Live Demo · AI Data Extraction
This demo shows AI extracting key fields from unstructured invoice text: supplier, line items, totals, VAT, due date. The same pattern works for CVs, reports, contracts, or any document with consistent structure.
Paste any invoice text below, or load the sample invoice.
Quick start
Extracted data
Your text is sent to OpenAI for extraction. It is not stored or logged. Use fictional or anonymised invoices for this demo.
A practical local-business workflow
Extraction is only the first step. The useful part is moving accurate information into the software your team already uses, while keeping approval with a person.
An invoice, purchase order or customer enquiry arrives by email, web form or upload.
AI identifies names, addresses, references, dates, line items, VAT, totals and other agreed details.
Your team sees a draft, corrects anything uncertain and remains responsible for the final record.
Approved data can create a draft job, update a spreadsheet or pass into accounting, CRM or operations software.
Document extraction built into your workflow.
Invoices, CVs, contracts, purchase orders, expense receipts, survey responses. If a human can read it, the AI can extract from it.
The result is clean JSON, ready to write to a database, trigger a workflow, or display in your app. No manual re-keying.
Not a standalone tool. Built into your upload flow, email parser, or admin portal, wherever documents arrive in your business today.
What the demonstration proves
The live example shows the core extraction step: ordinary invoice text becomes named fields and line items. A real implementation can use the same pattern for supplier invoices, purchase orders, work requests, delivery notes or customer enquiries.
For a builder, trades business or local service company, that might mean preparing a draft job record with the customer, site address, requested work and reference number already filled in.
What a production build still needs
This page is a capability demonstration, not an accounting system. Production automation should be designed around the source documents, the destination software and the decisions that must stay with your team.
Questions before you automate
It can identify fields such as supplier, invoice number, invoice and due dates, customer, currency, line items, subtotal, VAT and total. The exact fields are agreed for each business workflow.
Yes. Extracted invoice or enquiry details can be mapped into a draft job record in an existing system, ready for a member of staff to check before it is saved, assigned or sent anywhere.
This public demo accepts pasted text only. A production build can add document upload, OCR for scanned pages or photographs, email attachment handling and connections to existing software.
Yes. Important financial or operational data should go through validation and human review. A sensible workflow can flag missing or uncertain fields instead of silently treating every result as correct.
The pasted text is sent to OpenAI for extraction and is not stored or logged by NRB Consulting. Use fictional or anonymised invoices in this public demonstration.
Potentially. The structured result can be mapped to a database, spreadsheet, accounting package, CRM or job-management system where a suitable API, import route or integration point is available. See the AI automation service or custom software service for how a scoped build works.
Tell me what you receive and what you currently do with it manually. I'll tell you what's possible and what it costs.