AI & Automation - Document Intelligence
The paperwork already contains the data. Stop paying people to retype it.
Document intelligence is the AI use case with the clearest return for most Australian operations, because the input is unstructured, the volume is high and errors are cheap to catch. We build capture, extraction, validation and review as one pipeline into your CRM or ERP - with a human queue for anything the system is not sure about.
At a glance
- Who this is for
- Finance, procurement, despatch and compliance teams handling high document volumes.
- Typical first case
- Supplier invoices, because the baseline and the matching rules already exist.
- Non-negotiable
- Confidence thresholds, review queues and traceability from posted value back to source.
Document types
What we process.
Different document types need different validation. Scoping starts by naming the type and the system it must land in.
Supplier invoices and statements
Header and line detail extracted, matched to purchase orders and receipts, coded by rule, with mismatches queued for a person rather than emailed around.
Purchase orders and customer orders
Orders arriving as PDF or email attachments converted into sales orders, with product matching against your catalogue and unmatched lines flagged.
Delivery dockets and proof of delivery
Signed and scanned paperwork captured against the job or shipment, so despatch, invoicing and disputes all reference the same evidence.
Certificates and compliance records
Test certificates, licences, insurances and inductions read for issuer, scope and expiry, then tracked so lapses surface before they cause a stoppage.
Contracts and variations
Key terms, dates, values and obligations extracted into a register, with the source clause linked for verification.
Timesheets and site paperwork
Handwritten and photographed field records converted into structured entries against the correct job and cost code.
Pipeline
Capture to posted record.
Six stages. Validation against your own data is what turns extraction from a novelty into something finance will accept.
01
Capture
Documents collected from monitored inboxes, scanning, portals or upload - one intake path so nothing arrives by a route nobody watches.
02
Classify
Document type identified first. Extraction rules and validation differ by type, and misclassification is the most common source of bad data.
03
Extract
Fields and line items read, including from varied layouts, so a new supplier template does not require a rebuild.
04
Validate against your data
Extracted values checked against real records - supplier, purchase order, product, job - with totals and arithmetic verified.
05
Score and route
Confident, validated documents post automatically. Anything below threshold or failing validation goes to a review queue with the original alongside.
06
Post and trace
Written into your CRM or ERP with a permanent link back to the source document, the extracted values and the person who approved it.
Division of labour
Automated where it is safe, reviewed where it is not.
What this removes
Manual handling
- Reading and retyping documents into a system
- Chasing which invoice matched which order
- Filing and later hunting for source paperwork
- Spreadsheet registers for certificates and expiries
- Data entry backlogs at month-end
What stays human
Review and approval
- Anything below the confidence threshold
- Every mismatch against orders, receipts or catalogue
- First occurrences of a new document layout
- Payment approval and posting sign-off
- Periodic sampling of auto-posted documents
Assurance
How accuracy is handled honestly.
01Thresholds are set with you, not by us alone
The accuracy required to auto-post an invoice is a commercial decision. We measure on your documents and let you set the line.
02Every posted value is traceable to a source
Original document, extracted fields, validation result and approver, retained together. Extraction without traceability is not acceptable in finance.
03Accuracy is measured before go-live and after
Benchmarked against a sample of your real documents, then sampled again in production. We do not quote accuracy figures we have not measured on your data.
Continue exploring
Send us a sample of your worst paperwork.
A short assessment on your real documents shows what could post automatically and what would always need a human eye.