
Gumloop is a no-code automation tool where each step in a workflow is an AI agent. The steps can scrape a site, research a topic, pull data out of messy text, summarize, and make simple decisions. Think Zapier or Make, rebuilt with AI doing the work. It has more than 115 ready-made blocks, MCP support, scheduled runs and team controls. You drag blocks together to build things that would otherwise need code: process a pile of documents, research across several sources, turn unstructured text into a table, then send the results where they need to go. You pay in credits, so heavy workflows can get expensive. It's also harder to learn than basic automation tools. Gumloop assumes you already know what you want to automate and makes the AI parts easy. It won't teach you automation from scratch.
Gumloop sits between basic automation tools like Zapier and Make and writing your own code. If you've ever built a Zap and wished one step could read a document, pick out the key points and decide what happens next, that's what Gumloop's AI steps are for. Its library of more than 115 blocks covers the usual jobs: processing documents, researching the web, pulling out data and updating a CRM.
The trade-off is complexity. Gumloop expects you to understand automation already. It won't explain what a trigger is, and it focuses on making the AI parts easy instead. If you've never used an automation tool, start with Zapier. If you've outgrown Zapier because your workflows need some judgment, Gumloop is the next step.
Best for operations, marketing and data teams running repetitive work that needs decisions along the way, rather than just moving data around. Watch the credit pricing and estimate your volume before you commit, because heavy workflows get expensive fast. If all you need is simple "when this happens, do that" automations, you'd be paying for power you won't use.