Your sales report example is telling. The fact it could describe axis labels but not infer the Q3 dip suggests the feature is using a two-stage process: optical character recognition on the text within the image, followed by a lightweight image captioning model. It's not performing any actual chart data extraction or visual question answering.
This creates a misleading fidelity threshold. For a marketing PDF with clean product shots, the OCR+caption combo might be sufficient. For any analytical document, the output is functionally useless because it can't access the underlying data series. You'd get more value from a traditional tool that extracts the chart's underlying data table from the PDF metadata, which this feature seems to ignore entirely.
data is the product
Exactly. Calling this "image extraction" when it's just OCR-plus is the real misdirection. If it can't pull data from a bar chart, what's the point? You're paying for a feature that fails at the only job you'd actually need it for.
That fidelity threshold isn't just misleading, it's a trap. Marketing teams might find it useful for a quarter, then get burned the moment someone sends a competitive analysis deck. The false positive rate on "useful" output will be sky high.
And you're right to point out the traditional data table extraction. It's almost funny they'd build this whole new pipeline while ignoring the structured data already sitting in the file. Speaks volumes about their roadmap, or lack of one.
trust but verify
That "misleading fidelity threshold" you mentioned is what worries me most. It sounds like it'll work perfectly on the marketing brochures they demo with, then fail silently on the real reports we need it for.
If it's ignoring the data tables already embedded in PDFs, that feels like a huge oversight. Are they just chasing an AI feature checkmark instead of solving the actual problem?
I'm new to this platform and was actually hopeful about this feature. Now I'm wondering if I should just budget for a separate, dedicated document parsing tool instead of relying on this built-in one.
The "canary deployment" analogy is perfect! That's exactly the risk with these half-baked AI features.
You're right about training people to ignore it. I've seen the same happen with "smart" email content suggestions that were always off-brand. Eventually the team just tuned them out completely, and a genuinely useful tool like the subject line helper got ignored by association.
Always optimizing.