# AI document and invoice processing > We build document workflows that read invoices, purchase orders, tenders and forms, pull out the details you need into a structured list, and show each value next to its source so a person can check it before it goes into your systems. Source: https://www.fyadvisers.com/services/ai-document-processing/ Author: FYAdvisers Last updated: 2026-10-13 Intelligent document processing means using OCR and AI to read business documents and turn them into structured data: who sent it, what it refers to, the dates, the line items and the amounts. FYAdvisers builds these workflows for Singapore businesses that still retype details from invoices, purchase orders, tenders and forms. The AI extracts the fields, shows each value beside the part of the document it came from, and a person checks it before anything is posted to your accounting system, CRM or job records. ## A worked example: tender files into a compliance matrix For [Chromatic Media](/work/chromatic-media/), a printing and design business, we built a tender preparation workflow. The team uploads the tender files. AI reads them, extracts the requirements into a compliance matrix and prepares proposal drafts. Chromatic's team then reviews the requirements, the proposed responses, the design and the prices before deciding what to submit. The same pattern works for most document-heavy tasks: extract into rows that can each be checked against the source, then let people decide. ## What we build - **Invoice and bill capture.** Supplier, invoice number, dates, GST, line items and totals extracted from PDFs and scans, matched to the supplier record and queued for approval. - **Purchase order and delivery order matching.** Extracted lines compared with the PO and goods received, with mismatches flagged for a person. - **Tender and contract reading.** Requirements, deadlines, submission rules and evaluation criteria pulled into a checklist or compliance matrix. - **Forms and applications.** Details from application forms, claims and onboarding documents entered into your system after review. - **Document sorting.** Incoming email attachments classified by type and routed to the right queue. Extraction usually sits inside a larger [workflow automation](/services/workflow-automation/), with a [system integration](/services/system-integration/) to post the checked data into Xero, QuickBooks, an ERP or your own database. ## InvoiceNow and where AI fits IRAS's [GST InvoiceNow Requirement](https://www.iras.gov.sg/taxes/goods-services-tax-(gst)/gst-invoicenow-requirement) page describes InvoiceNow as Singapore's nationwide e-invoicing network, based on the Peppol standard and introduced by IMDA in 2019, which lets businesses send and receive invoices digitally. IRAS says all GST-registered businesses must submit invoice data to IRAS using InvoiceNow-Ready Solutions, rolled out in phases. The page lists phases for newly registered businesses from 1 November 2025 and 1 April 2026, and for existing GST-registered businesses from 1 April 2028 to 1 April 2031 according to their annual supplies. IRAS notifies businesses of their own dates. This affects what is worth automating with AI: - **Invoices received through InvoiceNow** arrive as structured data. They need mapping into your system, not AI extraction. - **Invoices from suppliers not on the network**, overseas suppliers, scanned receipts and delivery orders still arrive as documents. That is where AI extraction helps. - **Your InvoiceNow setup** comes from an InvoiceNow-Ready accounting solution or an IMDA-accredited Access Point Provider, as IRAS's page explains. We do not replace that, but we can connect document processing to the same accounting system. ## How a project runs 1. **Discovery.** We collect a sample of the documents you handle, note every layout and language, and agree which fields matter and what happens to them next. 2. **Prototype with your real data.** We run extraction on past documents and compare the output with what your team actually entered. You see which fields are reliable and which are not. 3. **Build.** We set up intake (email, upload or shared folder), extraction, validation rules such as totals adding up and GST numbers in the right format, a review screen and the connection to your system. 4. **Human review.** A person checks flagged fields and approves each document. Anything affecting payment or a submission is confirmed by your team. 5. **Monitoring.** We log corrections, review new layouts as suppliers change them, and adjust instructions or rules. ## What it costs We outline our own fees after a conversation. Running costs depend on volume and the services used. Cloud providers publish per-page prices; for example, when we checked in October 2026: - **Google Cloud Document AI** listed Enterprise Document OCR at US$1.50 per 1,000 pages after the first 1,000, and Form Parser and Custom Extractor at US$30 per 1,000 pages up to one million pages a month. - **Amazon Textract** listed Analyze Expense at US$0.01 per page and Detect Document Text at US$0.0015 per page in its US West (Oregon) example. Other cost drivers: - **Layout variety.** Ten supplier formats need less testing than three hundred. - **Scan quality and handwriting.** Poor inputs need more review and sometimes a stronger model. - **Validation and integration.** Matching against POs and posting into an ERP takes more work than exporting a spreadsheet. - **Review time.** Someone still checks flagged fields. ## Data and governance Documents often contain personal data: names, NRIC numbers on forms, addresses and bank details. We agree what is sent to each provider, where it is processed, how long it is kept and who can see it. PDPC's [Advisory Guidelines on use of Personal Data in AI Recommendation and Decision Systems](https://www.pdpc.gov.sg/-/media/files/pdpc/pdf-files/advisory-guidelines/advisory-guidelines-on-the-use-of-personal-data-in-ai-recommendation-and-decision-systems.pdf), issued on 1 March 2024, explain how the PDPA applies when AI systems use personal data. IMDA and the AI Verify Foundation's [Model AI Governance Framework for Generative AI](https://aiverifyfoundation.sg/resources/mgf-gen-ai/), released on 30 May 2024, sets out dimensions such as accountability, data, security, and testing and assurance. We use both as checklists, and keep an audit trail of what was extracted, what was corrected and who approved it. ## Build or buy **Buy** if your documents are mainly supplier bills going into Xero or QuickBooks. Tools such as Dext and Hubdoc are built for that. Larger teams often look at ABBYY or Rossum, and developers can use Microsoft Azure AI Document Intelligence, Google Document AI or Amazon Textract directly. **Build with us** if the documents are specific to your business (tenders, technical forms, job sheets), if extraction needs to feed several systems, or if a person needs a review step designed around how your team works. **Do neither** if you handle a few documents a week. Retyping may be cheaper than any setup. ## Who this suits - Finance and operations teams retyping invoices, POs or delivery orders every day. - Businesses bidding for tenders that read long documents to build checklists. - Firms processing application forms or claims with varied layouts. ## What to prepare - Twenty to fifty real documents covering your common layouts, with sensitive details removed where possible. - The fields you need and where each one goes. - What your team currently checks by hand. - The systems the data must reach. - Any rules about where documents may be processed or stored. [Get in touch](/#contact) and we will tell you which documents are worth automating first. ## Frequently asked questions ### What is intelligent document processing? Intelligent document processing (IDP) uses OCR and AI models to read documents, classify them and extract specific details, such as supplier names, dates, line items and amounts, into structured data. Unlike plain OCR, it understands which value is which, even when layouts vary. ### Can AI process invoices accurately? It can extract most fields from clear invoices, but accuracy depends on scan quality, layout variety and language. We test on your real documents before launch and keep a person checking low-confidence fields and anything that affects payment. ### Do we still need AI invoice processing if we use InvoiceNow? Invoices received through InvoiceNow arrive as structured data, so they do not need AI extraction. AI processing is for the documents that still arrive as PDFs, scans or photos, such as invoices from suppliers not on the network, delivery orders, claims and tender files. ### Which document types can you handle? Invoices, purchase orders, delivery orders, quotations, claims, application forms, contracts and tender documents are common. Handwritten and poor-quality scans are possible but need more testing and more human review. ### Where is our document data processed? We agree this with you before building. Many cloud document services offer a choice of processing region, and we confirm each provider's data use terms with you. Documents containing personal data are handled under your PDPA obligations.