Gumloop earned its following with a genuinely good visual canvas. You drag nodes, wire up tools, and watch an AI agent run step by step in front of you, which makes it one of the easier places to actually understand what your automation is doing while you build it.
The part that trips people up is the bill. Every run bills across four separate components: the model call, each tool call, compute time, and an orchestration fee on top of all three, 8% normally or 16% if you bring your own model key. The Pro plan starts at $37 a month for 20,000 credits, and a single agent conversation with a few tool calls and a minute of compute can rack up more credits than it looks like it should. If you want to build agents without reverse-engineering a four-line billing formula every time a bill looks high, here are seven other places to look, including Shogo, which skips the credit system entirely.
1. Shogo
What it is: A platform where you describe what you want built, a dashboard, a tracker, an internal tool, and the agents write real software behind it, instead of assembling a workflow out of nodes on a canvas.
Strengths: Billing is unlimited within fair-use 5-hour and weekly windows instead of Gumloop’s four-part credit formula (model, tool calls, compute, orchestration fee), starting at $8 a month for one user. Auto-route picks a model tier automatically across Anthropic, OpenAI, Google, and xAI, and the platform ships with more than 1,000 bridges and close to 900 ready-made skills. The client SDK and platform core are open source.
Weaknesses: There’s no visual canvas to inspect node by node the way Gumloop’s is, so you can’t watch logic execute step by step as it runs. Every major model requires the $20 Pro plan rather than the $8 Basic tier.
Best for: teams that want an agent to build and own real software rather than assemble and maintain a workflow, and who want one predictable seat price instead of a per-run credit formula.
2. Lindy
What it is: An AI “teammate” that lives in Slack and handles inbox management, meeting notes, and scheduled routines without a visual workflow builder.
Strengths: Lindy is the fastest of this group to get a non-technical person using productively. There’s no canvas to learn: you describe what you want in plain language and Lindy builds the routine. Anything with outside impact, like sending an email, waits for your approval first.
Weaknesses: Every active seat draws from a shared credit pool starting at $29.99 a month for 3,000 credits, and Lindy isn’t built for assembling multi-step automations the way a node-based canvas is. If your team wants to see and edit the exact logic of a workflow, Lindy abstracts that away on purpose.
Best for: teams who want an AI assistant handling communication and routine tasks without touching a workflow builder at all.
3. n8n
What it is: An open-source, node-based automation platform that added AI agent and MCP nodes on top of its original workflow engine.
Strengths: The Community edition is free to self-host, and n8n has one of the largest libraries of community-built workflow templates available. Teams with engineering capacity can run it on their own infrastructure and avoid a metered bill entirely.
Weaknesses: The hosted Cloud plans meter by execution, starting at €20 a month for 2,500 executions on the Starter tier, and an AI agent workflow with retries and loops can use that up quickly. Self-hosting removes the subscription cost but adds the ongoing work of maintaining and updating your own instance.
Best for: engineering teams that already run their own infrastructure and want full control over the automation stack.
4. Zapier
What it is: The most widely connected automation platform, with a no-code Zap builder that now extends into AI agents, an SDK, and MCP support.
Strengths: Zapier connects to more than 9,000 apps, the widest reach of any tool in this list, and its no-code interface is the easiest for a non-technical team member to pick up without training. The free plan includes 100 tasks a month.
Weaknesses: Every Zap step, AI action, MCP call, and SDK call draws from one shared task pool, and a single MCP tool call alone uses two tasks. Paid plans start at $19.99 a month, and task usage is less visible up front than it is with a credit-counter interface like Gumloop’s.
Best for: teams already standardized on Zapier’s app ecosystem who want to layer in AI steps without adopting a new platform.
5. Make
What it is: A visual automation builder similar in spirit to Gumloop, built around connecting apps on a canvas with branching logic and, more recently, AI modules.
Strengths: Make’s canvas is often considered more visual and approachable than code-heavy alternatives, with a large library of pre-built app connections. The Core plan starts at $9 a month for 10,000 credits, a lower entry price than Gumloop’s Pro tier.
Weaknesses: Make’s credit consumption scales with the complexity of your scenario, and more advanced AI modules draw down credits faster than simple app-to-app connections, which can make costs climb as a workflow gets more capable.
Best for: teams who want a visual, Gumloop-like builder at a lower starting price and don’t need Gumloop’s agent-specific features like Company Brain search.
6. Relevance AI
What it is: An “AI workforce” platform built for organizations deploying many agents at once, with calling, meeting, and agent-evaluation tools aimed at larger rollouts.
Strengths: Relevance AI includes agent evaluation and A/B testing out of the box, which most node-based builders don’t offer, plus enterprise security features like SSO and audit logs from the start.
Weaknesses: The platform has moved to enterprise-only, custom-quote pricing, with no public self-serve tier. A smaller team has to go through a sales conversation before seeing any numbers at all.
Best for: larger organizations planning a guided, multi-agent rollout rather than a self-serve trial.
7. Beam AI
What it is: A task-volume-priced automation platform aimed at automating specific, repeatable business processes end to end, with a self-healing and output-evaluation layer built in.
Strengths: The Free plan’s 20 tasks a month is enough to test one real process, and Beam’s output evaluation step checks the agent’s work before calling a task done, which few lighter tools include.
Weaknesses: The jump from Pro, $50 a month for 200 tasks, to Scale, $3,990 a month, is steep, with nothing in between for a team that has outgrown 200 tasks but isn’t ready for a four-figure bill.
Best for: teams automating one or two well-defined, high-value processes who fit inside 200 tasks a month or are ready to scale into an enterprise contract.
How to choose
If what draws you to Gumloop is the visual canvas itself, seeing every node and wire before it runs, Make is the closest match at a lower starting price, and n8n is the closest match if your team can self-host.
If what you actually want is the result of the workflow, software that works and keeps working, without maintaining the canvas that produces it, that’s a different job. We wrote a full breakdown of how credit pools, per-task billing, and unlimited-usage plans actually compare at scale in our guide to AI agent pricing models, which is worth reading before you commit a team to any of these.
FAQ
What’s the best Gumloop alternative for teams that don’t want to manage credits?
Shogo’s paid plans are unlimited within fair-use 5-hour and weekly windows rather than metered by credit, so there’s no four-part formula (model, tool calls, compute, orchestration fee) to track per run the way Gumloop requires.
Is there a free Gumloop alternative?
Lindy, n8n (self-hosted), and Zapier all have usable free tiers, and Make’s Core plan starts at $9 a month. Shogo also offers a free plan with daily usage to build on a real workflow, no credit card required.
What’s the cheapest AI agent platform for a small team?
Shogo’s Basic plan is $8 a month for one user, and Pro is $20 per seat a month, both with unlimited usage and no credit pool. Gumloop’s Pro tier starts at $37 a month before its orchestration fee, and Make’s Core plan starts at $9 a month for 10,000 credits.
Does Gumloop charge extra if I bring my own model key?
Yes, in a sense. Bringing your own key means Gumloop runs the model call at 0 credits, but the orchestration fee on that run doubles from 8% to 16% to compensate.
Can I use more than one AI model on a single platform?
Yes, on several of these. Gumloop and Lindy both let you choose a model per task or node. Shogo’s auto-route automatically sends each request to an economy, standard, or premium model tier based on complexity, with Anthropic, OpenAI, Google, and xAI.
What’s the difference between a node-based builder and an agent platform like Shogo?
A node-based builder like Gumloop, n8n, or Make has you assemble and maintain the workflow yourself, one node at a time. An agent platform like Shogo builds the working software from a description and keeps evolving it as you use it, so there’s no workflow diagram to maintain by hand.
