Visual workflow automation platform with hundreds of AI integrations.
Productivity
Make (formerly Integromat, rebranded in 2022) is the visual workflow automation platform that people graduate to when Zapier gets expensive or restrictive. Where Zapier gives you a linear list of Trigger and Action steps, Make gives you a real canvas — modules connected by data flow lines, parallel branches that merge back together, iterators that unpack arrays, aggregators that fold them back up, and error handlers wired as first-class citizens. It is closer in shape to a node-based engineering tool than to Zapier's spreadsheet-inspired UX, and that difference is the entire point.
The pitch is straightforward: real automation workflows are DAGs, not lists, and if you have ever tried to model "for each new order, look up the customer, split the line items, run a filter on each, then aggregate the results into a Slack message" inside Zapier, you have already discovered why Make exists. Add pricing that is roughly a third of Zapier's on a per-operation basis and you have the reason Make quietly runs an enormous amount of production automation for teams who never bothered to buy Zapier's brand.
Make is not the easiest tool in the space. There is a learning curve — modules, data trees, mapping panels, filter conditions, error routes — and the first few workflows take longer to build than the equivalent in Zapier. But once your team is fluent, the productivity curve keeps rising. Zapier hits a ceiling at "multi-step Zap with paths." Make keeps going: sub-scenarios, webhooks, custom modules, HTTP requests to arbitrary APIs, and now first-class AI modules that call OpenAI, Anthropic, or a custom endpoint inside any workflow.
In 2026 the tool sits in an interesting spot. It is more powerful than Zapier, cheaper than Zapier, and its AI story has caught up. It is less flexible than self-hosted n8n and does not have n8n's escape hatch of "just run it yourself if the pricing changes," but it is far more polished as a hosted product. For a team that wants power without operational overhead, Make is often the correct answer.
Visual scenario builder. The core product. A canvas where modules (Make's word for connector nodes) connect via data lines. You see the whole workflow at a glance, you see where data forks and merges, and you can inspect the exact payload flowing between any two modules. This is genuinely a different mental model than Zapier's list of steps, and for anything beyond "when X, do Y," it is the correct model.
Real DAG execution. Parallel branches that run independently and merge back. Routers that split on conditions. Iterators that unpack arrays and process each item. Aggregators that fold results back into a single output. These are engineering primitives, exposed as visual blocks, and they let you model workflows that would take pages of code — or would be simply impossible in Zapier — in a few dozen modules.
2,000+ integrations. Fewer than Zapier's 7,000+, but the coverage on the important tools is complete. Every major CRM, every mainstream email tool, every payment processor, every popular database. The gap versus Zapier shows up in the niche corners — some obscure vertical SaaS tools have Zapier connectors but not Make ones. For most businesses this is not a real constraint.
Native AI modules. OpenAI, Anthropic Claude, Google Gemini, and Hugging Face are all first-class module categories. You drop an "OpenAI - Create a Completion" module into a scenario, wire in the prompt with variables from earlier modules, and the response flows to the next step. You can also call any HTTP endpoint, which means any model you want to use — self-hosted Ollama, Groq, Fireworks — is accessible via a generic HTTP module.
Custom Apps and modules. If Make does not have a connector for an API you need, you can build one. The Custom Apps SDK is straightforward and the resulting module behaves like a native one — same UX, same error handling, same versioning.
Error handlers. Every module can have error routes wired independently. You handle a 429 rate-limit differently than a 500 server error differently than a data-shape mismatch, and the workflow can retry, log, notify, or fork depending on the failure mode. This is a level of error control that Zapier simply does not offer.
Scenario templates and blueprints. A gallery of pre-built scenarios you can clone as starting points, and the ability to export any scenario as a blueprint that another user can import. Useful for teams standardizing on common patterns.
Sub-scenarios. Reusable workflows that other scenarios can call as if they were single modules. This is how you keep large automations maintainable — factor out the "look up a customer and enrich" logic into a sub-scenario and call it from anywhere.
Data Stores. A lightweight built-in database for state that needs to persist across scenario runs. Not as capable as a real database but sufficient for storing lookup tables, tracking processed IDs, or holding configuration.
