place in an AI tools directory is in what happens when you insert an AI step into a flow.

AI agent steps

The AI step types are first-class workflow components with their own configuration panel. You select your AI provider (OpenAI, Anthropic, Google Gemini, and others), pick the model, write your system prompt, and define what the step should do with the data passing through the flow.

A practical example: you have a flow that watches a Typeform for new customer feedback submissions. The feedback text comes in, hits an AI step configured to classify sentiment and extract the key complaint category, and the output routes to a Slack notification with the classification or to a support ticket creation depending on the result. No code. The AI reasoning is embedded in the workflow.

A more complex example: an AI step with a structured output schema that extracts specific fields from an incoming document, followed by a conditional branch based on extracted values, followed by a human-in-the-loop step that emails a reviewer the AI's extracted values and waits for confirmation before proceeding to write the record to the database. This is a complete AI-assisted data pipeline with human review, built entirely visually.

The flexibility to insert AI steps anywhere, chain multiple AI steps, and combine them with conditional logic and human review steps is what distinguishes Activepieces from platforms where AI is limited to a single GPT "action" type.

Self-hosting

The self-hosted deployment runs on Docker. The typical setup is a docker-compose file that brings up the Activepieces application, a PostgreSQL database, and a Redis cache. If you've done any containerized deployment, it's straightforward. The docs cover both simple single-server setups and higher-availability configurations.

Once running on your own infrastructure, there are no licensing fees, no per-task charges, and no data leaving your network unless your flows deliberately send it to external services. For organizations with data governance requirements, healthcare data, or simply the kind of sensitive business data that shouldn't flow through third-party automation services, self-hosting is the clean answer.

The tradeoff is that you own the operations: updates, monitoring, backups. For teams with existing devops practices, this is routine overhead. For teams with no infrastructure experience, the cloud-hosted option is the practical path.

Connector quality

The 200+ connector library is broad but uneven. Core integrations for high-traffic apps like Slack, GitHub, Notion, and Google Workspace are reliable and regularly maintained. Less common connectors, particularly those maintained primarily by community contributors rather than the core team, can have gaps or lag behind API changes from the target service.

This is a normal characteristic of open-source connector libraries. Compare the connectors you need specifically, not the total count. If you're automating workflows for the top 20 business apps, Activepieces coverage is solid. If you need a specific niche app, check whether its connector is actively maintained.

Custom HTTP request steps mean you can call any API that isn't natively covered. This requires knowing the API you're calling, but for technical teams it's a straightforward fallback.

Comparing to Zapier and Make.com

Against Zapier: Zapier has more reliable connectors, a larger template library, and better non-technical user experience polish. Activepieces has dramatically better pricing for self-hosted, native AI steps, and no vendor lock-in. For teams that need to ship automation with AI reasoning at the center, and who have some technical capacity, Activepieces is the more economical and capable option.

Against Make.com: Make has powerful visual routing and a long track record. Activepieces has cleaner UX, open source, and better AI integration. Both have been improving their AI capabilities. Make's pricing is also scenario-based rather than task-based, which is more predictable than Zapier but still a cost at scale that Activepieces self-hosted avoids.

Against n8n: Closest comparison in the open-source automation category. n8n has a larger community and more templates. Activepieces has a more accessible UI for non-technical users and more opinionated AI step design. Both are good; the choice often comes down to which community you find more useful for your specific integration needs.

Getting started

The hosted free tier at activepieces.com is the zero-friction starting point. Create an account and build a flow that connects two apps you already use. The experience of building a working automation in 10-15 minutes is the product's best sales pitch.

For self-hosting evaluation, the documentation at docs.activepieces.com has a Docker Compose quickstart that gets a local instance running in under 30 minutes for most developers. Test with low-stakes flows before migrating anything critical.

The AI step types are worth testing specifically. Build a flow that includes an AI classification or extraction step and see how the structured output integrates with downstream steps. That combination is the core differentiator and the clearest reason to choose Activepieces over a standard no-AI automation platform.

Key features

• Visual workflow builder with 200+ pre-built connectors for popular apps
• AI agent steps that call OpenAI, Anthropic, and other LLMs inside flows
• Open-source under MIT license with full self-hosting support
• Human-in-the-loop approval steps for workflows requiring human review
• Custom JavaScript and TypeScript code steps inside flows
• Webhook triggers for event-driven automation
• Team collaboration with role-based access for shared workflows

Pros and cons

Who is Activepieces for?

• Teams that want Zapier-like automation without per-task pricing
• Developers embedding AI reasoning steps into business process automation
• Organizations with data privacy requirements that rule out cloud automation
• Startups building internal tooling with AI agents at the center of workflows

Alternatives to Activepieces

If Activepieces isn't quite the right fit, the closest alternatives are zapier-agents , n8n , and make-com . See our full Activepieces alternatives page for side-by-side comparisons.