There are two genuinely different products being sold under the same banner, and confusing them is the most expensive mistake in this category.

Layer one: frameworks

CrewAI, LangGraph, AutoGen, Paperclip. These give you primitives — agents, tasks, state, delegation — and expect you to assemble the rest. They are typically free or near-free to licence, which is what makes them look cheap.

They are not cheap. The licence is free; the operating cost is an engineer. You are signing up to write the orchestration, host it, monitor it, debug it at 11pm, and pay uncapped model bills on your own API keys. For a team with engineers who want that control, this is exactly right and nothing else will satisfy them.

Layer two: platforms and builders

Lindy, Relevance AI, n8n. No-code or low-code builders that remove the programming but keep you as the operator. You still design the automation, wire the integrations, watch the credits and maintain it as your business changes.

These are a genuine step up in accessibility. The catch is usage-based or credit-based billing, which makes monthly cost hard to predict, and the quiet assumption that someone on your side enjoys building automations. Many people discover they do not.

Layer three: managed services

Here somebody else operates the system. You describe the business, they build the agent team, connect it to your accounts, cap the spending, supervise the output, and hand you approvals and a report. You are buying the result, not the capability.

The cost is higher per month and the control is lower. That is the trade, and it is a real one — if you want to change how something works you ask rather than edit.

How to tell which layer you are

Do you have engineering time you are willing to spend on this? If yes, a framework will beat any service on flexibility and cost.
Have you already abandoned an AI tool at the setup stage? If yes, the problem is the model of the product, not the tool. A different builder will end the same way.
Can you predict your monthly AI spend today? If not, credit and usage billing will surprise you, and an all-in price is worth paying for.
Who gets blamed when the output is wrong? If the honest answer is "nobody currently", you need supervision more than you need software.
Is the work deterministic? Fixed, repeatable steps belong in an automation tool like n8n. Work needing judgement does not.

A test that cuts through it

Ask what happens the week after you buy. With a framework, the week after you buy is when your work starts. With a managed service, it is when theirs does. Neither answer is wrong — but only one of them matches what you were hoping for.

The cost comparison people get wrong

Framework pricing pages show licence cost. The real bill has three lines: licence, model API spend, and human time. Model spend is usually larger than the licence and is uncapped by default. Human time is almost always the largest line and never appears on any pricing page.

When you compare a free framework against a $899/month service, compare all three lines or the comparison is meaningless.

Where we sit, plainly

My Cloud Company is layer three, and we build on Paperclip — an excellent MIT-licensed framework from layer one. If you are technical, take Paperclip and run it yourself; it is genuinely free and genuinely good. We exist for the people who want the output without the terminal.

We have written head-to-heads for each of the main options, including where they beat us: CrewAI, LangGraph, Lindy, Relevance AI and the full list.

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Agent frameworks vs managed AI agents: which one fits your business