# 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.

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.

## How the work 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 can help

- 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 be trusted

- 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

## Systems

- Email
- Document storage
- Accounting or ERP systems
- Case management
- E-signature tools

## Human review

Any detail that affects money, compliance, or customer commitments is checked by a person before it updates your systems.

## Security and access

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.

## Integration approach

- **Pick the documents.** Start with a common document type that always has the same details.
- **Agree the details.** Agree which details to capture, how to check them, and where they go.
- **Set up checking.** Send uncertain or important results to a person with enough context.
- **Update once.** Save to your main system with a record of what happened, not a separate spreadsheet.

## Governance

- 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

## Measures

- Time from receiving a document to having a usable record
- Accuracy on spot-checked documents
- How many documents need a person, and why
- Rework caused by wrong details

## Typical sequence

- **Weeks 1–2.** List document types and measure how long they take today.
- **Weeks 3–4.** Trial AI on one document type, with every result checked.
- **Weeks 5–8.** Connect checked results to your main system.
- **Weeks 9–12.** Add similar document types once accuracy is steady.

## What you leave with

Expect a trial on one type of document with every result checked, then automatic updates to your system once accuracy is proven.

## 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.

Canonical page: https://appsoln.com/solutions/document-processing