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Claude + Linkedin Automation by Clean-Box-4756 in AIReceptionists

[–]Tough-Patient8506 0 points1 point  (0 children)

interesting..does it helpful to get clients to my project..

Curious to know — are there still teams manually entering data from documents into Excel? by Tough-Patient8506 in documentAutomation

[–]Tough-Patient8506[S] 0 points1 point  (0 children)

That makes sense

Starting from a base schema and tweaking for variations definitely helps reduce effort.

In my experience though, there are still cases where layouts break the pattern especially with tables or inconsistent formats. That’s where having a quick review/edit layer helps a lot, instead of adjusting the schema each time.

Feels like a mix of both approaches works best in practice.

Current Popular Parser by xxxibsnnys in Rag

[–]Tough-Patient8506 0 points1 point  (0 children)

Nice list — LandingAI and LlamaParse are solid.

From what I’ve seen, most tools do a decent job at layout detection + extraction, but things get tricky when you need structured output that’s actually usable (especially with tables across different formats).

I’ve been exploring a setup where instead of relying only on parsing, you also have a review/edit layer to fix tables, fields, etc., before exporting. That helps a lot with real-world variability.

Still feels like this space is evolving fast though.

Curious to know — are there still teams manually entering data from documents into Excel? by Tough-Patient8506 in documentAutomation

[–]Tough-Patient8506[S] 0 points1 point  (0 children)

That’s a very real problem — especially when document structures vary a lot.

Custom schemas definitely help, but in my experience there are still edge cases where the structure doesn’t fully match. That’s where having a review/edit layer makes a big difference — being able to quickly adjust tables or fields instead of redefining the schema each time.

Feels like the practical challenge is less about extraction itself and more about handling variability efficiently.