Lindy built a real following by turning “AI employee” from a buzzword into something you can actually hand your inbox to. It drafts replies, preps your meetings, and runs scheduled routines without you touching a workflow builder. For a lot of teams, that’s exactly the point: no nodes, no flowcharts, just a teammate in Slack.
But Lindy is priced and built around a specific shape of work, and that shape doesn’t fit everyone. Every active seat draws from a shared credit pool starting at $29.99 a month for 3,000 credits, and a single “big build” (a dashboard, a multi-source report) can eat 1,000 to 2,500 credits on its own. If your team needs agents that write and run real software, not just summarize and draft, Shogo is one option built for exactly that. If you simply want more seats without pricing per credit pool, there are several more worth knowing about.
Here are seven alternatives, what each one actually does differently, and who it suits.
1. Shogo
What it is: A harness that AI agents use to build and run real software, dashboards, trackers, internal tools, rather than an assistant that drafts and summarizes inside your existing apps.
Strengths: Paid plans are unlimited within fair-use 5-hour and weekly windows instead of a credit pool, starting at $8 a month for one user. Auto-route sends each request to an economy, standard, or premium model automatically, all behind one Shogo API key across Anthropic, OpenAI, Google, and xAI. The platform also connects to more than 1,000 bridges and close to 900 ready-made skills, and the client SDK and platform core are open source, so you can inspect or self-host what the agents do.
Weaknesses: The full model lineup is part of the Pro plan at $20 a seat; the $8 Basic plan runs on a single fast model. Auto-route also assigns a model tier rather than letting you hand-pick the exact model for one specific task the way Lindy’s per-task picker does.
Best for: teams who want an AI agent to build and own real internal software, not just operate inside existing apps, and who want pricing that doesn’t move every time usage goes up.
2. Gumloop
What it is: A node-based canvas for building AI agents and automations, aimed at teams who want to see and edit the logic behind every step.
Strengths: Gumloop’s visual builder makes it easy to chain tools, branch logic, and bring your own model key. The Free plan includes 2,000 credits and one trigger-based flow, enough to test a real workflow before paying. Bring-your-own-key users skip the model cost entirely and pay a lower effective rate through the reduced credit draw.
Weaknesses: Every run is billed across four components: the model, each tool call, compute time, and an 8% orchestration fee on top of all three (16% if you bring your own key). That’s a lot of moving parts to predict a bill from. The Pro plan starts at $37 a month for 20,000 credits, and heavier agent runs with multiple tool calls and long compute times can burn through that fast.
Best for: technical users who want fine control over workflow logic and are comfortable reasoning about a four-part credit formula.
3. n8n
What it is: An open-source, node-based workflow automation tool that has added AI agent and MCP nodes on top of its original automation core.
Strengths: The self-hosted Community edition is free, and n8n has one of the largest open libraries of pre-built workflow templates of any automation tool. For teams with engineering resources, hosting it yourself removes the per-execution cost entirely.
Weaknesses: The hosted Cloud plans meter by execution, starting at €20 a month for 2,500 executions on the Starter tier. Complex AI agent workflows with loops and retries can use up that allowance quickly, and self-hosting shifts the cost from a subscription to engineering time spent on maintenance and updates.
Best for: engineering teams that want full control over their automation stack and are willing to self-host.
4. Zapier
What it is: The most widely connected automation platform, now extending its no-code Zap builder into AI agents, an SDK, and MCP support.
Strengths: Zapier connects to more than 9,000 apps, more than any competitor in this list, and its interface is the easiest on this list for a non-technical person to pick up in an afternoon. The free plan includes 100 tasks a month to get started.
Weaknesses: Every step in a Zap, every AI action, every MCP tool call, and every SDK call draws from one shared task pool. Paid plans start at $19.99 a month on the Professional tier, and as you add AI processing and longer workflows, task consumption climbs in ways that are hard to predict in advance. Each MCP tool call alone uses two tasks.
Best for: teams already standardized on Zapier’s app ecosystem who want to add light AI steps without switching platforms.
5. Relevance AI
What it is: An “AI workforce” platform built for companies deploying many agents across a large organization, with calling, meeting, and evaluation features aimed at enterprise rollouts.
