AI Consignment Note Processing & Data Extraction Software

Automating their processes with AI

Affinda has removed the laborious workload from our accounts staff, who now focus on quality assurance and management of any outliers.

- Nathaniel Barrs, CTO, PSC Insurance

95%

reduction in manual work

10×

more invoices processed with no added staff

Enhanced auditability and tracking of invoice approvals

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Customer satisfaction is always our top priority, and Affinda has helped us achieve that by eliminating phone calls, manual handling, and delays.

- Jorg Both, Head of Business Systems, Northline

120,000

proof of delivery documents processed annually

82%

of documents straight-through processed in the first weeks

Automatic validation of documents against ERP system

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Two recruitment specialists reviewing a list of candidates

Affinda's ongoing improvements in its AI models demonstrate its innovative approach in Document AI.

– Michael Zhao, AI Product Manager, SEEK

High accuracy parsing across multiple languages
Improved customer experience thanks to better structured data
Stronger compliance with international data security and software standards

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Affinda’s support and expertise were invaluable… The experience working with Affinda was excellent.

- Nick Tran, Business Analyst, StateCover Mutual

300,000

documents processed annually

80

different document types

60%

Enhanced auditability and tracking of invoice approvals

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Logistics manager reviewing paperwork onsite

The results have spoken for themselves. I recommend Affinda to anyone looking to enhance their product or business with AI capability.

- Steve O’Keeffe, CTO, Felix

76%

reduction in manual data input

30%

reduction in compliance data errors

85,000

compliance documents processed annually

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Frequently asked questions

What is consignment note processing?

Consignment note processing is the workflow logistics and freight businesses use to capture, extract and validate shipment data from consignment notes. Our AI consignment note data extraction software automates this process to reduce manual effort, speed up consignment tracking and billing, and minimize errors. It ensures that shipment details, delivery information and reference numbers are accurately captured and recorded in your TMS, ERP and supply chain systems.

What is consignment note data extraction?

Consignment note data extraction is the process of reading a consignment note and extracting key shipment data such as consignment numbers, sender and recipient details, items, weights, delivery information and reference numbers. Our AI platform automates consignment note data extraction, converting both digital and paper documents into structured data ready for your TMS, ERP and logistics systems.

What is consignment note extraction?

Consignment note extraction is the automatic capture of shipment data from consignment notes using AI. Our consignment note extraction software combines reading order models, OCR, LLMs, RAG and more to convert this information with high accuracy and faster processing times.

What is an consignment note parser?

A consignment note parser is a software tool that automatically reads and extracts shipment data from consignment notes. It converts documents into structured, machine-readable formats ready for your systems. Our AI consignment note parser adapts with every interaction, handling variations in layout, language and format with ease while transforming the output into exactly what your TMS, ERP and logistics systems need.

What is consignment note line extraction?

Consignment note line extraction captures the shipment details within tables on your consignment notes â€“ items, weights, quantities, dimensions â€“ and converts them into structured data while preserving the relationships between each line. Our platform handles everything from simple item lists to complex nested tables with grouped items, interpreting the data with contextual understanding and accuracy.

What data fields can Affinda's AI consignment note processing software extract?

Affinda's AI consignment note processing platform can capture data from any field on a consignment note. Standard data fields include:

Shipment & Consignment Details

Consignment Number / Docket Number: Unique identifier for the shipment or consignment.
Shipment Date / Collection Date: Date the goods were collected or dispatched.
Carrier / Haulier Name: Name of the transport company or carrier handling the shipment.
Vehicle Registration / Trailer Number: Details of the vehicle or trailer used for transport.
Service Type / Mode: Type of service such as express, standard, or freight mode.

Sender & Recipient Information

Sender Name / Consignor: Name of the party dispatching the goods.
Sender Address: Full pickup or dispatch address including postcode.
Recipient Name / Consignee: Name of the party receiving the goods.
Recipient Address / Delivery Address: Full destination address including postcode.
Contact Details: Phone numbers, email addresses or contact names for sender and recipient.

Item & Cargo Details

Item Description / Goods Description: Text description of the items being shipped.
Quantity / Number of Packages: Total number of items, pallets or packages.
Weight / Gross Weight: Individual or total weight of the shipment.
Dimensions: Length, width and height measurements when provided.
Volume / Cubic Meters: Volumetric measurement of the cargo.

Delivery & Reference Information

Delivery Date / Required Date: Expected or actual delivery date.
Delivery Instructions / Special Instructions: Specific handling or delivery requirements.
Reference Numbers: Customer references, order numbers, or PO numbers.
Tracking Number: Unique tracking identifier for shipment visibility.

Other Fields

Freight Charges / Costs: Transport costs, surcharges or additional fees.
Signatures / Proof of Delivery: Captured signatures or delivery confirmation.
Notes / Remarks: Additional comments or special notes.
Document Date / Page Number: Issue date and document pagination.

Need custom fields or specific freight terminology? Simply define them in the UI or describe them in natural language and Affinda will extract and structure them automatically.

What file types does Affinda's AI consignment note processing solution support?

