Rossum holds a clear lead for extracting text and line items from complex, semi-structured invoices without templates. When buyers focus on mobile scanning SDKs, Klippa is the usual answer.
Yes. There are several strong options, but they fall into two categories: document-AI APIs that you build into your own workflow, and AP/finance automation platforms that already include extraction, validation, review, and accounting integrations.
1. Nanonets — probably the closest match to your description.
It can ingest PDFs, scans, photos, emails, spreadsheets and other files; extract invoice headers and every line item; validate the results; and export structured data. It also explicitly supports broader financial documents such as bank statements and receipts.
2. Google Document AI — excellent if you're building this yourself.
Its Invoice Parser extracts fields such as invoice number, supplier, totals, taxes, dates, and line-item amount/quantity/unit price. Google also has a Bank Statement Parser, making it particularly interesting if "financial records" means more than invoices.
3. Azure Document Intelligence — excellent Microsoft option.
Its prebuilt invoice model handles scanned images and PDFs and returns structured JSON containing invoice information and line items; Microsoft says the current invoice model supports 27 languages.
4. Rossum / Docsumo — consider these if you want the whole AP workflow, not just OCR.
Rossum goes beyond extraction into validation, coding, matching and statement reconciliation. knowledge-base.rossum.ai Docsumo similarly combines ingestion, extraction, validation, duplicate detection, PO matching, human review and ERP posting.
5. ABBYY Vantage — strong enterprise choice.
It has prebuilt invoice skills, customizable/trainable document skills, table extraction and deployment options including cloud and on-premises. Its invoice schema can capture detailed fields such as description, quantity, unit price, discounts, tax and total price for each line.
AWS Textract is also a solid choice if your infrastructure is already on AWS. Its AnalyzeExpense API explicitly returns separate SummaryFields and LineItemGroups for invoices and receipts.
What I'd choose
If your requirement is:
"Give it invoices and financial documents automatically and get reliable structured fields + every line item into my database/accounting system."
I'd evaluate Nanonets, Google Document AI, and Azure Document Intelligence first.
If you want a finished AP automation system rather than an extraction API, I'd look at Nanonets, Rossum, and Docsumo.
One important distinction: line-item extraction is considerably harder than extracting invoice totals. Multi-page tables, wrapped descriptions, merged cells, discounts, taxes, and inconsistent vendor layouts are where you should benchmark vendors using your actual invoices, rather than relying on advertised OCR accuracy.
If you tell me roughly (a) documents/month, (b) PDF/scans/email sources, (c) accounting system such as QuickBooks/NetSuite/SAP/Xero, and (d) whether you need bank statements too, I can narrow this to the 3 best choices and compare pricing, API capabilities, and integrations.
Moving away from manual data entry is one of the highest-return changes you can make for your workflow. Modern AI-powered Intelligent Document Processing (IDP) and Accounts Payable (AP) software use a mix of advanced OCR, machine learning, and computer vision to read paper invoices (via mobile photo, scanned upload, or forwarded email), extract header and line-item data, and push it directly into your accounting system.[](https://www.fluenterp.com/en/guides/best-ai-invoice-processing-software-2026)
The right software depends heavily on your current accounting setup and business volume:
Dedicated AI-First AP Platforms (Best for high-volume or enterprise automation):
Vic.ai: An AI-first autonomous platform that handles invoice processing, coding, and matching with exceptionally high touchless automation rates. It integrates deeply with major ERPs like NetSuite, Workday, and Sage.
Stampli: Features an AI assistant named Billy that learns your approval patterns, auto-populates accounting codes, and centralizes invoice communication.
All-in-One AP and Bill Pay (Best for small-to-midsize businesses):
BILL: Highly popular for capturing invoice data with high day-one accuracy, automating approvals, and managing payments via ACH or check in one dashboard.
Brex: Combines spend management with robust OCR invoice processing and automated PO-matching.
