Activepieces vs Make

Side-by-side comparison of features, pricing, and ratings

Analysis reviewed Live tool data as of 2026-09-29
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At a glance

DimensionActivepiecesMake
PricingFree (1 person), paid plans for builders/teamsFreemium (paid tiers scale with operations)
Integrations700+ apps, including Gmail, OpenAI, Slack, Notion, HubSpot, MCP3,000+ apps, including OpenAI, HubSpot, Salesforce, Slack, Canva
AI FeaturesAI agents with custom instructions, agent library (Lead Scorer, etc.), chat-to-automation, analyticsMake AI Agents, Library of Agents, MCP Server
DeploymentCloud (SOC 2 Type II) or self-hosted (Docker, Helm)Cloud (GDPR, SOC 2, SOC 3)
Best forAI-first teams, cost-conscious, self-hosting needsComplex workflows, broad app ecosystem, enterprise orchestration

If your priority is AI agent automation on a budget with self-hosting flexibility, pick Activepieces. If you need the widest integration library and advanced workflow logic (routers, iterators) across a massive app ecosystem, Make is your safer bet. Both are solid, but Activepieces leans into AI-first innovation while Make excels in general-purpose automation scale.

Try ActivepiecesTry Make
Activepieces
Activepieces

Open-source AI automation platform: build workflows and AI agents visually, no code.

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Make
Make

Visual AI automation platform for building workflows and AI agents across 3,000+ apps

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Pricing
Freemium
Freemium
Plans
$0
$16/mo (billed yearly)
$166/mo (billed yearly)
Custom
$0/mo
$9/mo
$16/mo
Custom
Popularity
3.8k views
4.8k views
Skill Level
Beginner-friendly
Intermediate
API Available
Platforms
WebAPI
Web
Categories
🤖 Automation & Agents🕸️ Agent Frameworks & Orchestration
🤖 Automation & Agents
Features
Chat-to-automation: describe a workflow in plain words and get a drafted flow
Drag-and-drop visual workflow builder with branching, retries, waitpoints, subflows, error handling
760+ open-source integrations (pieces) including Gmail, OpenAI, Slack, Notion, HubSpot
AI agents with custom instructions, tools, and human approval gates
Tables for storing data every flow and agent can read and write
MCP server to connect agents to Claude, ChatGPT, Cursor, GitHub Copilot, Gemini
HTTP piece to call any REST or GraphQL API with auth and pagination
TypeScript code step for the hardest steps
Human approval gates to control steps that touch money, customers, or production
Impact analytics: track hours saved, adoption, cost savings
Project-based isolation for teams and clients
SSO (Okta/Entra), standard or custom roles, audit logs, secret managers
Credits model: one credit per run, AI steps cost extra (2, 10, or 20 credits)
Self-hosting via Docker or Kubernetes, including air-gapped deployments
Cloud hosting in EU, US, or other regions on request
Drag-and-drop scenario builder for visual workflow design
3,000+ pre-built app connectors plus custom API actions
Routers, filters, aggregators, and iterators for data transformation
Make AI Agents that take action across connected apps
Library of ready-made AI agents to deploy and adapt
Make MCP Server linking AI models to business actions
Maia by Make: build automations and agents via natural conversation
Build by prompt, drag-and-drop, or via MCP
Agentic automation that adapts in real time to business needs
Make Grid for managing your whole automation landscape visually
Error handling with rollback
Real-time execution logs and monitoring
Sub-scenarios for modular workflow design
Data stores for persistent workflow state
Enterprise security: SSO, encryption, GDPR, SOC 2 Type II, SOC 3
Integrations
Slack
Gmail
HubSpot
OpenAI
Notion
Snowflake
QuickBooks
Stripe
HubSpot CRM
monday.com
NetSuite
Salesforce
Canva
Perplexity AI
DeepSeek AI

What real users say: Activepieces vs Make

Not marketing copy and not our opinion — a structured sweep of public discussion (reviews, forums, communities and video comments), showing what people praise and what they complain about for each tool.

Activepieces

62 mentions across 4 sources · 76% positive (averaged across 4 sources)

Hacker News, YouTube, Product Hunt, GitHub

What users praise

  • • True open-source license (MIT) allows free use in commercial apps
  • • Drag-and-drop builder is praised for being easy and intuitive
  • • Active and responsive team; feature requests implemented in a day
  • • Very competitive pricing compared to Zapier and n8n

What frustrates them

  • • Advanced features are gated behind paid tiers, limiting open-source claim
  • • Fewer integrations than rivals (700 vs n8n's 1000+)
  • • Community edition lacks some power features, pushing users to paid plans
  • • Some users find n8n's workflow capabilities more advanced for complex automation

Researched Aug 21, 2026

Make

94 mentions across 7 sources · 31% positive — critical (averaged across 7 sources)

Hacker News, YouTube, Product Hunt, App Store, Stack Overflow, Lemmy, Tech Press

What users praise

  • • Powerful drag-and-drop workflow builder with routers, filters, and iterators.
  • • Deep customization beyond Zapier, letting users fine-tune data transformations.
  • • 3,000+ app integrations covering major business tools like Slack and OpenAI.
  • • Sub-scenarios and modular design keep complex automations organized.

