AI document processing · UAE
AI document processing that leaves your team in control of every exception
For finance and operations teams who retype invoices, delivery notes or forms into a business system. We build a workflow that reads each document, checks it against your records, sends anything doubtful to a person, and updates your system only after approval.
- Arabic and English documents
- A person reviews exceptions
- Every value linked to its source
- Free 30-minute discovery call
The problem
Who this is for.
A finance lead, operations manager or IT owner with one repeated document task that has real volume and a system it should end up in.
Supplier invoices
Keyed into the accounting or ERP system by hand, with mismatches found at month-end.
Delivery notes and receipts
Checked against purchase orders on paper or in spreadsheets before payment.
Application and request forms
Mixed-language forms whose details are copied from a PDF, scan or phone photo into another system.
What changes. Your team stops retyping and starts reviewing. Clear documents move through with every value linked to where it was found; unclear ones arrive in a review queue with the reason flagged. Nothing reaches your business system until it has passed your checks or a person has approved it.
Illustrative workflow
One supplier invoice, step by step.
This walkthrough uses a synthetic invoice, not a client document. It shows how the workflow is designed, including the case where something is missing. It is not a recording of a live connection to your system.
Supplier invoice
Information, structured.
- Supplier identified
- Purchase order referenced
- Delivery reference missing
Every field can be checked against its source.
Review requiredConceptual interface — sample data, not a customer screenshot.
Intake
The invoice arrives in the agreed channel, such as a mailbox, upload folder or scan, as a PDF, scan or phone photo.
Extraction
Supplier, invoice number, dates, line items, VAT and totals are read into fields. Each field keeps a link to where it appears on the page.
Checks
Totals are recalculated and the invoice is compared with the purchase order and supplier record. Mismatches are flagged with the reason.
Exception
In the example the delivery reference is missing. The invoice is not guessed through; it goes to the review queue.
Human review
A reviewer sees the document beside the extracted fields, fixes or confirms the missing value, and approves or rejects.
Approved update
Only the approved record is sent to the connected system, and the reviewer's changes are logged.
Suitability
Where it fits, and where it doesn’t.
A good fit
Repeated volume
The same document type arrives often enough that retyping costs real time.
Accessible inputs
Documents arrive somewhere we can connect to, and samples can be shared safely (synthetic or redacted first).
A system to update
There is a business system with an API, import or agreed integration route.
An accountable owner
Someone owns the result and can decide what counts as an exception.
Probably not a fit yet
Very low volume
A few documents a month rarely justify a custom build.
Your software already does it
Many accounting and ERP products include capture features. If yours covers the need, we will say so.
No route into the system
If nothing can receive the approved record, start with the integration question, not the AI.
Fully hands-off expectations
We design for review. A workflow that must never involve a person is usually the wrong first project.
Integration
Integration boundaries.
What we connect
The input channel, your reference data (purchase orders, suppliers) and one target system for the approved record, through its API or an agreed import.
What we agree first
Which system is the record of truth, who may approve what, and what happens when the target system rejects an update.
When an update fails
The record stays in the queue with the error, nothing is posted twice, and the reviewer can retry or escalate.
What we don’t assume
That every document can be shared with every user or every provider. Access, hosting and model provider are agreed per project.
Control
Review and data handling.
Review queue
Low-confidence fields, failed checks and missing values go to a person, with the reason shown.
Source references
Every extracted value links back to its place in the document.
Logging
Inputs, outputs and reviewer changes are logged, with sensitive fields redacted where agreed.
No confidential uploads to start
We begin with synthetic or redacted samples. Please don’t attach real documents to the enquiry form.
Pilot
What a pilot delivers.
A pilot is bounded: one process owner, one main input source, one output integration, an exception queue, an agreed sample set and acceptance criteria. The scope and price are confirmed in a written proposal.
Working workflow
Extraction, checks, review queue and the approved update for one document type.
Evaluation results
Field-level and whole-document results on a held-out sample, with review rate and failures reported separately.
Operating guide
How to handle exceptions, update reference data and add new layouts.
Running-cost model
What the workflow costs to operate each month, so you can judge it with real numbers.
What drives cost and timeline: Number of document types and layouts, languages and scan quality, how many checks and reference sources are involved, the target system's integration route, the expected exception rate, hosting requirements and ongoing monitoring. We don’t publish a price list; we confirm scope, timeline and price in a written proposal after the discovery call.
Evidence
What you can examine today.
We are honest about the evidence. The examples below are labelled illustrations using synthetic data. Measured pilot results will be published here only after evaluation, with their sample size and limits.
The illustrative document workflow
How extraction, review and approval fit together.How to test AI document extraction
The evaluation method we use, and what to ask any vendor.What drives the cost of an AI project
Assessment, pilot and operating costs, without a rate card.
Value worksheet: one document workflow
A scenario based on your own assumptions, per month, in AED. Released capacity is time your team gets back; it only becomes a cash saving where spending actually falls or the time is used productively.
Enter all five values to see the estimate. Blank fields are not treated as zero.
Formula. Hours released = (manual minutes − average assisted human minutes) × documents per month ÷ 60. Capacity value = hours released × loaded hourly cost. After operating costs = capacity value − monthly running cost.
- Use the average assisted time across all documents. A few long exceptions can double the real average while the typical case looks quick.
- Machine processing time only counts as human time if a person has to stay occupied while it runs.
- Setup and implementation costs are not included. Add them separately when comparing options.
- This is not a Digital Cubic estimate or benchmark. Measure both times on a comparable sample before relying on the result.
Preparing for the first call? Use the project scoping checklist, which includes the questions we ask about AI and automation inputs.
Before you start
Questions about AI document processing.
Does it work with Arabic documents?
Yes, Arabic, English and mixed documents. Scan quality and layout matter more than the language, so we test on a representative sample before agreeing acceptance criteria.
How accurate is it?
It depends on your documents, so we don’t quote a single number. We measure field-level and whole-document correctness, the review rate and failures on a held-out sample during the pilot and report each separately.
Which systems can it update?
Any system with an API or an agreed import route. We confirm the integration scope after reviewing what your system supports.
Do we have to send you real invoices?
Not to start. We begin with synthetic or redacted samples and agree how a representative sample is shared after the first call.
What if our existing software can already do this?
Then we’ll tell you. Many accounting and ERP products include document capture, and using it may be the better first step.
Let’s make it work
Tell us which document your team retypes most.
Name the document type, roughly how many arrive each month and the system they end up in. Free 30-minute discovery call; please don’t attach real documents.