Scheduling and webhooks. Schedule scenarios by cron or interval, or trigger them by webhook. Webhook triggers respond immediately and include a full inspector for debugging incoming payloads.
Make prices on operations — each module execution counts as one operation, and each scenario run consumes as many operations as modules that fire. This is roughly equivalent to Zapier's task model, priced at a fraction of the cost.
Free — 1,000 operations/month, 2 active scenarios, minimum 15-minute interval between runs. Genuinely usable for small workflows.
Core ($10.59/mo, billed annually) — 10,000 operations/month, unlimited active scenarios, 1-minute intervals, full access to all connectors and features. This is the correct starting tier for most teams and delivers roughly the same throughput as Zapier's Professional plan at a third of the cost.
Pro ($18.82/mo) — 10,000 operations base, priority scenario execution, custom variables, full-text execution logs. The tier for teams running production workflows.
Teams ($34.12/mo) — Team-level workspaces, shared connections, roles and permissions. Priced per shared team workspace, not per user.
Enterprise (custom) — SSO, dedicated success, advanced security, higher operation volumes. Typically starts around $2,000/month depending on volume.
Operations scale with volume — buying additional 10,000-operation blocks costs roughly a dollar or two per thousand ops depending on plan. In practice a team running a moderately busy Make workspace with a dozen scenarios lands around $30-60/mo, compared to $200-400/mo for the equivalent throughput on Zapier.
| Feature | Free | Core | Pro | Teams |
|---|---|---|---|---|
| Operations/month | 1,000 | 10,000 | 10,000 | 10,000 |
| Active scenarios | 2 | Unlimited | Unlimited | Unlimited |
| Min interval | 15 min | 1 min | 1 min | 1 min |
| Custom variables | No | No | Yes | Yes |
| Full execution log | 1 day | 7 days | 30 days | 30 days |
| Shared workspaces | No | No | No | Yes |
| Starting price | $0 | $10.59/mo | $18.82/mo | $34.12/mo |
AI module calls consume operations and the underlying LLM token cost, similar to Zapier — but Make does not mark up the token cost. You bring your own OpenAI or Anthropic key and pay the model provider directly. This is materially better economics for AI-heavy workflows.
Pros.
Cons.
Ops teams graduating from Zapier. The archetypal Make customer. Zapier bill has crossed $150-200/mo, workflows are hitting Path limitations, and the team is willing to invest a week learning a more powerful tool to cut cost and unlock capability. Make is designed for exactly this migration.
E-commerce operations. Multi-marketplace order routing, inventory sync across channels, customer service ticket routing with AI classification, refund workflow orchestration. E-commerce workflows are branchy, high-volume, and cost-sensitive — the exact shape Make handles best.
Marketing operations at mid-market companies. Lead enrichment pipelines, multi-touch attribution workflows, campaign automation across many channels. When the workflow needs to fork into "SDR path" versus "PLG path" versus "enterprise path" and merge results back, Make's routers do the job.
AI-augmented business workflows. Any workflow that classifies, extracts, or generates content using LLMs at meaningful volume. Because Make does not mark up LLM tokens, AI-heavy workflows are dramatically cheaper on Make than on Zapier.
Internal tools and process automation. Approval workflows, notifications, cross-system syncs. The kind of glue work every mid-sized company has too much of.
Bad fit. Teams that need self-hosting for compliance or cost — use n8n. Non-technical users who want the absolute simplest possible learning curve — Zapier is easier for the first month. Teams whose primary need is AI agents rather than integration workflows — Dify is the right shape. Extreme high-volume workloads (millions of ops/month) where the economics push toward custom infrastructure.
Zapier. The gentler competitor. Easier to learn, more integrations, dramatically more expensive at scale. Correct choice for non-technical teams with modest volume. Wrong choice when workflows get complex or volume grows.
n8n. The self-hostable open-source option. Fair-Code licensed, comparable feature set to Make on the workflow side, and you can run it on a $20/month VPS with unlimited executions. Correct choice for teams with technical people and cost or data-sovereignty concerns.
Bardeen. Browser-based automation for workflows that need to interact with web pages directly. Different shape but overlapping use cases for scraping and in-browser automation.