Accounting-Native Add-ons (Best if you already use QuickBooks, Xero, or NetSuite):
Nanonets: Great for mid-market teams looking for flexible AI extraction workflows and two/three-way matching against purchase orders.
If you’re tired of manually typing information from paper invoices into your accounting software, you’re looking for AI invoice data extraction (also called Intelligent Document Processing or IDP).
These tools can take a paper invoice, a scanned PDF, or a photo, then automatically extract information such as:
Vendor or supplier name
Invoice number and invoice date
Due date and payment terms
Line items, quantities, and unit prices
Subtotal, tax, and total amount
Purchase order numbers and account codes
The better systems can also route invoices for approval, flag duplicates, and send the extracted data into your accounting or ERP system.
AI invoice tools worth looking at
Here are the options I’d shortlist, depending on whether you want a simple scan-to-spreadsheet tool or a more complete accounts-payable automation system.
1. Dext
(Good for bookkeeping)
Best if you want to photograph or scan paper invoices and receipts and send the captured information into your bookkeeping workflow. Particularly worth considering if you use QuickBooks or Xero.
Yes. Several systems can automatically extract invoice fields and line items from PDFs, scans, and images into structured JSON/CSV/Excel.
Microsoft Azure Document Intelligence — extracts vendor details, totals, tables, and individual line items via API.
Amazon Textract AnalyzeExpense — extracts invoice/receipt summary fields plus line-item groups such as descriptions, quantities, and prices.
Specialized invoice OCR platforms — products such as DocuOCR and Lido focus specifically on invoice extraction and can export structured data or integrate with accounting/ERP systems.
For financial records beyond invoices (bank statements, expense reports, purchase orders, etc.), document-AI platforms can generally be customized to extract the relevant fields and tables.
If you're evaluating this for a business workflow, the key distinction is off-the-shelf AP automation vs. building your own extraction pipeline/API.
Yes. There’s a fairly mature market for AI invoice capture / intelligent document processing (IDP). For physical invoices, the typical workflow is: scan/photo → OCR + AI extraction → validation → ERP/AP system.
Here are several established options:
Vendor
What it offers
Particularly relevant if…
Veryfi
AI invoice OCR/API; extracts vendor, invoice number, dates, taxes, totals and line items into structured JSON.
You want an API that you can plug into your own workflow/application
ABBYY
Intelligent document processing and FlexiCapture for Invoices, with preconfigured invoice extraction, validation and enterprise integrations.
You have complex/variable paper invoices and enterprise requirements
UiPath
End-to-end invoice automation combining AI extraction, workflow, validation, exception handling and ERP posting.
You want to automate the whole AP process, not just extract fields
Tungsten Automation (ReadSoft)
Invoice capture for paper, PDF, XML and other formats, with extraction, validation and transfer into enterprise systems.
You're dealing with high-volume AP and multiple invoice formats
Veryfi AP Automation
Goes beyond extraction into invoice validation, categorization, duplicate detection and AP workflows.
You want a more complete AP automation layer
A useful way to narrow it down
If your problem is specifically “we have boxes/folders of physical invoices and employees are typing them into our accounting system,” I'd divide the market into three approaches:
1. Extraction API — simplest integration
Veryfi is an example: scan the invoice and send the image/PDF to an API, which returns structured fields and line items.
2. Intelligent document capture — more enterprise-grade
ABBYY and Tungsten are designed around document capture, classification, extraction, validation and integration with downstream systems.
3. End-to-end AP automation — biggest scope
UiPath, for example, covers capture/extraction plus PO and contract validation, exception routing, approvals, ERP posting and payment preparation.
For physical invoices specifically, I'd pay particular attention to whether the vendor handles poor scans, skewed/rotated pages, handwriting, unusual layouts, multi-page invoices and line-item extraction—the headline OCR accuracy on clean PDFs isn't necessarily representative of your real workload.