Our AI agents can process any file type. Supported file types include PDF, JPG/JPEG, PNG, TIFF, DOC/DOCconsignment note (Word), consignment noteLSconsignment note (Excel), HTML and Tconsignment noteT/CSV.

How does Affinda process consignment notes and extract consignment note data?

Affinda's AI agents read, extract and validate consignment note data. Our platform is intuitive to set up and easily integrates into your systems. Simply:

Upload your consignment notes via drag-and-drop, email or API.
Configure business logic to match your organization's rules and workflows.
Let Affinda check and validate extracted data against your business logic and TMS, ERP, logistics, and supply chain systems to ensure accuracy.
Access structured consignment note data directly within your systems.

The result? Faster, more accurate consignment note processing with minimal manual input.

Can Affinda extract data from scanned or image-based consignment notes?

Yes. Our AI consignment note processing platform combines OCR with retrieval augmented generation (RAG), LLMs, agentic workflows, proprietary reading order algorithms and more, to automatically detect and process data from scanned or photographed invoices (PDF, JPG, PNG). Even low-quality images are automatically enhanced for reliable data capture and processing.

What language does Affinda's AI consignment note automation platform support?

Our AI consignment note processing platform can automatically detect and process consignment notes in 50+ languages, including multilingual consignment notes containing more than one language. Supported languages include: Afrikaans, Albanian, Amharic, Arabic (Standard, Egyptian, Sudanese, Algerian, Moroccan, Levantine), Bahasa Indonesian, Bengali, Bhojpuri, Bulgarian, Burmese, Chinese (Mandarin [PRC/Taiwan], Cantonese, Wu, Min Nan, Jinyu, Xiang, Hakka), Croatian, Czech, Danish, Dutch, English, Estonian, Finnish, French, German, Greek, Gujarati, Hebrew, Hindi, Hungarian, Italian, Japanese, Javanese, Kannada, Korean, Latvian, Lingala, Lithuanian, Macedonian, Malayalam, Marathi, Nepali, Norwegian, Odia, Persian (Farsi), Polish, Portuguese, Punjabi (Western and Eastern), Romanian, Russian, Slovak, Slovenian, Somali, Spanish, Swahili, Tagalog, Tamil, Telugu, Thai, Turkish, Ukrainian, Urdu, Vietnamese, Yoruba.

Does Affinda integrate with TMS, ERP, and logistics systems?

Yes. Our AI consignment note processing platform integrates with 400+ downstream systems, including major TMS, ERP, logistics, and supply chain platforms. You can create no-code integrations using our AI integrations agent, or build your own using our APIs â€“ whatever fits your consignment note data extraction workflow best.

What are some examples of AI consignment note workflow automations?

AI consignment note processing helps automate and optimize logistics workflows across operations teams such as:

Logistics Operations: Speed up consignment tracking and improve shipment visibility by extracting sender, recipient, delivery details and reference numbers from any consignment note format. Business-rule validation flags discrepancies like missing delivery dates, incorrect weights or duplicate consignment numbers.
Freight and Billing Teams: Accelerate billing cycles and reduce errors by automatically capturing freight charges, item details and weights â€“ even from complex multi-page notes with grouped cargo tables.
Supply Chain and Compliance: Use self-learning AI that adapts to new consignment note layouts, ensuring accurate delivery instructions, special handling requirements and regulatory data are captured every time.
TMS and ERP Teams: Feed structured consignment note data directly into your transport management and enterprise systems to enhance operational control, compliance reporting and scalability.

What is a consignment note OCR data extractor?

A consignment note optical character recognition (OCR) data extractor scans and accurately captures shipment information from consignment notes, regardless of format or language. Upload consignment note documents in PDF, JPG or PNG formats. The OCR technology first converts the documents into a text layer, ensuring all text (even from scans, photos or handwriting) is captured. Affinda's AI models then identify and extract key fields such as consignment numbers, sender and recipient details, items, weights, delivery information and reference numbers, transforming them into structured, usable data.

This automation eliminates manual data entry, reduces errors and saves time. Once the consignment note data is captured and structured, our AI consignment note processing pipeline can apply machine validation and post-processing to enable seamless integration with TMS, ERP, logistics and supply chain systems.

Businesses in logistics, shipping and freight rely on Affinda's AI for their consignment tracking, billing and supply chain processes, streamlining workflows and improving overall efficiency.

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The AI platform for consignment note processing

How to automate consignment note processing with Affinda's AI

Upload your consignment notes, your way

Watch as it extracts your consignment note data

Automatically route the data to your systems

Extract any information from any document, fast

Create models in seconds

Cleanse and transform data

Apply business logic

Affinda's AI reads, understands and extracts data from any consignment note or document

Pathway 1: Use our AI integrations agent

Pathway 2: Write your own code

Get AI agents to process your consignment notes

Automate consignment note processing with 99%+ accuracy

See ROI in weeks, not months

AI that instantly learns from your consignment note and adapts

Easy integration, zero disruption

Configure your consignment note model, customize and maintain control

Enterprise-grade security

Combine the best of artificial and human intelligence

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Automating their processes with AI

95%

10×

120,000

82%

300,000

80

60%

76%

30%

85,000

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