12 Best Bill of Lading Software Solutions for Shipping and Logistics in 2026

A bill of lading may show a different cargo quantity from the packing list, or a container number may not match the freight invoice. Resolving these discrepancies requires teams to locate related documents, verify details, and make corrections. The best bill of lading software addresses these challenges through document creation, data extraction, validation, and automation.

Some platforms focus on electronic signatures and document distribution, while others handle data extraction, reconciliation, or freight operations. The right choice depends on your workflow needs. For this listicle, we tested more than twenty platforms based on BOL processing, data validation, exception management, integrations, and document retrieval.

We shortlisted twelve platforms that address different shipping documentation, intelligent document processing, and freight automation requirements.

Best Bill of Lading Software at a Glance

Our List of Best Bill of Lading Software

We evaluated these twelve platforms against the tasks involved in bill of lading processing, including document creation, field extraction, shipment validation, exception handling, and data delivery.

1. Collatio by Scry AI

Collatio by Scry AI provides intelligent document processing for enterprises that need to extract, validate, and reconcile information across bills of lading and related shipping records. Its bill of lading software processes master and house BOLs, sea waybills, air waybills, and supporting trade documents from different carriers.  

The platform uses OCR, natural language processing, and contextual document interpretation to extract shipper details, container numbers, cargo descriptions, seal identifiers, ports, and freight terms. It handles scanned documents, PDFs, and carrier-specific layouts without requiring separate templates for every format.

It compares extracted BOL information with packing lists, commercial invoices, purchase orders, customs declarations, and carrier confirmations to identify missing or inconsistent details. Configurable validation rules flag discrepancies, while human reviewers can examine uncertain fields against the original documents. After validation, Collatio delivers structured information into connected TMS, ERP, and customs applications.

Pros and Cons

Key Features

• Multi-format ingestion: Processes PDFs, scans, emails, and carrier-specific layouts
• Data extraction: Captures shipment details, container numbers, cargo, ports, and freight terms
• Cross-document reconciliation: Compares BOLs with invoices, packing lists, purchase orders, and customs records
• Validation rules: Flags missing fields, duplicate references, discrepancies, and unusual changes
• Human review: Routes uncertain data and exceptions for verification
• Document integrity checks: Detects inconsistencies and potentially suspicious amendments
• Enterprise integration: Sends validated data to TMS, ERP, and customs systems via APIs
• Audit trails: Tracks processing activities, document versions, and review actions

2. SmartBOL

SmartBOL helps warehouses, manufacturers, and distribution centers create, sign, and distribute shipping documents, including VICS and master bills of lading, packing slips, and hazardous materials documentation. Drivers can sign through kiosks, tablets, or QR codes. For teams seeking bill of lading tracking software, SmartBOL also provides searchable access to signed documents, shipment photos, and statuses through its cloud portal.

Pros and Cons

Key Features

• BOL generation: Creates VICS BOLs, master BOLs, packing slips, and HazMat documentation
• Electronic signatures: Collects driver signatures through kiosks, tablets, and QR-based interfaces
• Multi-document signing: Applies one driver signature across documents associated with a shipment
• Shipment photo capture: Attaches photographs and comments to shipping records
• Cloud document retention: Stores signed documents for retrieval and distribution
• Automated document sharing: Sends completed records to carriers, brokers, and relevant teams
• APIs and webhooks: Connects shipment events with ERP, WMS, and TMS applications

3. ABBYY Vantage

ABBYY Vantage is an intelligent document processing platform that uses AI-powered skills to classify, extract, and validate information from business documents. Its skill catalog includes document processing capabilities for bills of lading, invoices, purchase orders, receipts, and delivery notes. Organizations can use Document Skills and Skill Designer to configure extraction requirements for specific document layouts. Process Skills coordinate classification, extraction, verification, and downstream activities.

Pros and Cons

Key Features

• Document Skills: Uses pretrained and configurable models to extract business document information
• Skill Designer: Creates and trains custom extraction skills for specific document requirements
• Classification Skills: Identifies incoming document types before processing
• Document assembly: Separates and organizes documents within combined files
• Human verification: Allows reviewers to correct extracted information
• Continuous learning: Uses reviewed document examples to refine extraction skills
• Automation integrations: Connects with Microsoft Power Automate, UiPath, Automation Anywhere, and other systems

4. Google Document AI

Google Document AI provides document processing APIs for extracting, classifying, and organizing information from PDFs, scanned records, and other business documents. Its Custom Extractor can capture selected BOL fields, such as shipment references, carrier details, cargo descriptions, and container information. Custom Classifier identifies document categories, while Custom Splitter separates combined document packets. Enterprise Document OCR extracts text and document layouts.

