AI document processing that stops your team retyping invoices and forms
Staff retyping invoices, forms, and attachments by hand? APPSOLN uses AI to read documents, pull out the details, and send them for a quick check before they update your systems.
The problem
Invoices, applications, contracts, forms, and attachments arrive in all sorts of formats. People retype details, chase missing information, and hold up other work while documents sit in inboxes.
Your team stays in charge
Any detail that affects money, compliance, or customer commitments is checked by a person before it updates your systems.
How it is done today
- Documents arrive by email, upload, or shared drive.
- Someone opens each one to see what it is.
- Key details are typed into a spreadsheet, accounting system, or case system.
- Missing or unclear details mean more emails back and forth.
- Problem documents sit unnoticed until someone remembers them.
Where AI helps
- Recognise what type of document it is
- Pull out the key details into a structured record
- Flag missing or inconsistent information
- Send documents to the right person or queue
- Compare details against known records where available
Where AI should not decide
- Give legal interpretations of complex contracts
- Approve payments or commitments on its own
- Read documents that are illegible or incomplete
- Replace the people who decide how exceptions are handled
Tools you keep using
- Document storage
- Accounting or ERP systems
- Case management
- E-signature tools
Data safety
Documents and extracted details are kept only as long as needed. How confident the AI is stays separate from business approval, and only authorised people can release records into finance or customer systems.
Rules and safeguards
- Documents and extracted details are kept only as long as needed
- AI confidence is kept separate from business approval
- Only authorised people can release records into finance or customer systems
- Accuracy is spot-checked by document type on a schedule
What to expect
Expect a trial on one type of document with every result checked, then automatic updates to your system once accuracy is proven.
Want to fix this in your business?
Expect a trial on one type of document with every result checked, then automatic updates to your system once accuracy is proven.
How we set it up
- Pick the documentsStart with a common document type that always has the same details.
- Agree the detailsAgree which details to capture, how to check them, and where they go.
- Set up checkingSend uncertain or important results to a person with enough context.
- Update onceSave to your main system with a record of what happened, not a separate spreadsheet.
A typical timeline
- Weeks 1–2List document types and measure how long they take today.
- Weeks 3–4Trial AI on one document type, with every result checked.
- Weeks 5–8Connect checked results to your main system.
- Weeks 9–12Add similar document types once accuracy is steady.
Common questions
Can AI approve invoice payments?
No. AI suggests the details. A person approves anything that moves money, affects compliance, or commits you to a customer.
What if every document looks different?
We start with one type that always has the same details. Completely unique documents are a poor place to start.
How do you check accuracy?
Uncertain and important results go to a person, and accuracy is spot-checked for each document type.
Related services
This is usually delivered through ai opportunity review and ai automation.
What makes this a fit
Document handling is a good fit when the same details are pulled from the same kinds of files and checked before they update a record. It is a poor fit when every document is different, or when the details move money or compliance status with nobody checking. Your finance or operations system stays as the official record. AI suggests the values, and a person approves them.
Start with the documents that cause the most delay
Tell us which documents your team retypes most, or apply for an Opportunity Review to confirm it is the best place to start.