Read. Extract. Route. Repeat.

AI reads your documents, extracts structured data, and routes it into your systems. Any format, any source.

The Document Processing Pipeline

Stage 1: Ingestion

Documents enter the pipeline from whatever channels your business uses — email attachments, uploaded files, scanned documents, photos, web forms, or direct API feeds from partner systems. The automation monitors these channels and captures documents as they arrive. No manual downloading or forwarding required.

Stage 2: Classification

Before extracting data, the AI classifies the document. Is it an invoice, a contract, a receipt, an application form, or a compliance document? Classification determines which extraction template to apply and where the processed data should go. For businesses with diverse document types, classification alone saves significant time — instead of a person opening each document to figure out what it is, the AI sorts the incoming stream into categories.

Stage 3: Data Extraction

The AI reads the document and extracts structured data. For an invoice: supplier name, invoice number, date, line items, amounts, VAT, payment terms. For a contract: parties, key dates, obligations, termination clauses. This isn’t OCR from the 2000s — modern document AI understands layout, context, and relationships between fields, even when formatting is inconsistent across different suppliers.

Stage 4: Validation

Extracted data is checked against your business rules. Does the invoice amount match the purchase order? Is the contract party a known entity in your CRM? Are required fields present? Validation catches errors before they enter your systems — both AI extraction errors and errors in the source documents themselves. Documents that pass flow through automatically; those that fail get flagged for human review.

Stage 5: Routing and Storage

Validated data is pushed to the right destination system — Xero for invoices, the CRM for client documents, the DMS for contracts, the HR platform for applications. The original document is filed in your document storage with metadata for easy retrieval.

What We Process

Invoices and Purchase Orders

Supplier details, line items, amounts, VAT, payment terms → accounting platform

Contracts and Agreements

Parties, key clauses, dates, obligations, risk flags → legal/contract management

Receipts and Expenses

Merchant, amount, date, category, VAT → expense management

Application Forms

Applicant details, qualifications, responses → HR/CRM

Compliance Documents

ID verification, certifications, licences, regulatory filings → compliance tracking

Client Correspondence

Key information, action items, follow-up requirements → CRM/project management

Reports and Statements

Financial data, KPIs, trend data → reporting/analytics platforms

Custom Document Types

Any structured or semi-structured document with extractable data

If your business processes a document type not listed here, it almost certainly follows patterns that AI can learn. The AI Audit analyses your specific document flows and identifies which types are worth automating based on volume and complexity.

What AI Document Processing Can’t Handle

Handwritten documents with poor legibility

AI handles printed text and clear handwriting well. Illegible handwriting, faded documents, and heavily damaged scans still need human interpretation. The system flags these rather than guessing.

Documents requiring judgement

Extracting data from a contract is automation. Deciding whether the contract terms are acceptable is a legal judgement. The AI extracts and presents; the human decides and acts.

Unstructured narratives

A document with clear fields (invoice, form, table) extracts well. A free-form letter with no consistent structure is harder to extract reliably. The AI can summarise and classify it, but structured extraction requires some predictability in the document format.

100% accuracy on first pass

No extraction system is perfect. Accuracy typically sits at 90–98% depending on document quality and consistency. The validation step catches most errors, and the system improves as it processes more of your specific document types.

Typical Costs and ROI

ScopeTypical CostTypical ImpactPayback Period
Single document type (e.g. invoices only)£3,000 – £6,00070–80% reduction in manual data entry2–3 months
3–4 document types with routing£8,000 – £15,00060–70% reduction across document workflows3–5 months
Full document processing pipeline£15,000 – £25,000Near-elimination of manual document handling4–6 months

ROI scales with document volume. Processing 100 documents per month manually might take 15–20 hours. Processing 1,000 per month takes 150–200 hours — at that volume, automation pays for itself within weeks.

Use the AI Savings Calculator or the AI Audit for numbers based on your actual document volumes.

Frequently Asked Questions

Operations

Find Out How Many Hours Your Team Spends on Document Admin

The AI Audit maps your document flows, measures volumes, and gives you a clear automation plan with expected accuracy rates and time savings.

Book a Document Processing Audit
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