Make vs Zapier: Which Is Better in 2026?

Last Updated: April 2026

"Make vs Zapier" is one of those questions where the answer most content will give you — "it depends!" — is technically correct and practically useless. So let's do better.

Make (the platform formerly known as Integromat, rebranded in early 2022 after its Celonis acquisition) and Zapier are the two gravitational centers of the iPaaS world. Between them, they power automations at a significant share of the small and mid-market SaaS economy. If you're reading this, you've probably already narrowed to these two. The question is which one, and why.

Here's the honest framing: the choice is less obvious than it looks. Zapier wins on surface area — more integrations, simpler onboarding, better marketing. Make wins almost every dimension that matters at scale — pricing, visual logic, error handling, power-user flexibility. Which one fits you depends on three things: how much volume you're running, how complex your workflows are, and how comfortable you are looking at a scenario diagram instead of a checklist.

We'll walk through pricing with real 2026 numbers, the UX gap on complex workflows, integration depth vs breadth, the state of AI features on each platform, and — if neither fits — where AI-native alternatives like Arahi AI change the shape of the problem.

Quick Verdict: Which to Pick

Short on time? Here's the bottom line.

If your situation doesn't fit cleanly into one of those rows, the rest of this article is for you.

The Feature Comparison Table

A side-by-side, no-spin feature comparison.

The biggest takeaways from this table: Zapier wins on breadth and approachability, Make wins on cost and flexibility, and AI-native platforms win on a different axis entirely — whether the workflow needs judgment, not just routing.

Pricing Deep Dive

This is where the rubber meets the road, and where most "it depends" comparisons lose their nerve. Let's do the math.

Zapier 2026 pricing

• Free — 100 tasks/month, single-step Zaps only.
• Professional — $29.99/month (annual) for 750 tasks. The real entry-level tier.
• Professional Plus — $73.90/month (annual), 2,000 tasks.
• Team — $103.50/month (annual), 2,000 tasks, unlimited users, shared workspace.
• Company / Enterprise — custom, starts ~$1,000/month for heavier volumes, SSO, SCIM.

Key wrinkle: Zapier counts each step that runs as a task. A 5-step Zap that fires once consumes 5 tasks. A 5-step Zap running 500 times a day consumes 2,500 tasks — every single day.

Make 2026 pricing

• Free — 1,000 operations/month, 2 active scenarios.
• Core — $10.59/month (annual) for 10,000 operations.
• Pro — $18.82/month (annual) for 10,000 operations, plus advanced features.
• Teams — $34.12/month (annual) for 10,000 operations, team collaboration.
• Enterprise — custom, starts around $500/month for high-volume and SSO.

Make counts each module invocation as an operation. A 5-module scenario running once consumes 5 operations. Same math — but Make's per-operation cost is a fraction of Zapier's per-task cost.

Worked example: 5-step workflow, 500 runs/day

Let's say you have a lead-routing workflow: webhook in → lookup in CRM → enrich via Clearbit → branch on score → post to Slack. Five steps, firing 500 times a day. That's 2,500 task/operation consumptions per day, or roughly 75,000 per month.

On Zapier, 75,000 tasks lands you well past Professional Plus (2,000 tasks) and into custom Company/Enterprise territory. Realistic cost: $600–900/month when you bundle in the volume discount on a high-task tier.

On Make, 75,000 operations fits comfortably into a higher Core or Pro tier. At Make's per-operation pricing, you're looking at roughly $25–60/month, depending on tier and any overage.

That's not a rounding error. That's a 10x-plus cost difference for the same workflow. Over a year, that's the difference between $300–700 and $7,200–11,000. If you're running any meaningful volume, this alone often decides the call.

The caveat: if your automations are simple, low-volume, and you value your setup time more than the monthly difference, Zapier's premium buys you faster time-to-working. Developer time is not free either.

Visual Builder: The Biggest UX Difference

This is the single biggest day-to-day difference between the two platforms, and it's the one most comparison articles under-sell.

