Make Review 2026: Visual Automation Platform for AI Workflows — Honest Hands-On Test

TL;DR

Make (formerly Integromat, acquired by Celonis) is a visual automation platform that lets non-developers build multi-step workflows — called “scenarios” — by dragging and connecting app modules on a visual canvas. Pricing starts free at $0/month (1,000 credits), with paid plans from $9/month (Core, 10k credits) up to Teams at $29/month (50k credits) [1]. The visual builder is best-in-class for complex branching logic, and the 2026 additions — AI agent builder, Maia AI assistant, GPT-5.2 and Claude Opus 4.8 modules — make it the strongest mid-market pick for teams that outgrew Zapier but don’t want to self-host n8n. The tradeoffs: credit-based billing can surprise you on data-heavy scenarios, the learning curve is steeper than Zapier, and the app catalog (3,000+) is smaller than Zapier’s 7,000+. Verdict: 8.5/10 — best visual automation tool for mid-complexity AI workflows.

What Is Make?

Make is a cloud-based visual automation platform that lets you connect apps and services through a drag-and-drop interface. You build “scenarios” — multi-step workflows that move data between applications, transform it, run conditional logic, and trigger actions based on events or schedules.

Make started as Integromat in 2016, earned a strong reputation for complex visual workflows, and was acquired by Celonis (the process mining unicorn) in 2021. The rebrand to “Make” happened in 2023, and the platform has since added AI capabilities: native AI modules (GPT-5.2, Claude Opus 4.8), a dedicated AI Agent Builder, and Maia — Make’s built-in AI assistant for designing and debugging scenarios [2].

What sets Make apart from Zapier and n8n is the visual scenario editor. Instead of configuring triggers and actions through forms and dropdowns, you build on a visual canvas where you can see the data flow between modules, route data conditionally using routers, aggregate results, and iterate arrays — all without writing a line of code.

Who it’s for: Operations managers, marketing teams, and SMBs building medium-to-complex automations. If Zapier feels limiting but you can’t justify the DevOps overhead of n8n, Make sits right in the middle.

Key Features

Visual Scenario Editor

Make’s core is its visual canvas. You build workflows by dragging modules onto a grid, connecting them with lines, and configuring each module with fields and dropdowns. The editor shows live data flowing through each step during testing — you can see exactly what data shape each module outputs before wiring it into the next step [4].

Key canvas features:

Routers — branch workflows based on conditional logic (if/then/else)
Iterators — process arrays of data item by item
Aggregators — collect results and combine them
Filters — skip messages that don’t match criteria
Error handlers — define what happens when a module fails

The canvas updates in real-time. You can add breakpoints, inspect data bundles at each stage, and replay failed executions after fixing the issue.

AI Modules and Agent Builder

Make offers three AI tools in 2026:

AI modules — pre-built connectors for OpenAI (GPT-5.2, GPT-4.1), Anthropic (Claude Opus 4.8, Sonnet 4.8), and custom AI providers (all paid plans). You can prompt these models directly inside workflows: generate text, summarize data, classify content, extract structured fields from unstructured text [2].
Maia AI Assistant — Make’s native chatbot for asking questions about your scenarios. Maia can explain a complex scenario, suggest performance improvements, help debug failures, and auto-generate simple scenarios from a description. It’s available on all plans (75 messages/month free, up to 400 on Teams) [5].
Agent Builder — launched in early 2026, this lets you compose agent graphs visually — connecting AI models, tools, and guardrails on a canvas. Agents can call webhooks, query databases, search the web, and orchestrate multi-step reasoning tasks. It’s Make’s answer to the agentic workflow trend [7].

3,000+ App Connectors

Make connects with 3,000+ apps across categories:

CRM: HubSpot, Salesforce, Pipedrive
Marketing: Mailchimp, ActiveCampaign, Google Ads
Productivity: Google Workspace, Microsoft 365, Notion, Slack
Databases: Airtable, Google Sheets, MySQL, PostgreSQL
Files: Google Drive, Dropbox, Box, SharePoint
Social: Facebook, Instagram, LinkedIn, X/Twitter

Each app has pre-built modules for its most common operations — Create Record, Search, Update, Delete — so you don’t need to build API calls from scratch. You can also use HTTP and Webhook modules for custom integrations.

