Extract, chunk, embed text
Revenue by region Figure 2. Net revenue per quarter, USD millions (synthetic data) EMEA APAC AMER 60 40 20 0 Q1 Q2 Q3 Q4 52
The bars are gone. A lone 52 floats with no region and no quarter.
Case study by NerdWare Tech. The demo runs on sample pages; numbers marked illustrative are not measurements.
Search the page, not the text.
We embed PDF pages as images, so the tables and charts that text extraction destroys stay answerable.
Interactive retrieval demo
- Coarse pooled search1 vector per page
- MaxSim rerankfull multivector
- VLM answerwith bbox citation
Light table
6 pages indexedcoarse MaxSim (illustrative scores)
Page viewer
Cited answer
illustrativeThe VLM only sees the top pages, as images, and has to point at the region it used.
One page in, one cited region out.
Five stages. Select one to see what it hands to the next.
MaxSim, one query token at a time.
Every query token finds its best-matching patch on the page. The page score is the sum of those maxima.
Page
Query token (qi)
Score(Q,D) = Σi maxj ( Eqi · EdjT )
Why not chat with your PDF.
Chat-with-PDF flattens a page into text before it ever searches. Here is the same chart both ways.
Embed the page as an image
Bar height, colour and axis stay together. The answer points at a box.
Tables stay tables
Rows and columns keep their geometry. No parser guesses where a cell ends.
Citations you can check
The answer returns a page and a normalised box, so a reviewer looks at the evidence, not a chunk id.
No OCR stage to maintain
One model reads layout, figures and text. Fewer moving parts to fail silently.
It can be measured
ViDoRe gives page-level relevance labels, so retrieval is scored before any LLM is involved.
Scored on retrieval, before any answer.
ViDoRe-style evaluation against a dense text bi-encoder. These bars are illustrative, not results.
Metric
TARGET, ILLUSTRATIVE
Latency budget per query (target)
Stack.
Have documents your search can’t read?
Tell us what you need answered from them. The demo above uses sample pages.
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