Zapier's editor is a linear flow. You see a vertical list: trigger at the top, then step 1, step 2, step 3, each one a card you expand to configure. It's familiar — it looks like a to-do list or a recipe. It is great for one-path workflows. Add Paths (Zapier's branching feature) and the UX starts to bend: branches collapse into nested cards, and following the logic in your head requires clicking through several layers. Loops ("Looping by Zapier") live behind another card. You never really see the whole picture at once.

Make's editor is a canvas. Modules are circles connected by lines. Routers fan out visually into branches. Iterators loop back. Aggregators merge. You can see the whole scenario at a glance, zoom out to spot bottlenecks, and drag-reorder logic without collapsing anything. For anyone who's ever sketched a workflow on a whiteboard, Make's UI feels like that whiteboard became real. For anyone who prefers sequential checklists, it can feel overwhelming for about twenty minutes — and then click into place.

The practical impact: in Make, a 4-branch scenario looks like a 4-branch scenario. In Zapier, a 4-branch Zap looks like a deeply nested series of cards you have to hunt through. For complex workflows, this alone is a major quality-of-life win for Make.

What Zapier gets right: the first-time experience. A total beginner can build a Gmail → Slack Zap in under five minutes without ever reading documentation. Make will require at least a glance at a tutorial. That gap is closing — Make's onboarding is significantly better than Integromat-era Make — but Zapier still owns time-to-first-automation.

Integrations: Breadth vs Depth

The marketing headline: Zapier has 7,000+ integrations. Make has roughly 1,800+. That is a real difference, but it's also a misleading one.

Where Zapier's breadth matters: If you're automating against a long-tail SaaS tool — a niche CRM, a regional payment processor, a newer no-code app — Zapier is far more likely to have a pre-built integration. That's a meaningful advantage for solopreneurs, agencies working across many client stacks, and anyone whose tool surface is unpredictable.

Where Make's depth matters: For the core tools most teams actually use — Salesforce, HubSpot, Google Workspace, Slack, Airtable, Notion, Stripe, Shopify — Make's modules often expose a larger slice of the underlying API. More triggers, more actions, more fields. In practice, this means more things you can do without dropping to a custom HTTP module or webhook.

A concrete example: HubSpot. Zapier's HubSpot integration covers the common objects well. Make's HubSpot app tends to go deeper on custom objects, associations, and batch operations — which matter enormously when you're doing real CRM automation at scale.

Both platforms also support generic HTTP modules for anything not pre-built. Make's HTTP module is widely considered more flexible; Zapier's Webhooks by Zapier is friendlier but more limited.

Recommendation: before picking, list your 10 most important integrations and search both platforms' app directories. The theoretical difference between 1,800 and 7,000 matters less than whether your specific tools are supported well.

For a broader map of alternatives that extend beyond these two, our best Zapier alternatives 2026 guide walks through a dozen more options.

AI Features in 2026

Both platforms have been racing to integrate AI since 2023. As of April 2026, Zapier has a narrow but real lead.

Zapier's AI stack

• Zapier Agents — Went GA in 2025. Lets you describe a goal in natural language and have an agent plan and execute steps across your connected apps. Still template-heavy and more reliable on well-defined tasks, but legitimately useful.
• Zapier AI Actions — Exposes your Zapier-connected apps as tools that OpenAI, Anthropic, and Microsoft Copilot can call. Widely adopted in ChatGPT GPTs and Claude-based assistants.
• Copilot — An in-editor assistant that builds Zaps from natural-language descriptions. Decent at scaffolding, still needs human review.

Make's AI stack

• AI modules — First-party modules for OpenAI, Anthropic, Mistral, Hugging Face, and others. Well-built, but they're modules — primitives inside a scenario, not a higher-order abstraction.
• Make AI — An in-editor scenario-building assistant launched in 2024, improved through 2025. Comparable to Copilot, slightly less polished.

The honest read: both platforms treat AI as a new kind of step you can add to a workflow. Neither is AI-native. If your workflow fundamentally requires an agent that reasons about context and decides what to do — as opposed to a deterministic tree with an LLM call inside — you'll hit the limits of this approach fast.

That's the gap AI-native platforms were built to fill, and we'll come back to it below.

Error Handling and Reliability

Automation is only as useful as its failure mode. This is where Make and Zapier diverge most, after pricing.

