Endless document layouts
Each supplier, customer and government form uses a different layout, which defeats fixed templates.
AI & Automation · Document Processing
AI document processing from inbox to ERP, with checks at every step
We build pipelines that read incoming documents, extract the fields you need, validate them against your vendors, orders and products, and post clean records to your ERP, with uncertain documents sent to a reviewer.
What is AI Document Processing?
AI document processing is the automated reading of business documents such as invoices, purchase orders, forms, receipts and contracts, using optical character recognition (OCR) and AI models to extract structured data. The extracted fields are validated against existing business records and either posted to a system such as an ERP or sent to a person for review. It replaces manual re-keying, not the judgment of the people who approve financial and contractual records.
Documents arrive as PDFs, scans, phone photos and email attachments in every layout imaginable. Template-based OCR tools break each time a supplier changes their invoice design, so staff end up re-keying anyway. Modern AI models handle layout variation far better, but they can still misread a figure or pick the wrong date, so extraction has to be paired with validation rules and a review step before data touches the books.
Why manual and template-based processing fall short
Poor scan and photo quality
Skewed scans, low-resolution photos, stamps and handwriting reduce what any OCR or model can reliably read.
Errors with financial impact
A misread amount, tax figure or bank detail posted straight to accounting causes reconciliation problems or worse.
Data that doesn't match records
Vendor names, product descriptions and units on documents rarely match your master data exactly.
Our AI Document Processing service
Document intake
Collecting documents from email inboxes, upload portals, scanners or shared folders, with deduplication and file-type handling.
OCR and layout analysis
Text and table recognition for scanned and digital documents, using OCR services or vision-capable models suited to your document types.
Field and line-item extraction
Extracting header fields and table rows such as vendor, document number, dates, totals, taxes and line items into a defined schema.
Validation and matching
Checking totals add up, matching vendors and products to master data, and comparing against purchase orders or receipts where available.
Review interface
A screen showing the document beside the extracted fields, with low-confidence values highlighted for a person to confirm or correct.
ERP posting
Creating draft vendor bills, orders or records in Odoo or another ERP, with the original document attached for audit.
Included capabilities
- Email and folder intake
- OCR for scans and photos
- Line-item table extraction
- Duplicate document detection
- Vendor and product matching
- Purchase order matching
- Arithmetic and tax checks
- Side-by-side review screen
- Draft records with source file attached
- Extraction logs and correction history
What AI Document Processing changes for your business
Less re-keying
Staff check and approve extracted data instead of typing it in from scratch.
Errors caught before posting
Validation rules flag mismatched totals, unknown vendors and duplicates before they reach the ledger.
Searchable document archive
Every record keeps a link to its source document and extracted text.
Handles new layouts
AI extraction copes with layout changes far better than fixed templates, reducing maintenance.
Where it makes the biggest difference
Vendor bill processing
Supplier invoices extracted, matched to purchase orders and goods receipts, and created as draft bills for accounts payable to approve.
Customer purchase orders
Incoming PDF orders read and converted into draft sales orders with products matched to your catalogue.
Delivery and logistics paperwork
Delivery notes, bills of lading and proof-of-delivery documents digitized and linked to shipments.
Forms and applications
Registration, admission or claim forms extracted into structured records, with handwritten fields flagged for review.
Seven steps from sample documents to live processing
Extraction is measured on your own documents before the build, and a parallel run confirms results before manual entry stops.
Collect samples
Gather a representative set of real documents, including poor-quality and unusual ones, and the records they should produce.
Define the schema
Agree exactly which fields to extract, their formats, and the validation rules each must pass.
Prototype extraction
Test OCR and extraction approaches on the samples and measure field-level results against the correct values.
Build validation
Implement matching against master data and business rules, and decide what triggers human review.
Integrate
Connect intake, review and ERP posting on staging, creating records as drafts rather than final entries.
Parallel run
Process live documents alongside manual entry and compare results before switching over.
Operate
Monitor review rates and corrections, add new document types, and refine rules as suppliers change formats.
What it connects to
AI Document Processing
- Odoo Accounting and Purchase
- Odoo Documents
- Other ERP systems via API
- Email inboxes
- Scanners and shared folders
- Cloud OCR and vision services
- Cloud object storage
Built with
Choosing an extraction approach
| Criterion | Manual entry | Template-based OCR | AI extraction with validation |
|---|---|---|---|
| Handles new layouts | Yes | No; each layout needs a template | Usually, without new templates |
| Effort per document | High | Low for known layouts | Low, plus review of flagged items |
| Main error type | Typing mistakes | Breaks on layout changes | Occasional misread values |
| Control | Full | Rules only | Validation rules and human review |
Security, quality and scale
Sensitive data controls
Bank details, identity numbers and personal data can be masked, restricted or processed on self-hosted models.
Draft-only posting
Records are created as drafts so financial entries always pass through a person with posting rights.
Document retention
Storage location, retention periods and access rights for original files are defined to suit your policies.
Provider review
OCR and model providers are checked for data retention and processing terms before any documents are sent.
What working with us looks like
ERP depth
We implement Odoo Accounting and Purchase, so extracted data lands in the right place with the right matching logic.
Tested on your documents
We measure results on your actual samples, including the difficult ones, before committing to an approach.
Validation-led design
We treat business rules and review as the core of the system, not an afterthought to extraction.
Local document realities
We design for the mix of printed, stamped, scanned and photographed documents common in Pakistani businesses.
What it costs
Fixed-price packages with the scope written down, paid stage by stage. Your project goes live once it's fully paid.
Related services, technologies and industries
Sources and further reading
Official documentation and guidance if you want to read more about this topic.
AI Document Processing: questions we hear most
How accurate is AI document processing?
Accuracy depends heavily on document quality, layout variety and which fields you need, so we measure it on your own samples rather than quote a figure. Validation rules and human review of low-confidence fields are what make the overall process reliable.
Can it handle handwritten or poor-quality scans?
Partly. Clear handwriting and reasonable scans can often be read, but faint, skewed or heavily stamped documents reduce reliability, and those fields are flagged for review. Improving capture, such as scanner settings or a mobile capture guide, often helps as much as the model.
Does it work with Odoo?
Yes. We post extracted data into Odoo as draft vendor bills, sales orders or other records through its API, with the source document attached. We can also integrate with other ERPs that offer an API.
Are our documents sent to an external AI provider?
They can be, under provider terms we review with you, or they can be processed with self-hosted OCR and open-weight models if documents must not leave your infrastructure. The trade-off is usually between convenience and running effort.
What does document processing cost to run?
Running cost depends mainly on document volume, page count and the OCR or model services used, plus hosting. We measure cost per document during the prototype so the figure is based on your real documents.
Next step
Send us twenty real documents
Share a sample of the invoices, orders or forms your team types in today. We'll test extraction on them and tell you honestly what can be automated and what needs review.