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  • AI-based Document Extraction

Turn PDF and image invoices into automation-ready invoice data

SupplyOn helps manufacturers convert unstructured supplier invoices into machine-readable invoice files using AI-based document extraction. Instead of leaving PDF and image invoices outside the digital AP process, teams can extract invoice data, validate it, route uncertain cases to human verification, and bring more suppliers into one controlled invoicing model.

What is AI-based document extraction?

AI-based document extraction converts unstructured invoices such as PDFs and images into machine-readable data. It enables finance teams to integrate non-structured invoice inputs into a digital AP process.

Many accounts payable teams already use structured eInvoicing where possible. However, a large share of supplier invoices still arrives as PDFs, scans, or images — creating a gap between digital processes and manual invoice handling.

The Challenge

Invoice automation stalls when too many suppliers still send PDFs, scans, or photos

Most AP teams already know the problem: structured eInvoicing works well where suppliers are digitally mature, but a large share of invoices still arrives as PDF attachments, scanned files, or images. Those invoices are harder to validate, harder to post automatically, and more expensive to process manually. If finance wants one central inbound model, it needs a way to convert low-maturity invoice inputs into clean digital data without building a separate process for every supplier. SupplyOn helps manufacturers use AI-based document extraction as a bridge between unstructured invoice receipt and automation-ready AP processing.

Bring PDF and image invoices into the digital AP flow

Convert unstructured supplier invoices into machine-readable invoice data instead of leaving them in manual side processes.

Increase automation without waiting for every supplier to adopt eInvoicing

Use AI-based extraction to onboard long-tail suppliers into a more digital invoice process even when structured formats are not yet available.

Improve invoice quality before AP has to fix it

Extract, validate, and structure invoice data earlier so AP teams spend less time on rekeying and correction.

Keep exceptions under control when confidence is not high enough

Route uncertain extraction results into human verification instead of letting poor data flow straight into posting or forcing every invoice into manual handling.

The Solution

Transform unstructured invoice documents into a controlled data-capture process

SupplyOn positions AI-based Document Extraction as part of its broader inbound invoicing model. Instead of treating PDFs and image files as unavoidable manual exceptions, finance teams can convert them into structured invoice data, apply validation, and feed them into the same AP process used for more mature invoice channels. That makes AI extraction a practical enabler for invoice automation, not just a scanning feature.

AI-based extraction for PDF and image invoices

SupplyOn uses AI-based document extraction to read invoice information from PDF documents and image-based invoice inputs. The goal is not simply to display the document, but to transform it into usable invoice data that can continue through the invoicing workflow. This is especially relevant for supplier populations that still rely on email attachments, scanned invoices, or mobile-captured invoice documents instead of structured XML or portal-driven submission.

Key Features
  • Extraction of invoice data from PDF documents
  • Support for image-based invoice inputs
  • Conversion of unstructured documents into structured invoice data
Impact
  • Broader digitization coverage across the supplier base
  • Less dependency on manual rekeying of invoice data
  • Faster transition from document receipt to usable invoice information
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Machine-readable output and validation readiness

The value of extraction is only realized when the result can actually be processed. SupplyOn transforms extracted content into a machine-readable invoice file that can be validated and passed into the next finance step. That matters because finance teams do not need another viewer – they need structured invoice data that can be checked against legal, business, and customer-specific rules. AI-based extraction therefore works best when combined with the broader invoicing environment for invoice validation, enrichment, and process control.

Key Features
  • Creation of machine-readable invoice output from extracted documents
  • Structured data basis for downstream validation
  • Integration into invoice-quality checks and business-rule validation
Impact
  • Higher invoice quality before ERP or AP handover
  • More consistent invoice handling across structured and unstructured inputs
  • Higher readiness for downstream automation

Human verification for uncertain cases

Not every invoice document should flow straight through based on extraction alone. SupplyOn supports human verification when the extracted result is uncertain or incomplete. This is critical in finance because the real objective is not “maximum extraction,” but reliable invoice processing. Human verification creates a controlled fallback path: high-confidence invoices move faster, while low-confidence cases are corrected before they cause posting errors, clarification loops, or supplier disputes.

Key Features
  • Human verification option and fallback path for edge cases and difficult document structures
  • Controlled handling of uncertain or incomplete document capture
  • Better balance between automation and finance-grade quality control
Impact
  • Lower risk of bad extraction data reaching AP posting
  • Better trust in AI-supported invoice capture
  • Reduced manual effort compared with fully manual document entry
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Value drivers of AI-based document extraction

AI-based document extraction brings unstructured invoices into the digital AP process. It reduces manual effort, improves data readiness, and extends automation to more suppliers.

Broader automation coverage

Bring PDF and image invoices into the digital AP process and include suppliers that are not yet ready for structured eInvoicing.

Reduced manual effort

Eliminate manual rekeying by extracting invoice data directly from documents and making it usable for downstream processing.

Higher data quality and validation readiness

Transform unstructured inputs into structured, validated invoice data to improve consistency before ERP and AP processing.

Scalable automation with controlled exceptions

Scale invoice automation across long-tail suppliers while routing low-confidence cases into human verification instead of manual fallback.

Less rekeying. More digital coverage. Better invoice data before AP touches it.

Frequently Asked Questions

AI-based Document Extraction in SupplyOn is the process of converting unstructured invoice documents such as PDFs and image files into machine-readable invoice data. It helps finance teams include non-structured invoice inputs in the digital invoicing process.

SupplyOn positions the solution for PDF invoices and image-based invoice documents. This is especially relevant for suppliers that still send invoices as email attachments, scans, or pictures instead of structured invoice files.

Standard eInvoicing starts with already structured invoice data. AI-based Document Extraction starts with unstructured documents and converts them into structured invoice data so they can enter a more controlled AP workflow.

The purpose of AI-based Document Extraction is not just text recognition. It is to extract invoice-relevant data in a way that can be transformed into a machine-readable invoice file and used in a finance process. That makes it more valuable than a simple document-reading step on its own.

Because many AP teams want one central invoice process, but too many suppliers still send PDF or image invoices. AI-based extraction helps AP digitize those invoices without forcing full manual entry or waiting for every supplier to adopt structured invoicing.

The extracted information is transformed into a machine-readable invoice file that can be validated and passed into the broader invoicing process. That means the extracted result can support downstream AP handling instead of remaining only as document text.

Make PDF and image invoices usable for modern AP automation

Connect AI-based extraction, machine-readable invoice creation, human verification, and downstream validation in one structured process — so your teams can reduce manual entry, broaden invoice digitization, and bring more supplier invoices into one controlled AP model.

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