What frustrates them

  • • Mobile app crashes repeatedly and lacks core scenario management.
  • • Learning curve is steep for non-technical users, despite 'easy' marketing.
  • • Support response times can be extremely slow, with tickets sometimes ignored.
  • • Name 'Make' is too generic, causing confusion about what it does.

Researched Aug 18, 2026

Feature-by-feature

Activepieces is an AI-first platform with a drag-and-drop builder, human approval steps, and chat-to-automation, making it easy to create AI agents with custom instructions. It includes an agent library (Lead Scorer, Deal Closer) and built-in analytics, gamification, and leaderboards to drive adoption. Self-hosting via Docker/Helm gives data control. Make offers a visual scenario builder with routers, filters, aggregators, iterators, and sub-scenarios for intricate logic. It has 3,000+ integrations, error handling with rollback, real-time monitoring, and data stores. Make's AI agents adapt in real time, and its MCP Server links custom actions. Activepieces integrates with MCP too, but Make's integration breadth (3,000 vs 700) is a clear advantage for teams needing niche apps. However, Activepieces' chat-to-automation and agent-centric features are more AI-forward, while Make's strength is complex data transformation and modular workflows. Both support webhooks, scheduling, and team collaboration, but Activepieces also offers SSO, SCIM, and RBAC; Make offers enterprise security compliance (GDPR, SOC 2/3).

Pricing compared

Both are freemium. Activepieces starts free for one person, with paid plans for builders and teams—pricing is lower than Make, especially for AI capabilities, as per its positioning against Zapier/Make. Make has a free tier, but its paid plans scale with 'operations' (tasks executed), which can get costly at high volumes. Activepieces' cost advantage is a key selling point, especially for teams diving into AI automation. However, if you need 3,000+ integrations, Make's pricing might justify itself despite the higher cost. Neither lists exact prices in the data, so evaluate based on your expected volume and AI usage. Self-hosting with Activepieces can reduce per-seat costs for enterprises.

Who should pick which

  • Sales team wanting AI lead scoring
    Pick: Activepieces

    Activepieces includes a Lead Scorer agent, chat-to-automation, and human approval steps—ideal for sales teams that want AI without coding.

  • Marketing team automating multi-channel campaigns
    Pick: Make

    Make's 3,000+ integrations (including Canva, Salesforce) and complex data transformation allow building deep, cross-platform workflows easily.

  • Enterprise with strict data compliance
    Pick: Activepieces

    Self-hosting via Docker/Helm gives full data control; also supports SSO, SCIM, and advanced RBAC for enterprise governance.

  • IT team automating incident response
    Pick: Make

    Make's real-time execution logs, error handling with rollback, and webhook triggers enable reliable monitoring and response automation.

  • Cost-conscious startup exploring AI agents
    Pick: Activepieces

    Activepieces is positioned as a lower-cost alternative to Zapier/Make with advanced AI features; free tier supports one person to start.

Frequently Asked Questions

Activepieces vs Make: which should you choose?

If your priority is AI agent automation on a budget with self-hosting flexibility, pick Activepieces. If you need the widest integration library and advanced workflow logic (routers, iterators) across a massive app ecosystem, Make is your safer bet. Both are solid, but Activepieces leans into AI-first innovation while Make excels in general-purpose automation scale.

Can I self-host Make like I can with Activepieces?

The data doesn't mention self-hosting for Make; it's cloud-based with compliance certifications. Activepieces explicitly offers self-hosting via Docker and Helm.

Which platform has more integrations?

Make connects to 3,000+ apps, while Activepieces has 700+. If you rely on niche apps, Make's broader ecosystem is a major factor.

Do both support AI agents?

Yes. Activepieces has AI agents with custom instructions and a library of agents, while Make offers Make AI Agents with real-time adaptation and MCP Server integration.

Are there human approval steps in Make?

The data for Make doesn't list human approval steps; Activepieces highlights them as a feature for controlled automation.

Which is better for a non-technical user?

Activepieces emphasizes drag-and-drop and chat-to-automation, making it accessible. Make's complexity with routers and iterators might be overwhelming for beginners.

How do the pricing models differ?

Both have free tiers, but Activepieces claims lower cost overall, especially for AI. Make's pricing scales with operations, which can increase costs at high volumes.

More Activepieces or Make comparisons

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If your goal is to automate cross-app business processes (CRM, email, databases), Make is the clear choice with its 3,000+ connectors and visual logic. If you want to build a functional web or mobile

Make vs Zapier comparison

If you want visual control over complex, multi-step logic and have some technical comfort, Make is the better buy. If you prioritize sheer app count, minimal learning curve, and AI-assisted workflow g

Activepieces vs Zapier comparison

If you're AI-forward, cost-sensitive, or need on-prem compliance, Activepieces wins—it's cheaper, open-source, and ships built-in agent orchestration. But if you live off sheer app breadth (9,000+ int

Activepieces vs n8n comparison

Pick Activepieces if your buyers are non-engineers and you need AI agents with human approval gates running without anyone touching a terminal — the chat-to-workflow drafting and per-step approval gat

Explore each tool further

Activepieces
View Activepieces reviewActivepieces alternatives
Make
View Make reviewMake alternatives

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Last reviewed: August 19, 2026