Dify. Not a direct competitor but the natural pair for AI-heavy workflows. Build the agent logic in Dify, expose it as an HTTP endpoint, and call it from a Make scenario. This gives you Dify's LLM ergonomics with Make's integration breadth.
Honorable mentions: Pipedream (developer-first with real code steps in every workflow), Tray.io (enterprise-tier integration platform), Workato (enterprise iPaaS with per-connector pricing).
Sign up at https://make.com. The Free tier gives you 1,000 operations per month and two active scenarios — enough to build and prove one real workflow before paying.
The recommended first move: pick a workflow you already run in Zapier or by hand, and rebuild it in Make. This is the only way to internalize the difference between the two mental models. The Zapier workflow is a list. The Make workflow is a graph. Once you have built the same automation in both, you will viscerally understand when to use which.
For the first scenario, start with a webhook trigger. Send a test payload with cURL, inspect it in Make's webhook inspector, and use it as the seed for the workflow. This is faster than wiring up a real trigger and gives you full visibility into the data shape.
Add AI modules once you have the base workflow running. The OpenAI module wants a system prompt, a user prompt, and mapping variables from earlier modules. Wire the output into an "Iterator" or "Aggregator" module if the response is a list or needs folding back into a scalar. Two iterations of "run, inspect, adjust" and you have a production-quality AI-augmented workflow.
Upgrade to Core ($10.59/mo) when you have three or four scenarios you actually depend on. The delta from Free to Core is the ability to run more than two scenarios simultaneously and to run at 1-minute intervals instead of 15 — both usually matter within the first month of real usage.
Is Make the same as Integromat? Yes. Integromat rebranded to Make in 2022. The underlying platform, features, and pricing model are the evolution of Integromat, not a new product.
How does Make compare to Zapier for cost? For equivalent throughput, Make is typically 3-5x cheaper. This is the single biggest reason teams migrate. A workflow that costs $200/mo on Zapier often costs $30-60/mo on Make.
Can I run AI workflows in Make? Yes, natively. OpenAI, Anthropic Claude, Google Gemini, and Hugging Face are first-class module categories, and you can call any HTTP endpoint for custom models. Because Make does not mark up LLM tokens, AI-heavy workflows are meaningfully cheaper on Make than on Zapier.
How steep is the learning curve? Steeper than Zapier, gentler than n8n. Expect your first complex scenario to take 2-3x longer than the Zapier equivalent. By the fifth scenario the productivity curve inverts.
Can I self-host Make? No. Make is cloud-only and closed source. If self-hosting matters, use n8n.
What happens when I hit my operation limit? The scenario stops running until the next billing cycle or until you buy an operations top-up. The system does not silently drop data — it queues webhook triggers and pauses scheduled ones.
Does Make support real-time triggers? Webhook triggers fire immediately. Polling triggers respect your plan's minimum interval — 15 minutes on Free, 1 minute on Core and above.
How reliable is Make in production? Comparable to Zapier. Occasional connector-side issues when a SaaS vendor changes their API, but the core execution engine is mature and reliable. Uptime has been consistent at 99.9%+ over recent years.
Make is the correct workflow automation platform for teams that have outgrown Zapier's pricing or feature ceiling, have at least one person willing to invest a week learning a more capable tool, and do not need self-hosting. The visual scenario builder is a genuinely better abstraction than Zapier's list-of-steps model for anything beyond trivial linear workflows, and the operations-based pricing makes moderately busy production workloads economically sane.
The AI story is now solid. Native modules for the major model providers, no token markup, and the ability to call any HTTP endpoint means the "AI in Make" workflow is at least as good as "AI in Zapier" and often better because of the routing and error primitives around it.
If you are a non-technical ops lead starting from scratch and cost is not yet an issue, start on Zapier — the learning curve is gentler and you will build faster in the first month. If you have technical people and want to control cost and data on your own infrastructure, evaluate n8n self-hosted. Make sits in the middle: hosted convenience with power that rivals n8n and pricing that dramatically undercuts Zapier.
Start on the Free tier at https://make.com, rebuild one existing workflow to feel the difference, and upgrade to Core at $10.59/mo when you have real scenarios in production. The upgrade path from Core through Pro to Teams is clean and rarely surprises on cost.