Invoice processing automation
Capture, match, approve and post supplier invoices.
Document Processing Automation
Invoices, forms, contracts, applications, statements: if your team opens a document, reads it and types what's in it somewhere else, AI can do most of that for you. It reads, extracts, checks and enters the data, and flags anything unclear for a person to review.
Works with documents from email, uploads, scans and shared folders.
A common starting point within business process automation. Documents are usually one step in a bigger process, and we can automate the whole thing.
Extracted and checked
It's slow, it's error-prone, and it gets worse every time your volume grows.
If it's a document your team handles regularly, it's worth asking. We'll tell you how well AI can read it before you commit.
Documents arrive wherever they do today: an inbox, an upload form, a shared drive or a scanner.
AI works out what each document is: an invoice, a contract, an application form.
It pulls out the fields you need, even when every sender uses a different layout.
Rules check the data: totals add up, dates make sense, the customer or supplier exists, it isn't a duplicate.
Anything the AI isn't confident about goes to a person, with the document and the extracted data side by side.
Clean data goes into your system, the document is filed, and the next step (like an approval) is triggered.
Our process: Audit → Identify → Build → Integrate → Improve. How we work
Older document tools relied on OCR plus a fixed template for each layout. That works until a supplier changes their invoice or a customer fills a form in a different way.
| Template-based OCR | AI document processing | |
|---|---|---|
| New layouts | Needs a new template | Handles most layouts without setup |
| Unstructured text (emails, letters, contracts) | Struggles | Reads and understands it |
| Understanding context | None. It reads characters. | Knows a "due date" from an "invoice date" |
| Tables and line items | Often breaks | Extracts line by line |
| Setup per document type | Heavy | Light, then improves with review feedback |
This is what's often called intelligent document processing: OCR where it's needed, plus AI that understands what it's reading.
When the AI isn't confident, or the stakes are high, the item goes to a person to check before anything is posted.
We add validation checks (totals, formats, duplicates, matching against your records) on top of the AI.
Every automated action is logged: what came in, what was extracted, what changed, and who approved it.
We sign an NDA before we see your data, access is limited to what the automation needs, and we never use your data to train AI models.
We connect automation directly to your existing software, so your team keeps working the way they do now.
No API? No problem. If your software can be reached, we can usually connect to it, and if it can't, we'll tell you before you spend anything.
Works with
Illustrative example
A logistics company receives delivery documents from dozens of carriers, each in a different format. Two admins open each email, read the PDF and type the shipment reference, dates, weights and charges into their operations system. It takes most of their day, and mismatches surface weeks later during invoicing.
Documents arriving in the shared inbox are read automatically. The data is extracted, checked against the matching shipment, and written into the operations system. Anything that doesn't match (a weight difference, a missing reference) lands in a short review queue. The admins now handle only the exceptions.
Document processing automation uses software to capture documents, extract the information in them and send it to the right system, without someone reading and retyping each one. With AI, it can handle documents with different layouts and even unstructured text such as emails and contracts.
It depends on document quality and type. Clean digital PDFs are extracted very reliably; poor scans and handwriting are harder. That's why we combine AI with validation rules and route low-confidence items to a person. We'll test on your real documents during scoping and show you the results before you commit to a full build.
No. It's a solution built and connected for you. We may use proven document AI services as part of it, but you don't have to choose, configure or maintain a tool. You get the finished workflow, running in your systems.
They go to a review queue with the document and the extracted fields side by side. Your team corrects or completes them in seconds, and the automation carries on from there.
Scanned documents, yes, if they're reasonably legible. Handwriting depends heavily on quality. We'll test samples and tell you honestly what to expect.
Yes. We sign an NDA before we see any documents, access is limited to what the automation needs, every action is logged, and we never use your data to train AI models.
Tell us what comes in and where it needs to go. We'll tell you how much of it AI can handle.
Find What You Can AutomateFree assessment. No commitment. If something isn't worth automating, we'll say so.