Best Make.com Alternatives (2026): 9 Picks by the Reason You Are Leaving

Last updated: October 19, 2026. Prices checked on vendor pricing pages in October 2026.

Make (the product formerly called Integromat) is good at what it was built for: visual scenarios with routers, iterators and error handlers. People rarely leave because it stopped working. They leave because a busy scenario burns credits, because only one person on the team can read the canvas, or because the inputs got too messy for fixed rules. Each of those problems has a different answer, so this guide is organized by reason, not by a single ranking.

Disclosure: DeskFerry publishes this guide and DeskFerry is our product. We compared the tools below using their public pricing pages and documentation, and we say where another tool is the better fit.

Why do teams look for a Make.com alternative?

Most switches come from one of four triggers: credit bills that grow with scenario length, a canvas only one person can maintain, a need to self-host for data control, or scenarios that fail whenever an input looks different. Knowing which one applies to you narrows nine options down to two.

The credit trigger is the most common, and it comes from how Make counts. According to Make's pricing page, each action a scenario performs uses credits, and most actions use one: reading from an app or webhook, searching, creating, updating or deleting a record, transforming data and iterating rows. Routers and error handlers such as Rollback, Break and Ignore are free. That means a scenario with ten modules spends roughly ten credits every time it fires, and an iterator over 50 rows multiplies the modules inside it by 50. A scenario that looked cheap in testing can become the largest line on the bill once a webhook starts firing hundreds of times a day. Before you shop, open Make's usage screen and find the three scenarios that spend the most. Those three, not your whole library, decide which alternative saves money.

How do Make credits compare with Zapier tasks and n8n executions?

The three billing units count different things. Make counts most module actions. Zapier counts each successful action step but not the trigger. n8n counts one execution per complete workflow run, whatever its length. Long workflows are therefore cheapest on per-run tools, and short, frequent ones are cheapest on step-based tools.

This table lists the entry points we checked on each vendor's pricing page in October 2026. Figures change often, so confirm before you buy.

Which alternative is cheapest for a 10-step workflow?

For a 10-step workflow running 1,000 times a month, n8n Starter and Make Core both cost little, while Zapier costs far more because each of the nine action steps is a task. The arithmetic below is an illustrative scenario using October 2026 list prices, not a measured customer bill.

Picture a lead-routing workflow: a webhook receives a form, then nine actions look up the company, check the CRM for duplicates, create or update a contact, post to Slack and log a row. On Make, that is about ten credits per run, or 10,000 credits a month, which fits the Core tier starting at $9 a month billed annually. On Zapier, the trigger is free but the nine actions are 9,000 tasks, which lands on the 10,000-task Pro tier at $129 a month billed annually or $193.50 billed monthly, according to Zapier's pricing table. On n8n Cloud, the same month is 1,000 executions, inside Starter's 2,500 at €20 a month billed annually. On Activepieces it is 1,000 credits, which the free plan covers if no AI steps are involved. The lesson holds beyond this example: the more steps per run, the stronger the case for a per-run tool.

Which Make alternative fits your reason for leaving?

Match the tool to the problem. Cost on long scenarios points to n8n or Activepieces. A canvas nobody else can maintain points to Zapier or to an agent you describe in plain English. Data residency points to self-hosted n8n. Inputs that keep breaking rules point to an AI agent platform.

Which Make.com alternatives are worth comparing in 2026?

Nine tools cover nearly every reason for leaving Make. Three are workflow builders like Make, two are open-source per-run tools, three are AI agent products, and one is an enterprise integration platform. Each summary below names who should pick it and the one catch that matters.

n8n: per-run pricing and self-hosting

n8n is the default answer to credit fatigue. Its pricing page states that an execution is a single run of the entire workflow, however many steps or how much data it handles. Starter is €20 a month and Pro €50 a month, both billed annually; Business at €667 a month is self-hosted only. The Community Edition is on GitHub for teams that run their own servers. The catch is that self-hosting makes upgrades, backups and uptime your job, and the editor is closer to Make's canvas than to anything a non-technical colleague will pick up quickly. Our n8n pricing breakdown works through the plan limits.

Zapier: the widest app coverage

Zapier connects 9,000+ apps and has the shortest learning curve of the group. Its billing counts each successful action step as a task, though triggers and built-in tools such as Filter, Paths, Formatter and Looping are free. That makes it a good home for short, high-value workflows and an expensive one for long scenarios. Zapier also includes Tables, Forms and basic Agents on its plans. See our Make vs Zapier comparison for a feature-by-feature view.

Activepieces: a lighter open-source option

Activepieces charges one credit per run regardless of step count, with extra credits for AI model steps. Plus costs $20 a month for 10,000 credits and Team $200 a month for 50,000, per its pricing page, which also lists 760+ integrations. It is open source, so self-hosting is available. The catch is a smaller connector library than n8n or Zapier.

DeskFerry: AI agents instead of scenarios (our product)

DeskFerry replaces brittle scenarios with agents. You describe the job in plain English in the agent builder, connect apps from 1,500+ integrations, and choose which actions need approval. There is no canvas to maintain. Plans are $49, $99 and $299 a month after a 7-day free trial. The catch: an agent reasons at each step, so for a simple copy-and-sync job a per-run tool is cheaper.