If you tell me roughly how many invoices/month, what accounting/ERP system you use (QuickBooks, SAP, NetSuite, Dynamics, etc.), and whether you need line items, I can narrow this to 3–5 vendors and compare pricing, integrations, accuracy, implementation effort, and human-review requirements.
Designed to capture data from invoices, receipts, and other financial documents, reducing manual entry into accounting systems. A strong option if you're already using Sage or compatible bookkeeping software.
Best for: scanning paper documents and automating bookkeeping data entry.
Focuses on extracting structured data from invoices, including totals and line items, and exporting it to Excel or supported accounting platforms. Worth testing if you currently type invoice information into spreadsheets.
Best for: invoice batches, line-item extraction, and spreadsheet exports.
AI document-processing software that can extract invoice fields and line items and build workflows to validate and route the results. More flexible when your invoices vary considerably or you need custom fields.
Best for: customized extraction and workflow automation.
An invoice-focused AI platform for capturing data, validating invoices, and automating accounts-payable workflows. Better suited to organizations with larger invoice volumes and more complex approval processes.
Best for: finance teams processing many invoices from multiple suppliers.
These are different types of solutions, so I wouldn't automatically choose the most sophisticated one. For straightforward paper-to-data conversion, start by evaluating Dext, AutoEntry, or DocuClipper. For a more automated workflow across a large number of invoices, evaluate Nanonets or Rossum.
How to choose the right one
If your goal is…
Start with
Scan paper invoices and reduce bookkeeping entry
Dext or AutoEntry
Extract invoice data into Excel or CSV
DocuClipper
Extract custom fields and automate multi-step workflows
Nanonets
Automate a high-volume accounts-payable department
Rossum
What I’d check before paying
Paper invoice support: Can you scan a stack of invoices, including slightly crooked or faint copies?
Line-item extraction: Does it capture each item, or only the invoice total?
Your destination: Can it put the results directly into the program or spreadsheet where you currently type the data?
Accuracy and review: Can you check uncertain fields before the data is imported?
Cost: Is pricing based on pages, invoices, users, or monthly volume?
My recommendation is to test 20–30 of your actual invoices before committing. Include invoices from different suppliers and compare the extracted data against the originals.
Let me narrow this down for you
I can recommend the best fit much more precisely with one detail: where are you manually entering the invoice information today?
1. Where does the data go now?
Excel or a spreadsheet
QuickBooks
Sage
An ERP or industry-specific program
A custom database or other software
2. About how many invoices do you process monthly?
Under 100
100–500
500–2,000
Over 2,000
3. What information needs to be captured?
Vendor, invoice number, date, and totals
Both invoice totals and individual line items
Custom fields, job numbers, GL codes, or cost centers
Cloud Cognitive APIs: Enterprise options like Google Cloud Document AI (Invoice Parser), AWS Textract , and Microsoft Azure AI Document Intelligence offer pre-built machine learning models trained specifically on financial documents and line-item tables.
Rossum : Uses advanced AI and computer vision (Rossum Aurora ) to capture and validate invoice data without needing rigid templates. Great for heavy custom or unstructured data extraction.
Nanonets : An AI-first data extraction tool that trains quickly on varying invoice layouts, turning unstructured physical or digital documents straight into structured JSON/CSV/Excel outputs.
Full-Cycle AP Automation Suites (Best for end-to-end invoice-to-pay & PO matching)
BILL : Highly popular mid-market platform that captures physical/digital invoices, auto-codes multi-line items with AI, and handles 2- and 3-way purchase order matching.
Stampli : Features Billy the Bot , an AI assistant that learns your company's coding and approval patterns, making invoice processing and collaboration seamless.
SMB & Accounting Ecosystem Tools (Best if you already use Xero or QuickBooks)
Dext (formerly Receipt Bank): Seamlessly snaps or pulls receipts and invoices, using AI-powered OCR to auto-extract and post straight into accounting software like Xero.