Strengths: The platform includes agent evaluation and A/B testing tools that most competitors don’t offer, along with SSO, RBAC, and audit logs built for enterprise governance from the start.
Weaknesses: Relevance AI has moved to an enterprise-only, custom-quote pricing model. There’s no public self-serve tier or published starting price, so a smaller team has to go through a sales conversation just to see numbers.
Best for: larger organizations ready for a guided enterprise deployment rather than a self-serve trial.
6. Dust
What it is: A workspace-based AI agent platform built around connecting company knowledge (Slack, Notion, GitHub, Drive) to custom agents your team builds together.
Strengths: Dust gives every seat access to more than 20 frontier models and includes US and EU data residency on its Business plan, which matters for teams with data-location requirements. The Free plan includes 500 credits to try real workflows.
Weaknesses: Pricing is in euros and scales per seat with a credit allowance behind it: Pro is €24 a seat a month for 8,000 credits, and Max is €120 a seat a month for 40,000 credits. Teams with uneven usage across seats can end up with some people hitting limits while others barely touch their allowance.
Best for: teams centered on Slack and Notion who want agents grounded in company knowledge with strong data-residency controls.
7. Beam AI
What it is: An automation platform priced by task volume, aimed at teams automating specific, repeatable business processes end to end.
Strengths: The Free plan includes 20 tasks a month with self-healing outputs, a reasonable way to test one real process before committing. Beam’s output evaluation step checks agent work before it’s considered done, which adds a layer of quality control most lighter tools skip.
Weaknesses: The jump between tiers is steep. Pro costs $50 a month for 200 tasks, and the next tier up, Scale, costs $3,990 a month. There’s no middle ground for a team that’s outgrown 200 tasks but isn’t ready for a four-figure monthly bill.
Best for: teams automating one or two well-defined, high-value processes who can fit inside 200 tasks a month or are ready to scale into an enterprise contract.
How to choose
If what you need is inbox triage, meeting notes, and scheduled routines inside a Slack-first workflow, Lindy still does that job well, and its approvals-before-action design is genuinely reassuring for first-time users.
If your team is outgrowing “draft my replies” and starting to ask for actual internal tools, like a dashboard pulling from three systems, a tracker your ops team can edit, a workflow that used to live in a spreadsheet, that’s a different kind of request. That’s software, not a reply draft, and it’s worth checking whether your current tool can build it at all before you spend another quarter stitching it together by hand.
Credit pools and task meters also affect cost in a way that’s easy to underestimate as usage grows. We broke down the real math behind credits, per-task billing, and unlimited-usage plans in our guide to AI agent pricing models, worth a read before you commit to a plan.
FAQ
What’s the best Lindy.ai alternative for building real internal tools, not just automating tasks?
Shogo is built for this specifically. Instead of running actions inside existing apps, Shogo’s agents write and ship working software, dashboards, trackers, internal tools, that your team owns outright, with pricing that doesn’t meter by credit.
Is there a free Lindy alternative?
Gumloop, n8n (self-hosted), and Zapier all offer usable free tiers. Shogo also has 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 a single user with unlimited usage, and Pro is $20 per seat a month for a small team, both without a credit pool to manage. For comparison, Lindy starts at $29.99 per seat a month and Gumloop’s Pro tier starts at $37 a month before its orchestration fee.
Does Lindy require approval before taking action?
Yes. Lindy requires approval for anything with outside impact, like sending an email or publishing a document. Read-only lookups don’t require approval.
Can I switch between AI models without switching platforms?
With Shogo, yes. Auto-route sends each request to the model tier suited to it, and Anthropic, OpenAI, Google, and xAI models are all available behind one API key. Lindy also lets you pick a model per task. Zapier, n8n, and Beam AI are generally tied to the models they’ve integrated rather than offering full provider choice.
What’s the difference between a credit-based platform and one with unlimited usage?
A credit-based platform (Lindy, Gumloop, Dust, Beam AI) charges per action, and heavier tasks use more credits, so cost scales with how much your team actually does. A platform like Shogo with unlimited usage inside fair-use windows charges a flat seat price regardless of how many actions you run within that window, which makes monthly cost predictable even as usage grows.