Gumloop: AI-heavy data flows

Gumloop is built around language-model steps for scraping, enrichment and research pipelines. Pro starts at $37 a month after a 14-day trial, and model and paid-API calls consume credits. It suits analysts more than operations teams that mainly sync records.

Lindy: agents for inbox and meeting work

Lindy focuses on assistant-style agents for email, meetings and outreach. New accounts get $50 in credits for 7 days; the Team plan starts at $49.99 per active user a month for 5,000 credits, per its pricing page. Per-user billing adds up for larger teams.

Pipedream: code-first, now heading to Workday

Pipedream gives developers JavaScript and Python steps beside prebuilt actions. Workday agreed to acquire Pipedream in November 2025, and its pricing page now leads with Connect, a product for embedding integrations in your own software. Developers will like it; business teams wanting a Make replacement should look elsewhere.

Pabbly Connect: budget workflows

Pabbly Connect does not count triggers or internal steps such as filters, routers and formatters as tasks, and it sells lifetime plans. Its prices appear in local currency by region, so check the page yourself. The editor is plainer than Make's.

Workato: governed enterprise automation

Workato is for IT departments running automation as a program, with pricing quoted by sales. It is overkill for a small team leaving Make over a credit bill.

When does an AI agent replace a Make scenario?

Use an agent when a person regularly fixes a scenario's output by hand. Typical signs are a router with a dozen branches that still misses cases, a text parser that breaks on new email formats, or a filter that needs updating every month. Fixed, repeatable syncs belong on a rule-based tool.

Here is the lead-routing scenario from earlier, rebuilt as a DeskFerry agent. It is an illustrative setup, not a customer result.

1. Brief. In the agent builder you write: "When a demo request arrives, research the company, decide if it fits our ideal customer profile, add or update the HubSpot contact, and post a summary to #sales. Ask before writing to HubSpot."
2. Trigger. A new form submission starts the run, or someone mentions the agent in Slack through the DeskFerry Slack app.
3. Steps. The agent reads the form, checks HubSpot for an existing contact, looks up the company and scores the fit against your written criteria. A Make version needs a branch for each case; the agent decides per lead.
4. Approval. Before creating the contact, the run pauses on an approval card showing the record it plans to write and why.
5. Output. Once you approve, the contact is saved and the summary lands in #sales. Each tool call appears in run history.

You can watch a similar agent being set up from a plain-English brief below.

Try it · interactive demo

Build a lead-qualifying agent in plain English, no workflow canvas

Replay

NBuildRun

Lead QualifierLead Qualifier

Describe what this agent should do

NEO builds it from plain English: apps, schedule and instructions.

Create an agent named “Lead Qualifier”. When a new lead fills the website form in HubSpot, research the company, score it 1–5 against our ideal customer, and post anything 4 or above to #sales in Slack with a one-line reason.

Describe the agent in plain English, then send it to NEO.

Start free trial

Ready-made versions of jobs like this are in the DeskFerry marketplace.

When DeskFerry is the wrong pick. DeskFerry runs in the web app and in Slack. It has no native mobile apps, no voice or phone agents, no browser agents that click through websites, and no self-hosted edition. If you need to keep everything on your own servers, use n8n or Activepieces. If your scenarios are fixed syncs that rarely fail, a per-run tool will be cheaper.

How do you move scenarios off Make without breaking anything?

Migrate in order of cost, not in order of age. Export each active scenario's blueprint, rank scenarios by monthly credit use, rebuild the most expensive one first, and run old and new versions side by side until their outputs match. Most of the savings usually come from the first few rebuilds.

The blueprint JSON that Make exports is the most useful artifact in the move. No major alternative imports it directly, so it serves as a specification: every module, field mapping and filter condition is listed, which keeps the rebuild honest. While rebuilding, decide whether each scenario is fixed or judgment-based. Fixed scenarios translate step for step into n8n, Zapier or Activepieces. Judgment scenarios, such as triaging replies or deciding which rep owns a lead, are where a written brief for an agent often replaces several routers. Keep the Make version switched on during a parallel run, compare records daily, and only turn it off once the new version matches. Our Zapier alternatives guide and n8n alternatives roundup cover the neighboring tools if your shortlist changes along the way.

Is it worth keeping Make for some workflows?

Often, yes. Make stays cost-effective for scenarios that rely on free router and error-handler modules and run rarely. A two-tool setup, with Make or n8n for fixed syncs and an agent platform for judgment work, is common and usually cheaper than forcing every job into one product.

The test is simple. For each scenario, write down its monthly cost in the current tool and in the destination's billing unit, plus the time someone spends fixing its mistakes. If the scenario is cheap and nobody touches it, leave it where it is. If it is expensive because of step count, move it to a per-run tool. If it is expensive because people keep correcting it, move it to an agent with approval turned on. Our best AI automation tools guide compares more options across both camps, and current DeskFerry plan limits are on the pricing page.