AI Document Processing
Paperwork read and entered without anyone typing it.
What is AI document processing?
AI document processing reads the documents arriving at your business, extracts the specific fields you need from each type, sends them into your existing systems, and holds anything it cannot read confidently for a person to check.
Typing details from documents is slow work that nobody wants, and the errors it produces are difficult to trace because the original sits in a folder somewhere while the wrong figure travels onward.
We set up reading for the document types you handle most: invoices, delivery notes, application forms, identity documents, receipts, including photographs taken on a phone in poor light.
The critical design decision is what happens when the system is unsure. Anything below the confidence threshold is held for a person rather than guessed, because a wrong figure entering your systems silently is considerably worse than a queue.
Why we tune on your own documents
Duara builds document reading from Nairobi for businesses where paper and phone photographs still arrive daily and somebody types their contents into a system.
We tune extraction against your own documents rather than shipping a generic reader. A system trained on your actual supplier invoices performs far better than one trained on invoices in general, and the difference shows up immediately in how much lands in the review queue.
Who this is for
- Staff retype details from documents
- You handle paper forms or scans daily
- Typing mistakes cause problems downstream
- Documents arrive as phone photographs
Industries we serve
- Logistics and freight
- Insurance claims
- Banking and microfinance
- Healthcare administration
- Agribusiness collection
- Distribution and wholesale
Problems this solves
These are the conditions where document reading returns real hours rather than shifting work sideways.
- Details typed by hand. Somebody reads each document and keys its contents into a system, which is slow and produces errors nobody notices immediately.
- Documents arriving as photographs. Suppliers and field staff send phone photos rather than clean scans, and most software handles those badly.
- Errors travelling downstream. A mistyped figure moves through several systems before anybody notices, by which point tracing it is expensive.
- Paper accumulating unprocessed. A backlog forms because processing depends on somebody having free time, which nobody reliably does.
What we deliver
Reading tuned to your specific document types, extraction into your existing systems, uncertain items held for review, and accuracy reported by document type rather than as a single figure.
Reading set up for your specific document types
Extracted details sent into your existing systems
Unclear items held for human checking
Accuracy reporting broken down by document type
Handling of phone photographs and poor scans
A record linking every extraction to its source document
Features
- Tuned to your documents. Extraction is trained on your actual supplier and customer paperwork rather than on generic templates.
- Photographs handled properly. Phone images in poor light are a first class case rather than an edge case, because that is how documents actually arrive.
- Uncertain items held, not guessed. Below the confidence threshold the document waits for a person, since a wrong figure entering silently is worse than a queue.
- Accuracy reported per type. A single overall figure hides that invoices read at ninety eight percent and handwritten forms at sixty.
- Source linking. Every extracted value links back to the document and the position it came from, so verification takes seconds.
Benefits
- Hours returned immediately. Typing is the largest single time cost in most document-heavy processes, and it disappears rather than shifting elsewhere.
- Errors caught at the boundary. Uncertainty is surfaced when the document is read rather than discovered three systems later.
- Backlogs stop forming. Processing no longer depends on somebody having spare time, so paper does not accumulate.
- Traceability improves. Every figure links to its source document, which makes audits and disputes far quicker.
Technologies we use
- Document type classification. Identifying what each incoming document is before deciding which fields to extract from it.
- Field extraction. Pulling specific values from each type, tuned against your own historical documents.
- Image preprocessing. Correcting skew, lighting and focus problems typical of phone photographs before reading.
- Confidence scoring. Per field certainty, so one uncertain value routes a document to review without discarding the rest.
- System integration. Extracted data written into your accounting, ERP or operational systems rather than into a separate store.
Confidence calibration matters more than raw accuracy. A system that knows when it is unsure is more useful than one that is slightly more accurate but always certain.
How the process works, step by step
Document processing usually takes four to six weeks, with most of that spent tuning against your real documents.
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Step 1
Free document review
We look at a sample of your actual paperwork to establish which types are worth automating and which are not.