Scheduling and Execution

Scenarios can trigger on a schedule (every 5 minutes to monthly), from webhooks, or when an app emits an event. Execution timeout is 15 minutes on Core, with longer timeouts on higher plans. You can also set data retention for execution history — from 30 days (Core) to unlimited (Enterprise).

Data Stores

Make includes built-in data storage — key-value data stores that persist data between scenario runs. You can store counts, flags, session tokens, or reference data without connecting to an external database. Data store sizes range from 10 MB (Core) to 500 MB (Teams).

Pricing

Make moved to a credit-based billing system in late 2025 [6]. Credits replace the old “operations” model — every module execution, data transfer operation, and AI call consumes credits.

Plan	Monthly Price	Annual Price	Credits/Month	Key Limits
Free	$0	$0	1,000	15-min timeout, 1 active scenario, 100 MB data transfer
Core	$10.59/mo	$9/mo ($108/yr)	10,000	Unlimited active scenarios, 5 GB data transfer, 30-day history
Pro	$18.82/mo	$16/mo ($192/yr)	20,000	Priority execution, 10 GB transfer, 60-day history
Teams	$32.94/mo	$29/mo ($348/yr)	50,000	20 GB transfer, 90-day history, advanced permissions
Enterprise	Custom	Custom	Custom	SSO, SLA, unlimited history, dedicated support

[Source: make.com/en/pricing — accurate as of June 2026] [1]

Credit costs vary by action:

Simple module (e.g. “Get Record”): ~1 credit per execution
AI module call: 5–20 credits per execution depending on model
Data operations (aggregate, iterate): variable based on data volume
Extra credits cost: $0.001 per credit (Core) if you overrun

The credit system is Make’s biggest pricing criticism. A single scenario with an AI module processing 1,000 records could consume 5,000–20,000 credits in one run. The Free plan is genuinely useful for testing, but production AI workflows almost certainly need Pro or Teams.

Annual billing saves ~15% across all paid plans. Make also offers an extra 50,000-credit add-on pack for $39/month on Teams plans.

Ease of Use

Make has a steeper learning curve than Zapier but a gentler one than n8n. Building a simple two-step workflow (e.g. new Gmail email → save to Google Sheets) takes about 5 minutes — comparable to Zapier. The difficulty ramps when you add routers, iterators, and error handling.

The visual canvas is Make’s biggest advantage over form-based tools. Seeing the data flow between modules makes it easier to understand what’s happening when something breaks. The “Run once” button lets you test with live data immediately, and the execution inspector shows every module’s input and output.

Maia helps here — you can ask “why did this scenario fail?” and get a readable explanation with a suggested fix. That’s a genuine time-saver for new users.

Starter tip: Use the template library. Make has 5,000+ pre-built scenario templates for common use cases. Start from a template and customize rather than building from scratch.

Pros & Cons

Pros

Best-in-class visual canvas for complex branching workflows — routers, iterators, aggregators make multi-step logic manageable without code
AI capabilities are practical — the AI modules for GPT-5.2 and Claude Opus 4.8 work inside workflows without API key management
Good middle ground — more powerful than Zapier, less overhead than self-hosted n8n
Data stores (built-in key-value storage) reduce dependency on external databases
Template library (5,000+ scenarios) means common automations are pre-built
Error handling — native retry logic, error handlers per module, and rollback support

Cons

Credit-based billing makes cost unpredictable, especially with AI modules that consume 5–20 credits per call
Smaller app catalog than Zapier (3,000 vs 7,000+)
No native mobile app for monitoring or debugging on the go
Execution logs only retained 30–90 days on standard plans (Zapier keeps 90+ days on Pro)
Learning curve for advanced features — routers, iterators, and error handlers take practice
Data-heavy workflows get expensive because every data transformation operation consumes credits

Use Cases

Marketing Operations: Lead Enrichment to CRM

A common setup: new form submission → enrich with AI (extract company info) → find or create HubSpot contact → add to Mailchimp list. Make handles this in 6 modules with error handling if the enrichment step times out.

E-Commerce: Order Processing

New Shopify order → check inventory in Airtable → route by product type → send to different fulfillment channels → notify Slack. The router and iterator modules handle multi-item order splitting cleanly.

