Dangerous Goods Declaration OCR

[ Dangerous Goods Declaration OCR ]

Automate Dangerous Goods Declaration OCR for Faster, Error-Free Compliance

Use LlamaParse to capture every field accurately from DG forms, then validate and export structured data.

Parse Dangerous Goods Declarations into Structured Data

LlamaParse turns dangerous goods declarations into clean, structured JSON or Markdown, capturing UN numbers, packing groups, quantities, and handling instructions reliably. Agentic document parsing understands messy layouts and stamps, adds citations and confidence scores, and reduces manual checks so shipments clear faster.

Best-in-Class Accuracy

Dangerous Goods Declaration OCR for Every Stakeholder

Freight Forwarding and Customs Brokerage

Use LlamaParse in LlamaCloud to parse Dangerous Goods Declarations into structured JSON with line-item UN numbers, packing groups, quantities, and signatures—without brittle template rules when shippers change layouts. Layout-aware table extraction plus metadata (page + coordinates) enables fast exception review and reduces customs holds caused by missing or inconsistent DG fields.

Chemical Manufacturing and Distribution

Automatically ingest supplier DG declarations and reconcile them against internal product master data so downstream shipping labels, SDS packets, and load plans are generated from the same source of truth. Multimodal parsing handles stamps, checkboxes, and dense multi-column tables, cutting manual QA time and preventing costly non-compliant shipments.

Airlines and Ground Handling Operations

Parse DG paperwork at acceptance to validate critical fields (proper shipping name, hazard class, net quantity, aircraft limitations) before freight enters the network, even when scans are skewed or low quality. Auto-correction loops and confidence scores surface only the risky consignments for manual review, improving on-time departures while tightening compliance.

Logistics and Compliance Startups

Ship a DG-declaration extraction feature quickly by calling LlamaParse APIs with natural-language parsing instructions to output the exact schema your app needs—no custom parsers to maintain. Tier-based agentic processing keeps unit economics predictable by reserving higher-accuracy parsing for complex pages while standard forms flow through cheaper modes.

The Solution

Dangerous Goods Declaration OCR Features for Accurate, Auditable Data Extraction

01

Layout-Aware Form Parsing

LlamaParse understands document layout so it can preserve reading order across headers, footers, multi-column sections, and stamped fields. For dangerous goods declarations, this keeps key fields like UN number, proper shipping name, hazard class, packing group, quantities, and signatures mapped to the right labels instead of getting scrambled.

02

Reliable Table Extraction

LlamaParse accurately reconstructs complex tables into clean, structured output rather than flattened text. That’s critical for dangerous goods declarations where line items, packaging details, and quantity units must stay aligned for downstream validation and filing.

03

Validation & Self-Correction Loops

LlamaParse runs validation steps and self-correction loops to reduce common extraction errors from poor scans, skewed pages, and noisy backgrounds. In dangerous goods workflows, this improves straight-through processing by catching inconsistencies like mismatched units, missing fields, or malformed UN identifiers before they hit your system.

04

JSON Output With Citations

LlamaParse can emit structured JSON with granular metadata like page numbers and coordinates for each extracted field. For dangerous goods declarations, this makes it easy to populate compliance systems and provide auditable citations back to the exact spot on the document for human review.

Technical OCR documentation

Agentic OCR, documented for builders.

Explore our developer guides to easily connect your document pipelines to LlamaParse.

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Eliminate Human Error

Our AI catches the typos that tired eyes miss.

Format Flexibility

Export to Excel, JSON, XML, or directly via API.

Enterprise-Grade Security

SOC2 Type II compliant with end-to-end encryption.

No-Code Templates

Train the tool on your specific forms in minutes, not days.

Lightning Speed

Average processing time of <3 seconds per page.

LlamaParse’s support of a wide variety of filetypes and its accuracy of parsing made it the best tool we tested in our evaluations. The LlamaIndex team was very responsive and we were off to the races within a day.

Turn data chaos into data clarity.

Parse your documents free. 10,000 credits to start.

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Common FAQs

How Does it Work?

01

Will the OCR keep critical dangerous goods fields mapped correctly, even on messy forms?

Yes—layout-aware parsing preserves reading order across headers, footers, multi-column sections, and stamped or handwritten fields. This helps ensure UN number, proper shipping name, hazard class, packing group, quantities, and signatures stay tied to the right labels instead of shifting or merging.

02

How do you handle tables with multiple line items, packaging types, and quantity units?

We reliably reconstruct complex tables into structured output, keeping rows, columns, and units aligned. That means your line items and packaging details remain consistent for downstream validation, filing, and integration with compliance workflows.

03

What happens when scans are skewed, low-quality, or have noisy backgrounds?

The system runs validation and self-correction loops to reduce common extraction errors caused by poor scans and distortions. It can flag or correct issues like malformed UN identifiers, missing required fields, or inconsistent units before they reach your operational systems.

04

Can I get structured JSON output that’s ready for my compliance or TMS systems?

Yes—output is available as clean, structured JSON designed for straightforward ingestion into compliance platforms, TMS/ERP tools, or internal databases. This minimizes manual rekeying and speeds up straight-through processing for dangerous goods documentation.

05

Do you provide auditability—can reviewers see exactly where each extracted value came from?

Yes—each extracted field can include citations such as page number and coordinates, so reviewers can jump directly to the source on the document. This supports audit trails and faster approvals without relying on guesswork.

06

How does this reduce manual review time without increasing compliance risk?

By preserving layout, accurately extracting tables, and validating key fields, the system reduces the most common causes of rework and exceptions. Your team reviews only what’s uncertain, with clear citations—so you move faster while keeping documentation defensible.