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Step 2
Type and field definition
We agree which document types are in scope and exactly which fields matter on each.
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Step 3
Tuning on your documents
Extraction is trained and measured against your own historical paperwork rather than generic samples.
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Step 4
Parallel processing
The system reads alongside your team so accuracy per type is measured rather than assumed.
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Step 5
Threshold setting and live
Confidence thresholds are set from the parallel results, then processing goes live with a review queue.
Quality assurance and how we work
The commitments attached to reading documents that feed your systems.
- Unclear documents are never guessed. Below threshold, a document waits for a person. A wrong figure entering silently costs more than any queue.
- Accuracy is reported per document type. We do not quote a single blended figure, because it hides that some types read far worse than others.
- Handwriting is tested, not promised. We measure handwriting performance on your actual forms before committing to it, and will say if it is not viable.
- Extraction is tuned on your paperwork. Generic readers underperform. We train against your own documents and show the difference.
- Every value links to its source. Any extracted figure can be traced to the document and position it came from, without searching.
Frequently asked questions about AI document processing
Does it handle handwriting?
Printed text is very reliable. Handwriting varies enormously, so we test on your actual forms and will tell you plainly if it is not viable.
What about poor quality scans and photos?
Phone photographs are treated as a first class case rather than an edge case, since that is how documents genuinely arrive.
What happens when it cannot read something?
The document is held for a person rather than guessed. A wrong figure entering your systems silently is worse than a queue.
How accurate is it?
It depends heavily on document type, which is why we report accuracy per type rather than quoting one blended figure that hides the weak cases.
Why tune on our documents?
A reader trained on your actual supplier invoices outperforms a generic one noticeably, and the difference shows immediately in queue volume.
Which systems can it write into?
Accounting, ERP and operational systems through their APIs, so data lands where you already work rather than in a separate store.
How long before it is processing our documents?
Four to six weeks, with most of that spent tuning and measuring against your real paperwork.
Do we need to change how suppliers send documents?
No. The point is handling what already arrives, including photographs and imperfect scans.
Can it process identity documents?
Yes, and those are usually among the most reliable because their layouts are standardised.
What is straight through processing?
A document read, extracted and posted with no human involvement. The proportion achieving it varies by type and we report it honestly.
Can we see why a value was extracted?
Yes. Every value links to the document and the position it came from, so checking takes seconds rather than a search.
What if a supplier changes their layout?
Confidence drops and documents route to review, which alerts you rather than silently producing wrong figures.
Does it work with documents in Swahili?
Yes, including mixed language forms, which are common in field collection and application paperwork.
Can it detect duplicate documents?
Yes, and duplicate invoices in particular are a common and rarely noticed cost.
Is our document data secure?
Documents stay within your systems, are processed under your access rules, and are never used to train public AI models.
How many document types can it handle?
As many as are worth defining. Each type needs its own field definition, so we start with the highest volume ones.
What if a document type is too varied?
Some are, and we will say so during the review rather than building something that sends most items to review anyway.
Does it replace our data entry staff?
It removes the typing. Most clients move those people onto checking and exception handling, which needs judgement.
Can it process a historical backlog?
Yes, and backfilling old documents is often worthwhile because it makes historical records searchable.
What does document processing cost per page?
Document volume and page count determine it. We project the monthly figure from your own throughput before anything is agreed.
Glossary of terms
Document processing vocabulary, plainly defined.
- Extraction
- Pulling specific values out of a document so they can be used without retyping.
- Confidence score
- How certain the system is about a particular extracted value, used to decide whether a person checks it.
- Review queue
- The list of documents held back because something could not be read confidently.
- Preprocessing
- Correcting image problems such as skew and poor lighting before attempting to read.
- Field
- A specific value being extracted, such as invoice number, date or total.
- Straight through processing
- A document read, extracted and posted with no human involvement at all.
Related services in AI Implementation
Talk to us about AI document processing
Send a sample of twenty real documents, including the messy ones. Accuracy on those decides feasibility far better than a demonstration on clean examples.
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