Gumloop vs. Make

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Make (formerly Integromat) helped define visual, no-code automation. Its scenario builder lets you map out complex multi-step workflows with branching, routing, and error handling, and it connects to 3,000+ apps. It's a great tool for teams that need to move structured data between many systems.

Gumloop is a unified platform purpose-built for AI automation, and includes both AI agents and workflows. If your team wants to create and orchestrate complex, multi-agentic systems with AI at the core — summarizing content, scraping the web, enriching data, reasoning across tools — Gumloop gives you that power. No engineering support required.

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Agents and AI

Make added AI modules to enhance their workflow builder. For Gumloop, 'Integrating AI' wasn't an afterthought, it was the main motivation behind building the product in the first place. Letting anyone automate complex work with AI is a primary goal of ours.

Gumloop is an AI-native automation platform for both AI agents and deterministic workflows. Gumloop Agents reason, adapt, and self-correct; workflows execute predefined steps with maximum reliability and lower cost. And the two work together: you can embed an agent inside a workflow, nest workflows inside other workflows, and create complex multi-agentic systems that trigger automatically.

Make's core product is its Scenario builder, an interface for multi-step automations with branching, routing, and error handling. In late 2025, Make added AI Agent capabilities, but agents live exclusively as modules inside scenarios. There's no standalone agent experience. If you want a simple chat interface, you need to build a scenario with a Slack or webhook trigger, add AI Agent modules, configure a "Simple Text Prompt," and wire up the response chain. What takes a few clicks in Gumloop takes significant setup in Make.

With Gumloop, anyone on your team can immediately start chatting to agents and get work done. With Make, you have to build an entire flowchart to chat with an agent.

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Integrations

Make has a huge integration library, with 3,000+ app connectors. If you need to connect a niche industry tool or a long-tail SaaS app, Make likely has a module for it.

Gumloop supports 100+ platform integrations and 50+ pre-built MCP servers covering the tools businesses actually use — Slack, Google Workspace, Notion, HubSpot, Salesforce, Airtable, and many more (with new integrations added regularly). We also offer AI-powered MCP nodes. Instead of hunting through a menu of prebuilt actions or stringing multiple steps together, you can describe what you want to do in plain language and Gumloop creates a working step that does exactly that. It's not just faster; it also lets you do things a traditional integration can't.

Additionally, a Gumloop subscription gives you access to dozens of premium integrations at no extra cost. This includes tools like Apollo (enrichment), Exa and Parallel (AI search), Firecrawl (web scraping), Google Maps, and Semrush (SEO). In contrast, Make requires that you have your own paid account for every single integration.

Enterprise readiness

Gumloop is built for enterprise from the ground up. We're SOC 2 Type II and HIPAA compliant, with features designed for organizations that take AI governance seriously.

Make also supports enterprise-grade capabilities, including SAML and OIDC SSO and team-level access controls. But the depth of governance differs significantly — especially when it comes to AI-specific controls.

Gumloop gives enterprises full control over who can use AI, and how. We support allow/deny lists for AI models, global fallback model settings, and per-model restrictions. For teams using MCP (Model Context Protocol) tools at scale: Gumloop offers Gumstack: a full platform for building, deploying, and managing custom MCP servers with CI/CD, per-tool RBAC, analytics dashboards, and end-to-end tracing for every tool call.

Pricing

When it comes to total cost of ownership, Gumloop's model is simpler and often more cost-effective for AI-heavy workflows.

Gumloop uses a unified credit-based system. All usage (agents, workflows, integrations) is abstracted into a single credit currency. Crucially, non-AI workflow steps are free. That means a workflow with many data-routing, formatting, or integration steps costs the same whether it has 3 steps or 30.

In Make, every module execution costs credits (including non-AI operations like reading a Google Sheet row or sending a Slack message). For AI features, pricing is dynamic and still subject to change as the feature is in beta.

A Gumloop subscription also includes premium integrations (Apollo, Firecrawl, Semrush, etc.). With Make, each of those tools would require separate bills and accounts.

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Gumloop vs. Make

Make is a solid tool for visual workflow automation, with an impressive library of 3,000+ integrations. If your primary need is connecting a large number of SaaS apps in structured, rule-based flows, Make is hard to beat.

But if your company is investing in AI agents, dealing with unstructured data, or scaling intelligent automation without engineering support, Gumloop is the better fit.

One platform for agents and workflows. Premium integrations included. Enterprise AI governance built in. Agents that reason, write code, and get better over time.

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