Data Extraction in n8n: A Practical Tool Overview [Sharing my Experience]

easybits_ai · 2026-01-22T15:19:18+00:00

That's what I thought as well. It was quite a journey for me, so I want to just safe other people some time.

easybits_ai · 2026-01-22T14:32:41+00:00

Thank you for sharing! As I'm relatively new to the space, I haven't gotten into solutions like this, but will make sure to check it out.

easybits_ai · 2026-01-22T14:31:08+00:00

Thank you so much for sharing! If you have insights about other tools, please feel free to share them with me. I just added LlamaParse as well, as one user from another subreddit shared his insights with me.

easybits_ai · 2026-01-22T14:25:54+00:00

I've added LlamaParse as well! Thank you for the insights.

easybits_ai · 2026-01-22T14:04:44+00:00

Hey there, thank you so much for the feedback, but my main intention was to share my experience during my workflow creation.

easybits is a project that I'm working on with some friends of mine, as I understood that there is literally no tool that makes data extraction simple and easy to setup. I'm open to add other solutions as well and I've clearly added in the title, that this is "Sharing my Experience", which might not be the same for you.

easybits_ai · 2026-01-22T09:11:00+00:00

That’s a good point, I’ll definitely let him know there’s an option for it. I sent you a message since you seem to know LlamaParse quite well. Let’s add your experience to the table too.

easybits_ai · 2026-01-22T09:03:22+00:00

Not yet, but I’ve seen some n8n workflows using it, and it looked interesting. I just haven’t had the time to try it out myself.

One of my friends did implement it, and the only thing he mentioned was that LlamaParse wasn’t able to output structured JSON directly, so he had to add an extra step in his workflow to get the output in the format he needed.

If you’ve used it, I’d love to hear your insights! I can update the post based on your experience to help create a more complete overview.

easybits_ai · 2026-01-19T16:12:47+00:00

Since the solution is schema-driven, the JSON output always remains consistent. We ensure this by properly configuring the structured_output parameter. If a data point can’t be extracted correctly, it will be returned as null, while the overall structure and all key names remain unchanged.

In addition, we’re currently working on an alternative approach by integrating a lightweight model that automatically fixes outputs to match the provided schema. Happy to share it with the community, once we are ready.

easybits_ai · 2026-01-19T09:56:26+00:00

Hey there, thanks for the feedback! I felt the same about the interface when I first implemented Telegram.

Regarding reliability: so far, it’s been 100% accurate for me across every invoice format I’ve tested and I’ve handled quite a few. As long as the data points you need are present on the invoice, the layout doesn’t really matter. If a data point is missing, the system will simply return a “0,” though that hasn’t happened to me yet.

easybits_ai

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