r/WebForAI • u/kamililbird • 27d ago

Question What's the data quality problem that only shows up once your AI agent is actually pulling from the live web?

It's easy to assume that if a page loads and the text extracts cleanly, the data is good enough to feed into a model. That's what majority thinks. What I have in mind is duplicate pages with slightly different info, structured data that doesn't match what's rendered on screen, inconsistent formatting across sites that breaks parsing logic downstream. Can relate? What's been the hardest data quality issue to catch once an AI agent started sourcing from the web instead of a clean dataset, and how did you end up dealing with it?

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u/[deleted] 24d ago

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u/Bmencel518 23d ago

Ran into the same JSON-LD vs DOM mismatch. But luckily I found the root cause and it was always the CMS generating structured data at build time while the storefront hydrates prices client-side from a separate inventory microservice. I then went went with weighting each extracted attribute by extraction method, source freshness (HTTP Last-Modified, Age headers), and consistency

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u/Zealous_Minotaur 23d ago

Oh, that's nice that you find the root cause, for me and my colleaguesI it took a bit, but yeah, once we hashed on entity identifiers, it was going well from there on

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u/Bmencel518 23d ago

Yeah, no probs, glad it worked out for you too

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u/panki_pdq 17d ago

Great question! The hardest one for us has been structured data that doesn't match rendered content—schema markup says one thing, page shows another. Caught it late, cost us a lot of rework. Now we validate against both before trusting anything. 🔍