Zapier handles errors at the platform level. When a step fails, Zapier auto-retries (with exponential backoff) up to a limit, then sends you an email and pauses the Zap. It's simple, non-technical, and works fine for common transient failures. The downside: when you need deterministic behavior — rollback, compensating actions, branching on specific error codes — you're largely out of luck. Error logic has to be simulated with filters and extra steps.

Make handles errors as first-class building blocks. Every module can have an error route — a visual branch that activates only when that module fails. You can catch specific error types, implement retry with custom logic, trigger rollback, or route failures to a human-review queue. For critical workflows (financial reconciliation, order fulfillment, data pipelines), this is the difference between "works most of the time" and "production-grade."

The tradeoff: Make's error handling requires you to think about failure modes explicitly. That's extra design work up front. For non-critical automations, Zapier's auto-retry is less work and perfectly adequate.

For a deeper look at how reliability scales in production automation, our enterprise workflow automation guide goes through the patterns that separate toy automations from real ones.

Enterprise Readiness

If you're evaluating for an organization with security and compliance requirements, the feature-gate landscape matters.

SSO — Zapier includes SAML SSO on the Team plan ($103.50/month starting tier). Make gates SSO to Enterprise. Advantage: Zapier for mid-market.

SCIM / user provisioning — Zapier's Company plan. Make's Enterprise. Even.

Data residency — Both offer US and EU data residency on higher plans. Make's EU-first origin means its EU footprint is more mature; Zapier has the broader region coverage.

Audit logs — Both platforms offer audit logs on enterprise tiers. Make's are more granular per-scenario; Zapier's are broader account-level.

Compliance certifications — Both hold SOC 2 Type II. Both support GDPR. Both offer HIPAA BAAs on enterprise tiers. Comparable.

Uptime SLAs — Zapier publishes a 99.9% SLA on Enterprise. Make publishes 99.9% on Enterprise. Both have had notable incidents in the last 18 months; neither is clearly more reliable.

Net: for enterprise buyers, Zapier's earlier SSO tier is a meaningful advantage. Make catches up at the top of the stack but gates more features higher.

For document-heavy workflows (contracts, invoices, compliance), our document workflow automation guide covers the patterns that matter.

When to Look Beyond Both: AI-Native Platforms

Here's the argument for stepping outside the Make-vs-Zapier frame entirely.

Both Make and Zapier are excellent iPaaS platforms. They were designed in the mid-2010s for a world where automation meant deterministic IF/THEN trees — trigger fires, steps run, data moves. That frame still works for a huge class of workflows: "when a form is submitted, add a row to a sheet and Slack the sales team." You don't need intelligence for that. You need plumbing. Both platforms are great plumbing.

But a growing share of what teams actually want to automate is not plumbing. It's judgment work:

• Read this inbound email, figure out which team should handle it, draft a response in our tone, and only escalate if the customer sounds frustrated.
• Look at this lead's activity across Salesforce, our product, and LinkedIn — decide whether they're sales-ready, and if so, hand off with a personalized note.
• Triage these 200 support tickets, cluster them by root cause, and draft a ticket for engineering on the ones that look like real bugs.

Try building any of these on a branching iPaaS flowchart and you'll end up with a 60-node tree you can't maintain. These are agent problems, not workflow problems.

This is where platforms like Arahi AI fit differently. Instead of modeling automation as a tree of IF/THEN nodes with an occasional LLM step, Arahi's primitive is a goal-directed AI agent. You describe what the agent should accomplish in natural language, connect it to your tools (1,500+ integrations, including the same CRMs, inboxes, and SaaS apps Make and Zapier support), give it a few guardrails, and let it reason its way through context and action each time it runs.

When a case comes in that doesn't fit the original design, the agent adapts. There's no tree to re-architect. For workflows where the inputs are messy, the right action depends on context, and maintaining a rigid flow would be a second full-time job, this shape of tool is a categorically different experience.

It's worth being clear-eyed about the tradeoff. Deterministic iPaaS is still the right choice when you need exact, repeatable behavior — especially for regulated or high-volume transactional workflows. AI agents are the right choice when the workflow would otherwise require a human to read context and decide.

