Forms become clean data. Batches get split into properly named files. Everything lands in the folder it belongs in, and anything it cannot place gets flagged rather than guessed at.
Works with the folders, naming and systems you already use.
Example data
Read it, key it in, name it, file it, tick it off. It shows up nowhere on an org chart, and in the busy season it takes months.
Somebody reads a form and types every line in. It is slow, boring, and where mistakes come from.
Every document needs the right name and folder. Get it wrong and nobody ever finds it again.
One file arrives holding dozens of separate documents. Someone splits it by hand, page by page.
It reads the document and returns a proper table with the right headers, ready to load into whatever you already use. Work that took months in the busy season takes minutes.
Illustration
Documents arrive by email and by provider drop. It works out what each one is, names it to your convention for that type, and puts it in the client folder it belongs in.
Example filing
Providers send everything in one file. It finds where each document ends and the next begins, reads enough of each to know whose it is, names it and files it.
Example batch
A misfiled document is worse than an unfiled one, because nobody knows to look for it. Anything it cannot identify, or any client it cannot match, stops and waits for a person.
Example queue
Most teams keep a list of which documents came in from which client. Updated by hand, it is usually wrong. This updates it as each document lands.
Example board
A document type is a description of what that document says and looks like, a naming pattern, and where it goes. Add as many as you need.
Example types
We build the first document types with you, from the paperwork you already handle.
A few of each document you handle, plus the folders and names you already use. That is enough.
Your mailbox, the drop folder, and wherever files end up. Nothing changes for anyone sending them.
Everything it is sure about gets filed. You check the short queue it flagged, then move on.
A document processing app reads incoming paperwork and does the work a person would otherwise do by hand: extracting the data, splitting batches into separate documents, naming each one, filing it in the right folder and updating whatever list tracks it. Arnold does all four, and flags anything it cannot identify rather than guessing.
Any printed or scanned document, rather than one fixed form. You describe what a document type says and looks like in your own words, and it extracts the fields you name. Forms, reports, policies, statements and plans are all in scope.
It stops. An unrecognized document type or a client it cannot match is flagged and left for a person, because a document filed in the wrong folder is worse than one that has not been filed at all.
No. It works with your existing folder structure and your existing naming conventions. Your team keeps looking in the same places for the same files.
Yes. It detects where each document inside the batch ends and the next begins, reads enough of each to identify whose it is, then names and files them separately. A four hundred page batch becomes around forty properly named documents.
Volume is the point. One client processed 782 documents in about a week and a half, all of which had previously been handled by hand. Individual documents run from a couple of pages to eighty.
Anywhere paperwork arrives faster than people can key it in. Insurance and law are the sharpest fit, along with agriculture, healthcare administration and anyone dealing with regulated filings.
Fifteen minutes on your own documents, not a canned demo. You will see the data it pulls out and exactly what it takes to set up.
No obligation, and nothing to install to take a look.