Pros and Cons

Key Features

• Custom Extractor: Captures selected shipment fields using configurable extraction schemas
• Custom Classifier: Identifies document categories using predefined or trained models
• Custom Splitter: Separates combined document packets into individual records
• Enterprise Document OCR: Extracts text and layout information from scanned documents
• Document AI Workbench: Supports processor configuration, training, and evaluation
• Confidence scores: Provides indicators for reviewing uncertain processing results
• Processing APIs: Connects extracted document information with custom applications

5. Lido

Lido converts information from PDFs, scanned documents, images, and emails into structured spreadsheet data. Its extraction capabilities support bills of lading with different carrier layouts, including documents that contain handwritten information. Users can specify required fields, process incoming files, and organize extracted shipment details in a spreadsheet-style interface. Lido also supports recurring workflows through cloud storage, email, and API connections.

Pros and Cons

Key Features

• Document Data Extractor: Captures specified fields from PDFs, images, scans, and emails
• Layout-independent extraction: Processes documents with different structures and field positions
• Handwriting recognition: Extracts information from handwritten document content
• Spreadsheet interface: Organizes extracted shipment details into structured rows and columns
• Cloud ingestion: Receives files through Google Drive, OneDrive, and email
• Workflow builder: Automates document collection, extraction, and subsequent actions
• Extraction API: Allows applications to submit documents and receive structured results

6. Shipamax

Shipamax specializes in extracting information from freight documents and automating repetitive logistics tasks. Its technology converts data from PDFs, scanned documents, images, and emails into machine-readable records. The platform was developed for freight forwarding and customs brokerage operations, including forwarding job creation, shipment data entry, and accounts payable invoice processing. It is relevant to freight organizations that want to automate document-based activities.

Pros and Cons

Key Features

• Freight document ingestion: Processes PDFs, scans, images, and email attachments
• AI data extraction: Converts unstructured freight information into machine-readable records
• Forwarding job creation: Uses extracted shipment details to support operational job creation
• Customs brokerage processing: Applies document information to customs-related tasks
• AP invoice processing: Extracts information from freight-related invoices
• Operational workflow automation: Uses extracted data to support recurring forwarding activities

7. Expedock

Expedock currently focuses on managed remote teams for logistics and other industries. Its service offering covers recurring operational activities, including documentation, administrative support, accounting, and customer service. Expedock previously developed freight automation technology for extracting and exchanging shipment information. Its published API documentation describes shipment records, customs declarations, invoices, commercial documents, and connections with transportation management systems.

Pros and Cons

Key Features

• Managed logistics teams: Provides remote personnel for recurring freight operations
• Documentation support: Covers administrative tasks associated with shipment records
• Accounting support: Supplies personnel for billing and back-office activities
• Team management: Handles recruitment, payroll, benefits, and personnel administration
• Operations oversight: Provides dedicated managers for remote teams

8. Raft

Raft provides AI-assisted operational workflows for freight forwarders, customs brokers, and logistics teams. Its platform combines document extraction, shipment information, business rules, and specialized agents for recurring freight activities. Extraction Studio processes logistics documents, while Shipment Navigator consolidates emails, transportation management records, carrier updates, and internal communications. Workitems tracks individual operational tasks, including invoice matching and document validation. Raft also supports customs data extraction, request classification, and workflow coordination across departments.

Pros and Cons

Key Features

• Extraction Studio: Extracts structured information from freight documents
• Intelligent Inbox: Classifies incoming emails, documents, and operational requests
• Shipment Navigator: Consolidates shipment records, carrier updates, and communications
• Workitems: Tracks individual tasks such as invoice matching and document validation
• Customs data extraction: Captures information required for customs-related workflows
• Workflow orchestration: Applies operating procedures and business decision rules
• Collaboration and audit records: Records operational actions and team decisions

9. Nanonets

Nanonets provides AI-powered document extraction and workflow automation for logistics, finance, and business operations. Its dedicated Bill of Lading OCR model extracts shipment references, shipper information, carrier details, container numbers, ports, weights, and other freight fields. The platform includes pretrained extraction capabilities and configurable models for additional document requirements. Users can process PDFs, scanned records, email attachments, and documents received through connected applications. Nanonets also supports validation, approvals, and structured data delivery.

