Turn scanned PDF archives into searchable, structured data
Years of paper records, box files, and scanned PDFs don't have to stay locked away as images. Convert them into structured, machine-readable data your team can actually search and use.
Built for old paperwork, not just new documents
An archive digitisation project usually starts with a box, a folder, or a shared drive full of PDFs that were scanned once and never processed further — different print quality, different eras of paperwork, sometimes different languages within the same archive.
Scanned and photographed pages
Reads paperwork that was scanned, photocopied, or photographed — not just born-digital PDFs.
Built for volume
Digitising years of paper archive means processing many documents, not one at a time by hand.
Multilingual Indian documents
Reads documents in English and regional languages commonly found across older Indian business paperwork.
Searchable, structured output
The result is machine-readable content and structured fields, not just a scanned image with no text layer.
An archive you can search beats a box of paper
Many Indian businesses hold years of paperwork — old contracts, historical invoices, correspondence, compliance records — as scanned PDFs or physical files that were photographed once and never looked at again. A scanned page with no text layer isn't searchable: finding one document means someone opening files one by one until they find it.
That cost compounds every time the archive is needed again — a compliance request, a legal discovery process, or simply a new team member trying to find how a past situation was handled. Each of those becomes a manual search through images instead of a lookup against searchable content.
Digitisation reads the layout, text, and tables on each scanned page and produces structured, machine-readable content — so an archive becomes something your team can search and query instead of a folder of images.
For records, compliance, and legacy-paperwork teams
A records or admin team migrating off physical filing, a compliance team that needs to produce a specific old document on request, and any business that inherited years of scanned paperwork from a previous system or acquisition all face the same problem: the documents exist, but finding one means someone searching through folders of scanned images by filename and hoping it's labeled correctly.
Digitisation turns that folder of images into something searchable by content — so producing a specific old invoice, contract, or record during an audit or a compliance request doesn't depend on someone remembering where it was filed.
Full-document digitisation, or specific fields
Archive digitisation typically means converting the full content of each page into searchable text and tables, rather than pulling a fixed set of fields — useful when the value of an archive is being able to find and read any document in it, not just look up a handful of data points.
If your documents are a specific type — invoices, GST forms, bank statements, or contracts — targeted field extraction may get you cleaner structured data faster. See both approaches, and the AI reasoning layer behind them, on the DocumentsAI homepage.
Either way, output is designed to be reviewed rather than trusted blind — scanned archives often include faded pages, handwriting, or damaged sections where automated reading can struggle, so digitised results from an older archive are worth spot-checking against the source before they become the system of record.