Finance: Invoice Automation

Gmail attachment detected as invoice → extract invoice fields with Claude Opus 4.8 → match to vendor in accounting system → create payment record → send approval request in Slack. The AI text extraction module saves hours of manual data entry [4].

AI Agent: Customer Support Triage

Make’s Agent Builder can power a customer support triage flow: incoming ticket → AI agent classifies sentiment and urgency → routes to correct team → triggers automated response for common issues → escalates to human for complex cases.

Alternatives

Tool	Best For	Starting Price	Key Difference
Zapier	Simple automations, largest app ecosystem	Free (100 tasks/mo)	7,000+ apps, simpler but less powerful
n8n	Developers and teams who want to self-host	Free (self-hosted) or $20/mo (cloud)	Open-source, fully customizable, more complex setup
Gumloop	AI-heavy workflows with built-in LLM ops	Free tier available	Purpose-built for AI agents, newer platform
Activepieces	Open-source alternative to Zapier/Make	Free (self-hosted)	Growing fast but smaller community
Lindy AI	AI-first automation for email/calendar	Free tier available	Stronger AI inbox features

Make vs Zapier: Zapier wins on simplicity and app count. Make wins on complex workflows, AI modules, and pricing (Make’s $10 plan includes unlimited scenarios; Zapier’s $30 Professional plan limits you to 2,000 tasks).

Make vs n8n: n8n wins on cost (self-hosted is free), customization (full code access), and AI agent depth. Make wins on visual builder polish, no DevOps required, and built-in data stores [8].

Our comparison: n8n vs Make 2026 has the full breakdown.

Verdict: 8.5/10

Make is the best visual automation platform for teams that need complex workflows but don’t want to hire a developer or manage infrastructure. The 2026 additions — Agent Builder, Maia assistant, and latest LLM support — keep it competitive as automation shifts toward AI-powered workflows.

Pick Make if: You’re building mid-complexity automations with branching logic, you want AI modules built in, and Zapier feels too limited. Your team has at least one person comfortable with visual workflow design.

Skip Make if: You need the largest app catalog (choose Zapier), you want full control and lower costs (choose n8n), or your workflows are all AI-agent-driven with minimal human oversight (choose Gumloop or a purpose-built AI agent platform).

Make’s credit-based billing is its biggest risk — AI-heavy workflows can burn through credits fast. Start on the Free plan, test your real workflow, calculate credit consumption, then pick a plan. Annual billing saves 15% if you’re committed.

FAQ

Is Make free?

Yes. The Free plan gives you 1,000 credits/month, access to the visual builder and all apps, and 15-minute execution timeout. It’s enough to test and run simple automations.

How much does Make cost per month?

Paid plans start at $9/month (Core, annual billing) for 10,000 credits. Pro is $16/month for 20,000 credits. Teams is $29/month for 50,000 credits. Enterprise is custom-priced.

Is Make better than Zapier?

Depends. Make is better for complex branching workflows and AI modules. Zapier is better for simplicity, larger app catalog, and teams that don’t need visual workflow design.

Can Make use AI?

Yes. Make has native modules for OpenAI GPT-5.2, Anthropic Claude Opus 4.8, and custom AI providers. The Agent Builder lets you compose multi-step AI agent workflows visually.

What’s the difference between Make and n8n?

Make is a hosted visual platform (easier setup, less control). n8n is open-source (free self-hosted, more customizable, requires DevOps). Make costs more at scale but requires zero infrastructure management.

Does Make have a mobile app?

No native mobile app. The web interface works on mobile browsers for monitoring, but you can’t build or edit workflows from a phone.

Sources

[1] Make.com Official Pricing — https://www.make.com/en/pricing [2] Make 2026 Help Center — https://help.make.com/2026 [3] G2 Make Reviews — https://www.g2.com/products/integromat-by-celonis-make/reviews [4] Make Product Page — https://www.make.com/en [5] Maia by Make — https://help.make.com/introduction-to-maia-by-make [6] Make Credits Documentation — https://help.make.com/credits [7] Best AI Agent Platforms 2026 — https://www.make.com/en/blog/best-ai-agent-platforms [8] Zapier: n8n vs Make — https://zapier.com/blog/n8n-vs-make/