Lindy vs. n8n: 10x simpler, just as powerful 

n8n requires advanced knowledge of JavaScript, JSON, SQL, and APIs to manage basic setup and functions.

Integrations have to configured manually, with API keys and access tokens to be required for most systems, including LLMs.

Lindy takes care of the configuration, so all you need to do to build your first agent is log on.

Lindy has every LLM in product, and native integrations that make connecting as simple as in-product SSO.

You need to build workflows on n8n node by node, manually configuring every condition and output.

It’s robust but requires technical skills and a lot of time, which can slow down AI adoption and limit teams from innovating with AI.

Build a custom AI agent on Lindy with a prompt. Give feedback or make changes directly in the flow editor.

Either way, no code is required, so you can move faster without relying on engineering.

If you get an error, you have to parse JSON strings to find the inconsistency and transform the data with Javascript.

Everything that is fixed in n8n has to be done manually, and it’s often a technical fix.

Because Lindy uses AI to build agents for you, it can also use AI to fix them.

Lindy's Agent Builder can tests, troubleshoot errors, and rebuild workflows to be production-ready without you doing anything.

With n8n, you have to give it a memory module to remember anything, with choices ranging from Chroma to pgVector to Qdrant.

Lindy remembers previous conversations by default without needing configuration, so agents can learn over time and improve.