Gumloop Alternatives

n8n is a workflow automation tool with a visual canvas, AI agent nodes and code steps in JavaScript or Python. For a Gumloop user, the biggest change is the billing unit. n8n bills on executions, and an execution is a single run of your entire workflow, however many steps it has and however much data it processes. A Gumloop agent that reads a sheet, calls a model three times and writes to a CRM spends credits on each of those moves plus the compute minutes. In n8n, that whole run is one execution, and the model tokens go on your own OpenAI or Anthropic bill, with no fee on top.

Prices are public. The cloud plans, Starter at $20 a month billed annually ($24 month to month) for 2,500 executions with unlimited steps and Pro at $50 a month billed annually ($60 monthly) for 10,000 executions, are hosted by n8n. Business costs $800 a month billed annually ($960 monthly) for 40,000 executions, adds SSO, environments and Git version control, and is sold for self-hosting only. A company with fewer than 20 employees can apply for the Startup plan, 50% off Business. Paying Starter month to month costs $288 a year, against $240 on the annual plan. Our n8n review and our guide to n8n pricing go deeper on the plans.

The free Community Edition runs on your own server under the Sustainable Use License, a fair-code license that is not OSI open source: you can use it for internal business work, not resell it as a service. It lacks SSO, environments and Git version control. The limit is the effort. You build more yourself than in Gumloop, where an agent can work from a prompt, and self-hosting means you run upgrades and backups. An n8n training course shortens the ramp-up, and an n8n agency can rebuild your Gumloop flows for you.

Make builds automations as scenarios on a visual canvas: modules linked by lines, with routers for branches, filters between steps and error handlers you can see. Gumloop users who liked its original canvas usually find Make familiar, and Make has added AI modules of its own. The difference is that each step is a step you placed, not a decision an agent makes at run time, so the same input produces the same path every time.

Usage is counted in credits. By default, one operation equals one credit, and an operation is one module doing its job. The Free plan gives 1,000 credits a month with no time limit. Core costs $9 a month billed yearly, or $10.59 month to month, for 10,000 credits and unlimited scenarios. That is half as many credits as Gumloop Pro for under a third of its price month to month ($10.59 against $37), and a Make credit buys a whole module run, where a Gumloop credit is worth $0.005 of tokens or compute. Our Make review and our guide to Make pricing cover the plans above Core.

Two traps. Polling triggers spend an operation on every check, even when nothing new arrives, so a scenario that checks a sheet every minute can burn credits on empty checks. And bundles multiply: a module that returns 100 rows runs the following modules 100 times. Build with instant webhooks where an app offers them, and filter early. If you are torn between this canvas and a run-based one, our n8n vs Make comparison puts them side by side. If you would rather not rebuild your Gumloop flows yourself, a Make agency can do it. The limit for a Gumloop user is the AI side: an agent that decides its own steps is a smaller part of Make than of Gumloop.

Zapier is the automation tool most business users already know: a trigger, a few actions and a catalog of more than 9,000 apps. A marketer or a sales ops manager can build a Zap in minutes, and Zapier now sells AI agents and chatbots as separate products next to Zaps. For a Gumloop user, it trades AI depth for breadth and simplicity: most of your apps are probably already in the catalog.

It counts tasks. A task is counted each time an action step in a Zap runs successfully, and some steps use more than one, such as an advanced AI step at 3 tasks or an MCP tool call at 2, while trigger, filter and certain built-in tool steps do not count. The Free plan includes 100 tasks a month. Professional starts at $19.99 a month billed yearly ($29.99 month to month) and Team at $69 a month billed yearly ($103.50 monthly). Agents are priced on their own: Agents Free runs up to 400 activities a month, and Agents Pro costs $33.33 a month, billed annually at $400, for 1,500 activities. Nonprofits get 15% off any paid plan. Our Zapier review details each tier, and our Make vs Zapier comparison helps if you hesitate between the two.

The trap is the overage. Pay-per-task billing is enabled by default for accounts opened since 2024: past your plan's tasks, extra tasks are billed at 1.25 times your normal task cost on an annual plan and 2.5 times on a monthly plan. A Zap that loops over 50 rows with three actions uses at least 150 tasks per run, so long, data-heavy Zaps get expensive faster than at n8n or Make.

