Back office

Intelligent Document Processing

Invoices, forms and contracts read, validated against your rules and posted automatically.

What this is

Extraction alone just moves the error downstream, so validation is the core of this. Fields are extracted, checked against your business rules and reference data, clean cases post straight through and genuine exceptions reach a person with the document and the failed rule side by side.

The problem

What this solves

If more than one of these is familiar, there is usually a case worth scoping.

Staff retype data from PDFs and scans into finance systems daily.
Documents arrive in dozens of layouts and template tools keep breaking.
Keying errors surface weeks later in reconciliation.
Backlogs delay payment, approval or fulfilment.

How it works

The shape of the build

Indicative. The final design follows your systems, data and constraints.

Validation before posting, so extraction confidence alone never creates a financial entry.

Ingest
Email, upload, scanner or file drop, with deduplication.
Classify
Document type identified first so the right rules apply.
Extract
Fields located by meaning rather than coordinates, so new layouts do not break it.
Validate
Totals, tax, dates, suppliers and purchase orders checked against your reference data.
Post or escalate
Clean cases posted automatically; exceptions queued with the failed rule shown.

Scope

What is included

Deliverables you receive, in your own infrastructure and repositories.

Multi-format ingestion pipeline
Classification and layout-independent field extraction
Business rule validation before anything posts
Straight-through posting into finance, ERP or operations systems
Exception queue with document, extraction and failed rule together
Per-field accuracy reporting and a full audit trail

Outcomes

What changes once it is live

Operational changes you should expect. We measure the specific numbers for your business rather than quoting generic figures.

Routine documents processed without manual keying
Errors caught at validation rather than at reconciliation
Only genuine exceptions reaching a person
An audit trail linking source document to system entry

Delivery

How we run the engagement

Our approach

Discovery

Process walkthroughs, data review, constraints and a written scope you sign off before build.

Architecture

Data model, integration boundaries, hosting and the security model, agreed up front.

Proof of concept

A narrow build on your real data against an agreed quality bar, so the go-ahead is evidence-based.

Development

Two-week increments, each ending in a working deployment and a review.

Testing

Automated coverage on critical paths, evaluation sets for AI behaviour, acceptance testing with your users.

Deployment

Staged rollout into your infrastructure with monitoring and a tested rollback path.

Monitoring & support

Quality, cost and latency tracking after launch, with handover documentation or an ongoing retainer.

Questions