Gumloop review: My honest experience after 2 years

I can't help but roll my eyes.

No, we are still a long way from AI agents being able to do all of the work of a human being.

However, I'm optimistic. And out of all the AI tools I've tested, only one stands out right now: Gumloop.

I came across the tool two years ago from a friend who's an investor (and I know when this friend invests in something, it will be promising because he's the smartest person I know in tech).

So I reached out and had Max, the CEO of Gumloop, give me a demo of the platform. And then I actually went and created my own AI agents with the tool.

And I have to say, I'm quite blown away.

This AI agent platform space is getting crowded with a bunch of tools. So maybe you’ve already heard of Gumloop from someone and now you’re reading this to see what the platform is and does.

After being a user for the past two years, I can say that almost all the agent builders right now are watching Gumloop and trying to replicate it. It's by far one of the easiest agent builders I've used. And what really makes it different from something like Claude Cowork is it's multiplayer aspect.

You can create agents and skills that you can share across your whole team. All while giving admin users access to controling model usage, AI spend, tool calls, and more.

I want to give you a fast track to what Gumloop is and how to use it.

So here's my honest Gumloop review. I'm not being paid to write this, I just know this article will be helpful for those looking to use the platform — be it for their marketing needs, development needs, sales needs, education needs, or really whatever.

I'm going to go over what the tool promises to do, what I honestly think of it (aka the pros and cons I've currently come across), and who I think it will be best suited for (and who it's not for).

Okay, let's get into it.

(If you want my TLDR, scroll to the bottom or click here.)

Who is Gumloop for?

When you land on the Gumloop website, you're greeted with a heading that says:

"Build, share, optimize & control agents"

The messaging has shifted since I first reviewed Gumloop. It used to say "Automate any workflow with AI. No coding required." Now the focus is squarely on AI agents, not just automated workflows.

The platform is still very much designed for non-technical knowledge workers. It gives you everything you need to build agents, share them, optimize them (swap to open-weight models to save costs, use refelections to have self impriving agents), and enterprise-grade control.

At its core, Gumloop empowers anyone to become an AI Engineer without knowing how to code.

So, who can get the most out of Gumloop? In my opinion, it’s:

• Growth and marketing teams: It can help you automate long workflows, scrape the web, integrate ChatGPT (or other LLMs) into automation workflows (think like Zapier), help you with lead scoring, and even SEO workflows (what attracted me to it).
• Freelancers and solopreneurs: You can literally create an AI agent for anything in your workflows. Be it help you find leads, help you deliver on your services, or automate any repetitive tasks you would have a VA do.
• Sales teams: You can build AI-assisted workflows like scraping the web to find contracts, do outreach, and integrate with a sales CRM to score your leads.
• Product and engineering teams: It can help you automate any internal operations, create prototypes that require AI to be integrated into a product, or even scrape web pages for document processing.
• HR teams: It can help you automate parts of the hiring process or even send employee satisfaction surveys with their templates (more on this later).
• Customer support teams: Use the platform to create workflows to help you with categorizing tickets or automating responses.

Because the platform is so broad, pretty much anyone in tech or online business can benefit in some shape or form. When I first wrote this review (a year ago), I would have said it was best for marketers, freelancers, or small business owners. But Gumloop has grown fast. Companies like Shopify, Ramp, Gusto, Instacart, and Opendoor are now using the platform. So it is clearly scaling well beyond small teams and into serious enterprise use cases too.

If you’re a customer of Zapier or Claude (like me), then you’ll most likely be a great candidate for using Gumloop as well. The main difference is that Gumloop takes an AI-first approach to automation. So it’s like if Zapier and ChatGPT had a baby — that’s how I would explain it in one sentence.

Gumloop's popular features

Gumloop has evolved a lot since I first reviewed it. The platform used to be all about building automation workflows. That still exists, but the product has expanded into something much bigger.

When you log in now, you are greeted with a chat interface that says "Hey [your name], how can I help?" It feels more like talking to an AI assistant than opening an automation tool.

You can type what you want to build, mention an agent with @, attach files, and connect apps to give your agent more abilities.

The platform can now be thought about in five parts:

• Agents. Chat-first agents that run autonomously and handle multi-step work. They can be triggered by apps, recurring schedules, or webhooks, and subagents now run in the background while you keep chatting with the main agent.
• Skills. Reusable playbooks agents attach to. Agents write their own skills, run their own code, and improve them over time based on how runs actually go.
• Company Brain. Your company knowledge in one indexed place. You can sync Slack, Gmail, Google Drive, Notion, Salesforce, Gong, and Linear so agents answer with real context instead of guessing.
• Connectors and MCP. Over 300 connectors, plus MCP servers and custom apps your team builds. Every tool call gets traced through one logging layer.
• Artifacts. Agents build dashboards, forms, presentations, and small apps you can share on a link. You can publish them on a custom subdomain or on your own company domain.
• Teams and sharing. Owner, editor, viewer, and use-only access, granted to a person, a team, or the whole organization.

For example, I created a SEO agent that pulls my Google Search Console data, as well as my conversion data from PostHog, to create a full SEO/AEO dashboard.