Dify is a platform for building AI applications: agentic workflows on a visual canvas, chat apps, and knowledge bases that turn your documents into searchable context for the model. It sits closer to Gumloop's AI side than Zapier or Make do, with model choice across OpenAI, Anthropic, Gemini and others, and it can run in Dify's cloud or on your own servers. Where Gumloop bills each agent's tokens and minutes, Dify Cloud sells workspaces with quotas, and you can switch to your own API key once the included message credits are used.

Dify Cloud has three self-serve tiers. Sandbox is free, for trying the core features, with 200 message credits. Professional costs $59 a month, or $590 a year billed annually, per workspace, with 5,000 message credits a month, 3 team members, 50 apps and 20,000 trigger events a month. Team costs $159 a month, or $1,590 a year, with 10,000 message credits a month and unlimited trigger events. Paying Professional monthly costs $708 a year, so the annual plan saves $118.

The Community Edition is free to self-host, but read the license before calling it open source in a procurement file. Dify uses a modified Apache 2.0 license: you may not run a multi-tenant service from the source code without written permission, and you may not remove the logo from its console. For internal use, that is rarely a problem, and you can still call a Dify app from a business workflow through the Make and Dify integration or the Zapier and Dify integration. The limit for a Gumloop user is the connector side: Dify is built for AI apps over your data, with fewer ready-made app integrations than Zapier or Make.

Activepieces is a younger automation platform with a builder close to Zapier's, AI steps and agents, MCP support and a codebase you can host yourself. Its core is released under the MIT license, while its enterprise folders sit under a commercial license, which makes it open core rather than fully open source. Its connectors, called pieces, are written in TypeScript, so a developer can add one when it is missing.

Pricing is flat and public. Free costs $0 with 1,000 credits and no card, and runs past the limit wait for the next reset. Plus costs $20 a month flat for 10,000 credits, or $16 a month billed yearly, and Team costs $200 a month flat, or $166 a month billed yearly. Extra credits on Plus and Team cost $0.007 each. A run is one credit however many steps it has, so a ten-step flow without AI costs the same as a two-step one. AI steps are the exception: 2 credits on a fast model, 10 on a smart model and 20 on a frontier model, while each agentic action costs 1. Free and Plus allow up to 5 users; Team includes 25 and 50,000 credits a month. Plus with yearly billing comes to $192 a year, against $444 for a year of Gumloop Pro at $37 a month.

From Plus, you can bring your own AI keys: the price of the plan does not change, every AI step drops to 1 credit and the model cost moves to your provider bill. An embed offer, from $36k a year, lets software vendors put Activepieces inside their own product. The limit is depth: the catalog of pieces is smaller than Zapier's or Make's, and the AI agent features are newer than Gumloop's, so test the two or three integrations your flows depend on before you move.

Lindy builds AI agents that act like assistants: they triage an inbox, prepare meetings, update a CRM or answer from Slack, and you set them up by describing the job rather than wiring steps. It follows the same direction Gumloop has taken with its agents, so it suits teams that liked Gumloop's agents more than its canvas. The difference is the billing model, which follows people rather than runs.

Every active user in your workspace is billed, from $49.99 a month for 5,000 credits each, pooled across the team; Lindy also shows some visitors an entry tier at $29.99 for 3,000 credits, so check the grid you are offered before you sign up. Anyone who uses Lindy takes a seat, including teammates who @mention it in Slack, after a 7-day trial for those who join through Slack. Top-ups cost $10 per 1,000 credits and stay until you use them, while monthly credits refresh each billing cycle and do not roll over. When credits run out, Lindy pauses credit-using actions until the next cycle, with no surprise bill. You can start with $50 in free credits, valid for 7 days. A team of five active users pays $249.95 a month, where Gumloop Pro gives unlimited seats from $37. Our Lindy review and our page on Lindy pricing go further.

The limit is cost at team scale and control. Bigger jobs use more credits, so the bill is no easier to predict than Gumloop's, and you get less say over each step than in a workflow tool. For a solo founder, it is a quick way to hand off email and meetings; for a ten-person team, count active users first.