n8n Review 2026

Make

Visual, node-based automation with a genuinely usable free tier

Make (formerly Integromat) sits between Zapier's simplicity and n8n's technical depth: a visual, node-based canvas that handles complex multi-branch workflows Zapier's linear builder can't, while staying approachable enough for non-technical marketers and ecommerce operators without requiring code. All plans include unlimited workflows and unlimited steps within them — the core billing unit is the "operation," counted each time a complete workflow runs, regardless of how many steps or how much data it processes internally. The operation-counting model is genuinely worth understanding before committing, since it's the most common source of billing surprises: Make counts every module that executes, including triggers, filters, routers and iterator loops — a workflow that looks like "3 steps" on the visual canvas can easily consume 8-15 operations per actual run. Core starts at $9-10.59/month (billed annually) for 10,000 operations, which comfortably covers most SMBs running 5-15 active scenarios at average volume; Teams jumps 81% in price over Pro for what's largely admin/collaboration functionality, worth skipping for solo operators or two-person teams. With 1,500+ pre-built app connectors, Make trails Zapier's 7,000+ but comfortably beats n8n's roughly 400 native integrations, landing in a genuinely useful middle ground. As of November 2025, additional operation packs cost 25% more than plan-included credits (~$11 per extra 10,000 ops) — a real cost to model if you're running close to your tier's limit regularly. For teams comfortable with a visual canvas and willing to think in operations rather than tasks, it delivers meaningfully more automation per dollar than Zapier while staying more approachable than n8n's code-first flexibility.

Zapier AI

The most integrations of any automation platform, now with AI steps and Agents

Zapier built its dominance on one simple advantage that's still true in 2026: more app integrations than any competitor, 7,000+ connected apps covering virtually every SaaS tool that exists, wrapped in the most beginner-friendly linear automation builder available. Zapier AI adds natural-language workflow creation (describe an automation in plain English and Zapier drafts it), AI-powered steps inside existing Zaps, and Zapier Agents for delegating open-ended tasks to an AI teammate that can browse the web and act on a schedule. A meaningful 2026 restructure is worth understanding before budgeting: the free plan's task allowance was cut from 750 to just 100 tasks/month, and Professional jumped to $29.99/month for 750 tasks. AI steps, code steps and SDK calls all bill under the same task-based model now — a multi-step AI agent chews through the task allowance considerably faster than a simple two-step Zap, so a workflow that looks affordable on paper can push you into a higher tier once AI steps stack up. The standalone Zapier Agents product is a separate paid add-on (~$50/month for 1,500 activities) distinct from AI steps inside regular Zaps. At scale, the price gap versus competitors is stark: teams report paying roughly $130/month on Zapier Professional for 10,000 tasks worth of automation, versus $20-30/month for equivalent volume on Make.com, or $30-50/month on n8n. Zapier remains the right choice specifically when integration breadth is the actual constraint — a niche CRM or obscure SaaS tool that only Zapier connects to — rather than budget or workflow complexity, where Make or n8n deliver meaningfully more automation per dollar.

Relevance AI

Build a coordinated 'AI workforce' of role-based agents

Relevance AI's core concept is an "AI workforce": rather than one general-purpose assistant handling every request, you build narrowly-scoped agents with distinct roles — a research agent, an SDR agent, an ops agent — that work together as a coordinated team, each using only the tools and information assigned to its specific job. That multi-agent orchestration approach makes it particularly strong for go-to-market teams building sales and revenue-operations workflows where several specialized tasks need to hand off to each other. A significant pricing restructure took effect in September 2025 and remains the current model: costs split into Actions (what an agent actually does — API calls, tool use) and Vendor Credits (the underlying LLM model costs), with no markup on Vendor Credits and the option on paid plans to bring your own API keys to bypass them entirely. The free tier includes 200 Actions/month plus $2 in bonus vendor credits — useful for initial testing, but genuinely difficult to forecast real monthly spend from, since usage compounds quickly once agents run continuously or handle complex, multi-step tasks. Paid plans run from roughly $19/month for individuals up to about $199/month for teams, positioning it as more affordable at the entry level than Lindy (~$50/month) but with real usage-based cost uncertainty that Lindy's flatter-feeling tiers avoid. It's best suited to teams that want a genuine multi-agent "workforce" model for sales or ops specifically, and are comfortable actively monitoring Actions and Vendor Credit consumption rather than a fully predictable flat bill.

Gumloop

Trending

Drag-and-drop AI workflow automation for operations teams

Gumloop is a node-based canvas for building AI automations, positioned between rigid no-code connectors and writing your own orchestration code. Nodes cover web scraping, LLM calls, conditional branching, loops over lists, file handling and integrations with the tools ops teams already use. The distinguishing capability is that AI is a first-class step rather than a bolt-on: a flow can scrape a batch of company sites, ask a model to classify each one, filter on the result and write rows to a spreadsheet or CRM, all without leaving the canvas. Flows run on a schedule, from a webhook, or from a Chrome extension on the page you are viewing. Growth, recruiting and RevOps teams use it for enrichment pipelines, lead research, content repurposing and report generation that would otherwise be a weekly manual grind.

Gumloop

Trending

Drag-and-drop AI workflow automation for operations teams

Gumloop is a node-based canvas for building AI automations, positioned between rigid no-code connectors and writing your own orchestration code. Nodes cover web scraping, LLM calls, conditional branching, loops over lists, file handling and integrations with the tools ops teams already use. The distinguishing capability is that AI is a first-class step rather than a bolt-on: a flow can scrape a batch of company sites, ask a model to classify each one, filter on the result and write rows to a spreadsheet or CRM, all without leaving the canvas. Flows run on a schedule, from a webhook, or from a Chrome extension on the page you are viewing. Growth, recruiting and RevOps teams use it for enrichment pipelines, lead research, content repurposing and report generation that would otherwise be a weekly manual grind.