What makes that possible is not a builder. It is four things working together.

• Connectors: This agent has Search Console, PostHog, Ahrefs, DataForSEO (free in Gumloop), Firecrawl, Google Analytics, Google Sheets, and Webflow attached. It reaches the data itself.
• Skills: This is where my actual methodology lives. My keyword research process, my topical authority framework, how I decide what counts as a decaying page. The agent reads the skill and runs it the same way every time.
• Reflections and evaluations: The agent reviews its own runs and updates itself. I have self-updates turned on, so the skill gets sharper the more I use it.
• Artifacts: The dashboard is not a report the agent typed out. It is a real page I can open, share, and refresh.

I wrote the manual version of parts of this workflow in one of my newsletter editions a while back. It took me a couple of hours every time I ran it. The agent does it in a few minutes.

The drag-and-drop builder is gone

When I first reviewed Gumloop, it had a drag-and-drop canvas. You found the nodes you wanted, dragged them onto a canvas, connected them, and hit run. I spent a lot of this review talking about it.

That is not how Gumloop works anymore. The node canvas and the whole Flow concept have been retired. You do not build automations by assembling nodes. Now you just simply talk to the chat and it will figure out what tools it needs, and create automations for you. And from there, all you do is tell it to create a skill (based on any workflow you chat with it about) and it will create and save the right sklls.

The ability for Gumloop to just spin up skills is what really surprises me. It's better than any other agent builder I've used.

Where agents live

In Gumloop, you can organize your agents the same way you would in a Google Workspace.

I structure mine in folders. This way others on my team can also easily access them and know how I've grouped them. Each agent can also be accessed off of the Gumloop platform. You can actually talk to your agents via email, Slack, or Microsoft Teams. You can also set triggers that can run on a schedule, app event, or from a webhook.

Now let me talk about what all of this costs.

Related reads: Gumloop vs n8n: An honest comparison

How much does Gumloop cost?

One of the first things I thought about the platform, well after I figured out what it does, was the price. No-code AI tools are generally not cheap because they are essentially a “middleman” between the thing you want to do and existing LLMs and APIs from different software tools.

Gumloop has a freemium SaaS pricing model. The plans work based on credits that you use to run your Flows and Agents. With their free plan, you get 5,000 credits per month. From there, you will need to upgrade to get more credits.

Gumloop’s pricing plans

Here are Gumloop's current pricing tiers:

• Pro: Free 14-day trial, then starts at $37 per month for 20,000 credits, then pay-as-you-go (1 credit = $0.005). This plan includes unlimited seats, unlimited teams, GitHub skill sync, and access to both frontier AI models as well as open-weight models. You can also bring your own API keys.‍
• Enterprise: Custom pricing. Includes everything in Pro plus role-based access control, SCIM/SAML support, admin dashboard, audit logs, custom data retention, incognito mode, AI model access control, virtual private cloud (VPC), and workflow queuing.

If you want to compare all the features of each plan side-by-side, check out their pricing page.

Max (their CEO) gave me a 20% off coupon code when I met with him. So if you want to use the same promotion code when checking out, use code: MARKETERMILK

This will bring down the Pro plan from $37 per month to $29.60 per month!

How Gumloop's pricing works

I know the pricing can seem a bit confusing at first, so here's a bit more details about the pricing model:

• 1 credit equals $0.005, so $1 buys 200 credits
• Model calls bill at cost, converted at that same rate
• Every successful tool call costs at least 1 credit, and enrichment or scraping tools charge more on top
• Compute is 5 credits per session-minute of active work
• An orchestration fee of 8% gets added on top of those three
• Workflows are billed on node costs only, and most native nodes cost nothing
• Overage runs at $0.005 per credit, capped by default at 1,000,000 overage credits per billing period on Pro
• Bring your own key and the model portion drops to 0 credits, though the orchestration fee doubles to 16 percent

Basically the TLDR is that Gumloop passes the exact costs of using different LLMs and APIs/MCP servers from other tools. You just pay an 8% orchestration fee for using Gumloop's cloud-based agent harness.

Gumloop's customer support

Okay, you might be asking why I even included this section. I believe that every company that offers a product or service should have great customer service.

People want to know that when they invest in you, you are also going to be there to help them when they run into any problems or questions.

So let’s talk Gumloop customer support.

If you need to get in contact with Gumloop’s customer service, you can email them at founders@gumloop.com.

They’re also active on social media and YouTube so you can message them there as well.

There are also tons of support documents and a community forum that acts as a community helpdesk to ask questions or find answers to existing questions. There’s even a Slack channel for users so you can get quick answers from the Gumloop team.

You can also hire an automation expert through your admin dashboard. You will have to be logged in to access that feature.

As the company grows, I do suspect there will be even more forms of support as well. When I first wrote this review, Gumloop's stated goal was to build a 10-person billion-dollar company. That vision has evolved. In March 2026, they raised a $50 million Series B led by Benchmark (with participation from Shopify Ventures, Y Combinator, First Round Capital, and others), bringing their total funding to $70 million. Max has acknowledged that the surge in enterprise demand means they are now actively scaling up their sales and engineering teams. So the 10-person dream has shifted into something bigger.

