Paper & scanned records
Paper & Scanned Records Analysis
Ten thousand pages of crooked scans, faxes and handwritten margins. You need to know what is in them, what is missing, and be able to point to the page.
The problem
Paper productions, medical records, decades-old business files and agency responses still arrive as images. Review platforms index them poorly: the OCR is whatever the scanner produced, handwriting is invisible, and a fax-of-a-fax becomes a page that searches as blank.
Automated summarization makes it worse rather than better. A model will describe a corpus fluently whether or not it read it correctly, and bad text extraction turns quietly into bad analysis.
This service closes that gap. Extraction is calibrated on your material before the full set runs, every finding cites a page, and anything that could not be read is reported rather than guessed.
What you get
- Calibrated OCR with an accuracy report measured on your material, not a vendor's benchmark
- Chronologies and timelines built from the record, every entry citing document and page
- Medical record summaries with treatment timelines and provider-by-provider breakdowns
- Issue-coded indexes across the full production, including handwritten and stamped material
- Gap and completeness analysis — what the production implies exists but does not contain
- Entity, date and amount extraction across a corpus too large to read linearly
- A log of every page that could not be read reliably, so the exposure is known before opposing counsel finds it
- Searchable, cited working files loaded back into your review platform or delivered in standard formats
How the work runs
Representative sample
A few hundred pages establish the real condition of the record: scan quality, layout variety, handwriting, stamps, duplicates.
Calibrated extraction
Text extraction is scored against controlled ground truth on that sample before the corpus runs, so the error rate is measured rather than assumed.
Independent cross-checking
Findings are re-derived by independent passes; disagreements are escalated to a reviewer, never silently resolved.
Cited delivery
Every assertion resolves to a page. The accuracy report and the unreadable-page log ship with the work product.
Common questions
How is this different from running OCR in our review platform?
Platform OCR is a single pass with no measurement. Here the extraction is tuned to the document population, scored against known-good text, and reported with a per-page confidence, so counsel knows which pages to trust and which to read by eye. Handwriting, stamps and marginalia are extracted separately and flagged, rather than dropped.
What about handwriting and marginalia?
Handwritten notes, stamps and annotations are treated as first-class content and extracted separately from printed text, because confidence in them is genuinely lower. They are surfaced with that lower confidence marked, so a reviewer knows where to look.
Can this go back into our platform?
Yes. Improved text, coded fields and chronologies can be delivered as overlays or load files for the platform you already use, so the work product lives where the review team works.
Can you support a declaration about the process?
The methodology, the calibration results and the processing log are documented to support a declaration describing how the analysis was produced. Expert opinion testimony is a separate question, discussed at scoping.
What size production is worth this?
Any production large enough that reading it linearly is unattractive. In practice that is a few thousand pages to a few hundred thousand.
Start with a scoping call and a sample
Tell us about the matter and the data. For anything document-heavy, a representative sample under an appropriate agreement lets us return a processed slice, an accuracy report on it, and a fixed price for the full job before anything is committed.