Activepieces vs AI by Zapier

Detailed side-by-side comparison to help you choose the right tool

Activepieces

Automation

An AI-first automation platform designed for teams to streamline workflows and processes.

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Starting Price

Custom

AI by Zapier

Automation & Workflow

AI-powered automation platform that connects AI capabilities with 8,000+ apps to automate workflows and analyze data across various business applications.

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Starting Price

Custom

Feature Comparison

Scroll horizontally to compare details.

FeatureActivepiecesAI by Zapier
CategoryAutomationAutomation & Workflow
Pricing Plans8 tiers8 tiers
Starting Price
Key Features
  • â€ĸ AI agents with custom instructions and tools
  • â€ĸ Visual drag-and-drop flow builder
  • â€ĸ 689+ native integrations
  • â€ĸ AI-powered text analysis and data extraction within Zaps
  • â€ĸ Integration with 8,000+ apps
  • â€ĸ No-code workflow builder with AI steps

💡 Our Take

Choose AI by Zapier if you want a mature, proven platform with the largest integration library and enterprise support. Choose Activepieces if you're a startup or small team that wants an open-source, self-hostable alternative with no per-task fees, need to keep automation data on your own infrastructure for compliance reasons, or want to build custom pieces without vendor lock-in.

Activepieces - Pros & Cons

Pros

  • ✓Flat-rate pricing with $0 per execution means millions of runs cost the same as thousands — highly predictable at scale
  • ✓689+ native integrations including Gmail, OpenAI, Slack, Notion, and HubSpot cover most mainstream SaaS needs
  • ✓Open-source and self-hostable via Helm or Docker, so data can stay inside your network with no vendor lock-in
  • ✓Enterprise governance is built in: SAML SSO, SCIM, RBAC, and audit logs come without third-party add-ons
  • ✓Handles multi-step logic and branching more cleanly than Zapier, according to G2 and Trustpilot reviewers migrating from competitors
  • ✓SOC 2 Type II and GDPR compliant managed cloud with EU and US data regions for regulated industries

Cons

  • ✗Smaller integration catalog than Zapier's 7,000+ apps — niche or long-tail SaaS tools may require custom pieces
  • ✗AI agent tooling is newer than the underlying automation engine, so advanced agent patterns may still be maturing
  • ✗Self-hosting requires DevOps capacity to manage Helm charts, workers, and upgrades
  • ✗Documentation and community are smaller than Zapier or Make, so troubleshooting edge cases may take longer
  • ✗Paid tier pricing (Pro, Platform, Enterprise) is not published on the website — all require a sales conversation to get a quote, making it difficult to compare costs before committing to a demo

AI by Zapier - Pros & Cons

Pros

  • ✓Connects AI processing to 8,000+ apps — the largest integration library of any automation platform, far surpassing competitors like Make (1,800+) or n8n (400+)
  • ✓Zero coding required to build sophisticated AI-powered automations, making it accessible to non-technical marketing, sales, and ops teams
  • ✓AI is embedded natively as a Zap step, so it chains seamlessly with triggers and actions from other apps without API configuration
  • ✓Free tier includes 100 tasks/month with AI access, allowing meaningful testing before committing to a paid plan
  • ✓Expanding AI product suite (Agents, Chatbots, MCP, Canvas) provides a growing ecosystem rather than a single-purpose AI feature
  • ✓Enterprise-grade security with SOC 2 compliance and SSO support makes it suitable for regulated industries

Cons

  • ✗Task-based pricing can become expensive at scale — heavy users running thousands of AI-enhanced Zaps monthly may find costs escalating quickly beyond the base plan
  • ✗AI capabilities are limited to text-based operations (analysis, generation, extraction) — no image, audio, or video AI processing is available natively
  • ✗Free plan is restricted to two-step Zaps, which severely limits the complexity of AI workflows you can build without upgrading
  • ✗AI by Zapier's model and prompt capabilities are less transparent and customizable than using dedicated AI platforms like OpenAI or Anthropic directly
  • ✗Debugging complex multi-step AI Zaps can be difficult, as errors in AI output propagate through subsequent steps with limited visibility into intermediate results

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