My only worry with that great companies are built with great people. Of course, AI is going to progress and we will have so many parts of a regular tech job be automated. But people want companies to feel human. And when you use AI for all of your customer service efforts, it starts to dehumanize your company. The challenge is going to come on the customer service front when a company grows — I know this from my time working at Webflow and watching that company grow into a multi-billion dollar company.

Regardless, I’m rooting for that goal and want it to come true. But something to think about as the company scales.

Gumloop scalability (and security)

Large companies like Shopify, Ramp, Gusto, Instacart, Samsara, and Opendoor currently use Gumloop. That should show the scalability and security of the platform.

From day one, Gumloop has been enterprise-ready by default. The platform is SOC 2 Type 2 and GDPR compliant, it does not use your data for any training models, it’s SOTA encrypted, and there’s access control for different users and team members.

Gumloop has also launched a product called Gumstack, which is built specifically for enterprise security and observability. It gives security teams a single dashboard to monitor all AI agent activity across the organization. It includes SSO and SCIM support, role-based access control, per-tool authorization, tool call traceability, and MCP inventory auditing. If you are evaluating Gumloop for a larger team, Gumstack is worth looking into.

Overall, it’s a trustworthy platform. And if it wasn’t, I probably would have not spent most of my Wednesday writing up this review. If you want to learn more about their policies, you can check it out here.

Gumloop pros and cons

After using Gumloop for over a month, using the pre-built templates, and creating my own Flows from scratch, I have some opinions. I see both strengths and weaknesses in the platform. Let me go over them.

Gumloop pros

Here’s what I love about Gumloop:

• Amazing user experience: The Gumloop UI/UX is so good. It's better than most AI agent platforms I've used. You can tell the team really understands how to build products that are delightful to use. I often judge products by the emotional response they create, and Gumloop just feels good to use.
• Skills: This is the feature I didn't expect to care about as much as I do. A skill is basically a written playbook your agent follows. I have my keyword research process, my topical authority framework, and my content decay rules all written as skills. The agent runs them the same way every time. It's the difference between an AI that guesses at your job and one that actually does it your way.
• Agents that improve themselves: Reflections and evaluations let the agent look back at its own runs and update its skills. I have self-updates turned on. My SEO agent is better today than the version I set up, and I didn't touch it.
• Most of the integrations you need: Gumloop connects to almost any tool in your tech stack, with 300+ connectors plus MCP servers and custom apps your team builds. My SEO agent alone has Search Console, PostHog, Ahrefs, DataForSEO, Firecrawl, Google Analytics, Google Sheets, and Webflow attached to it. In my original review I complained that there was no Search Console integration. They shipped it, and now it's the connector I use most.
• Model-agnostic: Gumloop lets you choose which AI model powers each agent. Claude, GPT, Gemini, Grok, and open-source models like DeepSeek, Kimi, GLM, and Qwen are all in there, with open source as the default. It means you're not locked into one provider and you can trade cost against quality per agent. You can also bring your own API key, which drops the model portion of your bill to zero credits.
• Agents meet you where you work: My SEO agent is available over email, in Slack, in Microsoft Teams, and on a hosted page. I don't have to log into Gumloop to use the thing I built in Gumloop.
• Secure: The fact that they don't use your data to train anything is great. And they have to make it this way or else larger enterprises would not be open to using them. This gives smaller business owners and even service providers peace of mind knowing our client data will not be leaked anywhere.

Overall, the pros definitely outweigh the cons. However, there are some things that bother me.

Gumloop cons

Here are a few things that I wish would be improved:

• Limited instant support: At the time of writing this, there is no live chat option for support on the website. You’ll either have to troubleshoot on your own through the forum or wait for someone to answer your questions via email or the Slack community.
• Editors note: I used to have a con for needing a smaller tiered plan because the paid plan used to start at $97 per month. Gumloop has listened and simplified their pricing over time. The paid plan (now called Pro) starts at $37 per month with unlimited seats, which is a big improvement from where they started.

Honestly, that’s it for the cons right now that I’ve personally experienced. I’ll keep an eye on anything and update this article accordingly (as I've continued to do).

TLDR: My final thoughts

If you made it this far, you probably have a good idea of who Gumloop is for, what it does, and how it works. But if you’re just skimming through and now you’re reading this part, here’s a summary of everything you need to know.

Is Gumloop worth it?

✅ Yes, if you’re looking for a tool to create and deploy cloud-based AI agents, this is the best platform I’ve personally found and used so far. Think of the platform as a company-wide agent layer that sits on top of your existing tools.

What makes the platform unique?

The tool has an amazing user-friendly interface and is easy to use. You describe what you want in a chat and the agent builds it. You can also create Skills, which is essentially when you write down how you do a task so your agent runs it that way every time. It's like having functions when you're programming. I have yet to see another platform in this space be able to do this.

Give the platform a go and test it for yourself. The 14-day free trial will allow you to get a feel for it. If you decide to upgrade to a paid plan, use the promotion code MARKETERMILK at checkout to get 20% off your monthly subscription.

And if you find some cool use cases, email me about it (my email is in the footer). I’d love to see what you’re working on!