If you want a detailed breakdown of where AI-native orchestration fits vs traditional iPaaS, the Arahi vs Zapier alternatives page walks through the head-to-head. For connected apps, the integrations directory shows what's supported natively.

For comparable analysis of Zapier against the open-source, self-hosted option, our n8n vs Zapier comparison covers that angle. If you're specifically in marketing, our marketing automation workflow examples lays out what good flows actually look like.

Verdict

Pick Zapier if: you're a solo operator, small team, or agency that values integration breadth, fast setup, and friendlier error messages over raw cost efficiency. Zapier will get you to a working automation in under an hour, will support almost every long-tail SaaS tool you might touch, and has the best AI features of any traditional iPaaS in 2026. Budget enough headroom for task usage to scale faster than you expect.

Pick Make if: you're a power user or operations team with meaningful workflow volume, branching logic, or error-handling requirements. Make is 30–50% cheaper at scale, has a visual editor that is genuinely better for complex scenarios, and handles failures as first-class building blocks. The learning curve is real but short — most teams are productive within a week.

Pick Arahi AI if: your workflows need judgment, not routing. If you find yourself building larger and larger trees of IF/THEN logic to cover edge cases, or wishing your automation could "just figure out" what to do with messy input, you're describing an agent problem, not a workflow problem. AI-native platforms solve a different-shaped problem than traditional iPaaS, and trying to force agent work into a Zap or a scenario will frustrate you long before it works.

For a real-time view of how this landscape is shifting, our workflow automation news tracker logs what changes and when.

Frequently Asked Questions

Is Make better than Zapier?

For visual workflow design, cost at scale, and power-user flexibility, Make (formerly Integromat) beats Zapier. For the fastest time-to-first-automation, broadest integration library, and easiest learning curve, Zapier wins. The better choice depends on volume, complexity, and technical comfort — not a blanket "better" answer.

What was Integromat?

Integromat was the original name of Make, founded in 2012 in Prague. It rebranded to Make in early 2022 after being acquired by Celonis. The product, team, and pricing model stayed largely the same; only the name and UI changed. Long-time Integromat users generally reported the rebrand as a visual and branding upgrade rather than a functional disruption.

Is Make cheaper than Zapier?

Yes, in almost every comparable scenario. Make prices per "operation" (each module run), and Zapier prices per "task" (each step that runs). A single Zapier task often equals multiple Make operations, but Make's per-unit price is far lower. For a 5-step workflow running 500 times per day, Make is typically 30–50% the cost of Zapier's equivalent plan. At very low volume, the absolute difference can be small and not worth the learning curve; at meaningful volume, Make often saves thousands per year.

Does Zapier have more integrations than Make?

Yes — Zapier lists 7,000+ integrations vs Make's roughly 1,800+. But the integration count is a misleading metric. Many of Zapier's apps have shallow action coverage (1–2 triggers, 1–2 actions), while Make's modules often expose deeper API surface on the tools most teams actually use daily. Check your specific stack on both platforms' app directories before choosing.

Can Make handle complex workflows better than Zapier?

Yes. Make was designed around a visual scenario builder with native branching (routers), iteration (iterators and aggregators), error handlers, and parallel paths. Zapier added branching (Paths) and looping (Looping by Zapier) later; the UX still lags. For workflows with complex logic or multiple branches, Make is noticeably more pleasant and less fragile to maintain.

Which has better AI features in 2026?

Zapier leads narrowly as of 2026. Zapier Agents (now GA) and Zapier AI Actions are more polished than Make's AI module ecosystem. Both platforms let you call OpenAI, Anthropic, and others via modules, but neither was designed from the ground up around AI agents — which is why AI-native alternatives like Arahi AI have emerged. If AI is central to your workflow rather than an add-on step, a purpose-built AI-native platform will generally outperform either.

What's the best alternative if neither Make nor Zapier fits?

For self-hosting and open-source flexibility: n8n (see our n8n vs Zapier comparison). For AI-native orchestration with goal-directed agents instead of rigid IF/THEN trees: Arahi AI. For enterprise iPaaS with heavy compliance needs: Workato or Boomi. See our full list of Zapier alternatives for a broader comparison, and the Arahi vs Zapier page for a detailed head-to-head.