Pros and Cons

Key Features

• Pretrained BOL OCR: Extracts common shipment fields from bills of lading
• Custom field extraction: Captures organization-specific information beyond predefined fields
• Line-item processing: Extracts cargo descriptions, quantities, and weights
• Multi-source ingestion: Accepts PDFs, images, scans, emails, and cloud storage files
• Human review: Allows users to verify and correct extracted information
• Workflow configuration: Supports validation rules, approvals, and data processing steps
• System integrations: Delivers structured information through APIs and connected applications

10. Extend.ai

Extend.ai provides document processing APIs for developers and enterprise teams that need structured information from complex files. Its logistics capabilities cover bills of lading, proofs of delivery, packing lists, freight invoices, and customs records. Extend combines document parsing, classification, extraction, splitting, and configurable processing workflows.

Development teams define extraction schemas and receive structured outputs with confidence indicators and references to source documents. Its logistics offering also distinguishes BOLs from proof-of-delivery records and handles shipment information across different carrier layouts.

Pros and Cons

Key Features

• Document parsing: Converts complex document content into structured information
• Schema-based extraction: Returns selected shipment fields in defined JSON structures
• Document classification: Distinguishes BOLs, PODs, invoices, and other records
• Document splitting: Separates combined files into individual document types
• Confidence scoring: Identifies extracted values that require further review
• Processing modes: Supports different configurations for speed, cost, and accuracy requirements
• APIs and SDKs: Supports application development using several programming languages
• Source references: Connects extracted values with supporting document content

11. Vector

Vector provides digital bill of lading software that connects shipping documentation with carrier communication and facility operations. Its eBOL solution supports electronic signatures, document capture, and proof-of-delivery workflows. Shippers, carriers, and consignees can access shipment records, share documents, and receive status updates through connected channels. The platform also supports discrepancy resolution, making it useful for transportation networks that need better coordination across shipping activities.

Pros and Cons

Key Features

• Electronic BOL: Supports digitally signed shipping records at origin and destination
• Paper BOL digitization: Converts existing paper records into structured electronic information
• Proof of delivery: Supports delivery documentation and confirmation workflows
• Document sharing: Provides electronic records through portals and email
• Shipment status notifications: Sends updates about shipment progress
• Issue resolution: Supports collaboration around shipping discrepancies
• Digital Gate: Connects driver check-in with facility activities
• Yard management: Coordinates vehicle movements and operational status

12. M.Folio by Matilda Technologies

M.Folio by Matilda Technologies supports electronic bills of lading and warehouse execution activities for distribution centers, warehouses, and third-party logistics providers. Its eBOL functionality replaces paper shipping documents with digital records that drivers can sign through mobile devices or self-service kiosks. The platform also connects document processing with driver check-in, yard operations, and dock activities. Matilda’s broader offering includes dock scheduling, fulfillment analytics, and 3PL billing.

Pros and Cons

Key Features

• Electronic BOL processing: Creates, signs, and stores digital shipping documents
• Multi-document signatures: Applies one driver signature across several BOLs
• Self-service signing: Supports driver signatures through kiosks and mobile workflows
• Document archiving: Stores electronic BOLs in searchable records
• Audit history: Records signature information and document changes
• Driver check-in: Connects shipping paperwork with arrival and departure activities
• Yard management: Supports vehicle movement and dock coordination
• Enterprise integrations: Connects warehouse operations with existing management systems

How to Choose the Best Bill of Lading Software

The right bill of lading software depends on how your team handles shipping documents and where delays occur. Before comparing platforms, consider the following factors to find one that fits your operations.

1. Map your bill of lading workflow

Start by identifying which tasks take the most time. Warehouse teams may need faster document creation and electronic signatures, while freight forwarders may prioritize extraction. Finance teams often need stronger validation and invoice reconciliation capabilities.

2. Examine document formats and extraction quality

Next, consider the documents your team receives daily. The software should handle scanned PDFs, emails, handwritten records, and different carrier layouts. Test actual BOLs to see how accurately it captures container numbers, cargo quantities, weights, and consignee details.

3. Review integrations and workflow automation

Extracted information needs to reach the right systems. Check whether the platform connects with your TMS, WMS, ERP, and customs applications. Also, assess whether it can assign tasks, update shipment records, and transfer approved data without repeated manual entry.

4. Evaluate document controls and governance

As shipping documents pass between teams, it should be clear who can access, edit, and approve them. Look for role-based permissions, version histories, and audit trails that show when information was corrected and who approved the changes.

5. Test exception handling capabilities

Not every BOL will contain complete or matching information. Check whether the software identifies missing fields, incorrect quantities, and duplicate references. Your team should also be able to review original documents and resolve discrepancies before processing continues.

6. Compare reporting and document visibility

Finally, consider how easily managers can monitor operations. Look for reports on document volumes, pending approvals, processing status, and recurring errors. The platform should also make it easy to retrieve shipping records and identify unresolved issues across departments.